ICLR 2024
2260 papers
#InsTag: Instruction Tagging for Analyzing Supervised Fine-Tuning of Large Language Models
Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, Jingren Zhou $\pi$2vec: Policy Representation with Successor Features
Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci, Thomas Paine, Yutian Chen, Misha Denil $\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
Yining Jiao, Carlton Jude Zdanski, Julia S Kimbell, Andrew Prince, Cameron P Worden, Samuel Kirse, Christopher Rutter, Benjamin Shields, William Alexander Dunn, Jisan Mahmud, Marc Niethammer 3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yuqi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang, Xin Tong, Yang Liu, Qixing Huang 3D Reconstruction with Generalizable Neural Fields Using Scene Priors
Yang Fu, Shalini De Mello, Xueting Li, Amey Kulkarni, Jan Kautz, Xiaolong Wang, Sifei Liu A Benchmark for Learning to Translate a New Language from One Grammar Book
Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu A Branching Decoder for Set Generation
Zixian Huang, Gengyang Xiao, Yu Gu, Gong Cheng A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler, Pablo Piantanida A Framework for Inference Inspired by Human Memory Mechanisms
Xiangyu Zeng, Jie Lin, Piao Hu, Ruizheng Huang, Zhicheng Zhang A Graph Is Worth 1-Bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen A Hard-to-Beat Baseline for Training-Free CLIP-Based Adaptation
Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan A Neural Framework for Generalized Causal Sensitivity Analysis
Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar A Plug-and-Play Image Registration Network
Junhao Hu, Weijie Gan, Zhixin Sun, Hongyu An, Ulugbek Kamilov A Precise Characterization of SGD Stability Using Loss Surface Geometry
Gregory Dexter, Borja Ocejo, Sathiya Keerthi, Aman Gupta, Ayan Acharya, Rajiv Khanna A Probabilistic Framework for Modular Continual Learning
Lazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles Sutton A Quadratic Synchronization Rule for Distributed Deep Learning
Xinran Gu, Kaifeng Lyu, Sanjeev Arora, Jingzhao Zhang, Longbo Huang A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis
Izzeddin Gur, Hiroki Furuta, Austin V Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust A Recipe for Improved Certifiable Robustness
Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson A Restoration Network as an Implicit Prior
Yuyang Hu, Mauricio Delbracio, Peyman Milanfar, Ulugbek Kamilov A Robust Differential Neural Ode Optimizer
Panagiotis Theodoropoulos, Guan-Horng Liu, Tianrong Chen, Augustinos D Saravanos, Evangelos Theodorou A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Edward Carlyn, Samuel Stevens, Kaiya L Provost, Anuj Karpatne, Bryan Carstens, Daniel Rubenstein, Charles Stewart, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Lei Sha, Cornelius Emde, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz A Sublinear Adversarial Training Algorithm
Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng, Neil Shah, Tyler Derr A Unified Framework for Bayesian Optimization Under Contextual Uncertainty
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco, Remi Monasson Accelerating Sinkhorn Algorithm with Sparse Newton Iterations
Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil, Tesi Xiao, Lexing Ying Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi, Mark Heimann, Rushil Anirudh, Danai Koutra, Jayaraman J. Thiagarajan Accurate Forgetting for Heterogeneous Federated Continual Learning
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang, Kunda Yan, Bo Han, Gang Niu, Lei Fang, Changshui Zhang, Masashi Sugiyama Achieving Human Parity in Content-Grounded Datasets Generation
Asaf Yehudai, Boaz Carmeli, Yosi Mass, Ofir Arviv, Nathaniel Mills, Eyal Shnarch, Leshem Choshen Active Retrosynthetic Planning Aware of Route Quality
Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang, Fei Wu AdaMerging: Adaptive Model Merging for Multi-Task Learning
Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao Adapting to Distribution Shift by Visual Domain Prompt Generation
Zhixiang Chi, Li Gu, Tao Zhong, Huan Liu, Yuanhao Yu, Konstantinos N Plataniotis, Yang Wang Adaptive Federated Learning with Auto-Tuned Clients
Junhyung Lyle Kim, Taha Toghani, Cesar A Uribe, Anastasios Kyrillidis Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill Adaptive Rational Activations to Boost Deep Reinforcement Learning
Quentin Delfosse, Patrick Schramowski, Martin Mundt, Alejandro Molina, Kristian Kersting Adaptive Regret for Bandits Made Possible: Two Queries Suffice
Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David Woodruff, Elad Hazan Adaptive Self-Training Framework for Fine-Grained Scene Graph Generation
Kibum Kim, Kanghoon Yoon, Yeonjun In, Jinyoung Moon, Donghyun Kim, Chanyoung Park Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
Anna Bair, Hongxu Yin, Maying Shen, Pavlo Molchanov, Jose M. Alvarez Adaptive Window Pruning for Efficient Local Motion Deblurring
Haoying Li, Jixin Zhao, Shangchen Zhou, Huajun Feng, Chongyi Li, Chen Change Loy ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process
Changyao Tian, Chenxin Tao, Jifeng Dai, Hao Li, Ziheng Li, Lewei Lu, Xiaogang Wang, Hongsheng Li, Gao Huang, Xizhou Zhu ADOPD: A Large-Scale Document Page Decomposition Dataset
Jiuxiang Gu, Xiangxi Shi, Jason Kuen, Lu Qi, Ruiyi Zhang, Anqi Liu, Ani Nenkova, Tong Sun Advancing the Lower Bounds: An Accelerated, Stochastic, Second-Order Method with Optimal Adaptation to Inexactness
Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov, Ali Kavis, Kimon Antonakopoulos, Volkan Cevher, Martin Takáč Adversarial Attacks on Fairness of Graph Neural Networks
Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li Adversarial AutoMixup
Huafeng Qin, Xin Jin, Yun Jiang, Mounîm El-Yacoubi, Xinbo Gao Adversarial Causal Bayesian Optimization
Scott Sussex, Pier Giuseppe Sessa, Anastasia Makarova, Andreas Krause Adversarial Imitation Learning via Boosting
Jonathan Daniel Chang, Dhruv Sreenivas, Yingbing Huang, Kianté Brantley, Wen Sun Adversarial Training Should Be Cast as a Non-Zero-Sum Game
Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher AffineQuant: Affine Transformation Quantization for Large Language Models
Yuexiao Ma, Huixia Li, Xiawu Zheng, Feng Ling, Xuefeng Xiao, Rui Wang, Shilei Wen, Fei Chao, Rongrong Ji AgentBench: Evaluating LLMs as Agents
Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
Weize Chen, Yusheng Su, Jingwei Zuo, Cheng Yang, Chenfei Yuan, Chi-Min Chan, Heyang Yu, Yaxi Lu, Yi-Hsin Hung, Chen Qian, Yujia Qin, Xin Cong, Ruobing Xie, Zhiyuan Liu, Maosong Sun, Jie Zhou AGILE3D: Attention Guided Interactive Multi-Object 3D Segmentation
Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe, Konrad Schindler, Theodora Kontogianni AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang, Cheng Long, Gao Cong, Jingyuan Wang Align with Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
Eliya Segev, Maya Alroy, Ronen Katsir, Noam Wies, Ayana Shenhav, Yael Sapir Ben-Oren, David Zar, Oren Tadmor, Jacob Bitterman, Amnon Shashua, Tal Rosenwein AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye Hao, Fei Ni, Yao Mu, Yan Zheng, Yujing Hu, Tangjie Lv, Changjie Fan, Zhipeng Hu AlpaGasus: Training a Better Alpaca with Fewer Data
Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, Hongxia Jin Alt-Text with Context: Improving Accessibility for Images on Twitter
Nikita Srivatsan, Sofia Samaniego, Omar Florez, Taylor Berg-Kirkpatrick Amortizing Intractable Inference in Large Language Models
Edward J Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment
Sergei Solonets, Daniil Sinitsyn, Lukas Von Stumberg, Nikita Araslanov, Daniel Cremers An Efficient Tester-Learner for Halfspaces
Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan An Emulator for Fine-Tuning Large Language Models Using Small Language Models
Eric Mitchell, Rafael Rafailov, Archit Sharma, Chelsea Finn, Christopher D Manning An Improved Analysis of Per-Sample and Per-Update Clipping in Federated Learning
Bo Li, Xiaowen Jiang, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian U Stich An LLM Can Fool Itself: A Prompt-Based Adversarial Attack
Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan Kankanhalli An Unforgeable Publicly Verifiable Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen, Irwin King, Philip S. Yu Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models Without Specific Tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao, Zhengyang Liang, Yaohui Wang, Yu Qiao, Maneesh Agrawala, Dahua Lin, Bo Dai AntGPT: Can Large Language Models Help Long-Term Action Anticipation from Videos?
Qi Zhao, Shijie Wang, Ce Zhang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, Chen Sun AnyText: Multilingual Visual Text Generation and Editing
Yuxiang Tuo, Wangmeng Xiang, Jun-Yan He, Yifeng Geng, Xuansong Xie Approximately Piecewise E(3) Equivariant Point Networks
Matan Atzmon, Jiahui Huang, Francis Williams, Or Litany Are BERT Family Good Instruction Followers? a Study on Their Potential and Limitations
Yisheng Xiao, Juntao Li, Zechen Sun, Zechang Li, Qingrong Xia, Xinyu Duan, Zhefeng Wang, Min Zhang Are Models Biased on Text Without Gender-Related Language?
Catarina G Belém, Preethi Seshadri, Yasaman Razeghi, Sameer Singh ARGS: Alignment as Reward-Guided Search
Maxim Khanov, Jirayu Burapacheep, Yixuan Li ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Dieter Fox, Abhishek Gupta At Which Training Stage Does Code Data Help LLMs Reasoning?
Yingwei Ma, Yue Liu, Yue Yu, Yuanliang Zhang, Yu Jiang, Changjian Wang, Shanshan Li Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi AttEXplore: Attribution for Explanation with Model Parameters eXploration
Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin, Jason Xue, Flora D. Salim AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation
Zihao Tang, Zheqi Lv, Shengyu Zhang, Yifan Zhou, Xinyu Duan, Fei Wu, Kun Kuang Augmented Bayesian Policy Search
Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo AutoVP: An Automated Visual Prompting Framework and Benchmark
Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
Yuan Gao, Weizhong Zhang, Wenhan Luo, Lin Ma, Jin-Gang Yu, Gui-Song Xia, Jiayi Ma Backdoor Contrastive Learning via Bi-Level Trigger Optimization
Weiyu Sun, Xinyu Zhang, Hao Lu, Ying-Cong Chen, Ting Wang, Jinghui Chen, Lu Lin Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models
Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, Bo Li BadEdit: Backdooring Large Language Models by Model Editing
Yanzhou Li, Tianlin Li, Kangjie Chen, Jian Zhang, Shangqing Liu, Wenhan Wang, Tianwei Zhang, Yang Liu Balancing Act: Constraining Disparate Impact in Sparse Models
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada Bandits with Replenishable Knapsacks: The Best of Both Worlds
Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
Yaoming Wang, Jin Li, Xiaopeng Zhang, Bowen Shi, Chenglin Li, Wenrui Dai, Hongkai Xiong, Qi Tian Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine A Heller, Subhrajit Roy BatchPrompt: Accomplish More with Less
Jianzhe Lin, Maurice Diesendruck, Liang Du, Robin Abraham Bayesian Low-Rank Adaptation for Large Language Models
Adam X. Yang, Maxime Robeyns, Xi Wang, Laurence Aitchison Be Aware of the Neighborhood Effect: Modeling Selection Bias Under Interference
Haoxuan Li, Chunyuan Zheng, Sihao Ding, Peng Wu, Zhi Geng, Fuli Feng, Xiangnan He Beating Price of Anarchy and Gradient Descent Without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Andrew Stavroulakis, William Overman, Ioannis Panageas, Georgios Piliouras Behaviour Distillation
Andrei Lupu, Chris Lu, Jarek Luca Liesen, Robert Tjarko Lange, Jakob Nicolaus Foerster Benchmarking and Improving Generator-Validator Consistency of Language Models
Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks
Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma BENO: Boundary-Embedded Neural Operators for Elliptic PDEs
Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation
Peng Xu, Wenqi Shao, Mengzhao Chen, Shitao Tang, Kaipeng Zhang, Peng Gao, Fengwei An, Yu Qiao, Ping Luo Bespoke Solvers for Generative Flow Models
Neta Shaul, Juan Perez, Ricky T. Q. Chen, Ali Thabet, Albert Pumarola, Yaron Lipman Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain
Marcus J. Min, Yangruibo Ding, Luca Buratti, Saurabh Pujar, Gail Kaiser, Suman Jana, Baishakhi Ray Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs
Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs
Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai Bongard-OpenWorld: Few-Shot Reasoning for Free-Form Visual Concepts in the Real World
Rujie Wu, Xiaojian Ma, Zhenliang Zhang, Wei Wang, Qing Li, Song-Chun Zhu, Yizhou Wang Boundary Denoising for Video Activity Localization
Mengmeng Xu, Mattia Soldan, Jialin Gao, Shuming Liu, Juan-Manuel Perez-Rua, Bernard Ghanem Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks
Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström BrainLM: A Foundation Model for Brain Activity Recordings
Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed A Rizvi, Matteo Rosati, Christopher Averill, James L Cross, Prateek Mittal, Emanuele Zappala, Rahul Madhav Dhodapkar, Chadi Abdallah, David van Dijk Branch-GAN: Improving Text Generation with (not so) Large Language Models
Fredrik Carlsson, Johan Broberg, Erik Hillbom, Magnus Sahlgren, Joakim Nivre Bridging State and History Representations: Understanding Self-Predictive RL
Tianwei Ni, Benjamin Eysenbach, Erfan SeyedSalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon Building Cooperative Embodied Agents Modularly with Large Language Models
Hongxin Zhang, Weihua Du, Jiaming Shan, Qinhong Zhou, Yilun Du, Joshua B. Tenenbaum, Tianmin Shu, Chuang Gan Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game
Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee, Mark A. Hasegawa-Johnson, Yingzhen Li, Chang D. Yoo CABINET: Content Relevance-Based Noise Reduction for Table Question Answering
Sohan Patnaik, Heril Changwal, Milan Aggarwal, Sumit Bhatia, Yaman Kumar, Balaji Krishnamurthy CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-Training for BEV Perception
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang, Atul Prakash, Zhuoqing Mao, Chaowei Xiao Cameras as Rays: Pose Estimation via Ray Diffusion
Jason Y. Zhang, Amy Lin, Moneish Kumar, Tzu-Hsuan Yang, Deva Ramanan, Shubham Tulsiani Can Large Language Models Infer Causation from Correlation?
Zhijing Jin, Jiarui Liu, Zhiheng Lyu, Spencer Poff, Mrinmaya Sachan, Rada Mihalcea, Mona T. Diab, Bernhard Schölkopf Cauchy-Schwarz Divergence Information Bottleneck for Regression
Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, Jose C Principe Causal Modelling Agents: Causal Graph Discovery Through Synergising Metadata- and Data-Driven Reasoning
Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montana-Brown, Tiantian He, Ayodeji Ijishakin, Ivana Drobnjak, Daniel C. Castro, Daniel C. Alexander CausalLM Is Not Optimal for In-Context Learning
Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut Causally Aligned Curriculum Learning
Mingxuan Li, Junzhe Zhang, Elias Bareinboim CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha Srinivasa, Abhishek Gupta CellPLM: Pre-Training of Cell Language Model Beyond Single Cells
Hongzhi Wen, Wenzhuo Tang, Xinnan Dai, Jiayuan Ding, Wei Jin, Yuying Xie, Jiliang Tang Chain of Log-Concave Markov Chains
Saeed Saremi, Ji Won Park, Francis Bach Chain-of-Experts: When LLMs Meet Complex Operations Research Problems
Ziyang Xiao, Dongxiang Zhang, Yangjun Wu, Lilin Xu, Yuan Jessica Wang, Xiongwei Han, Xiaojin Fu, Tao Zhong, Jia Zeng, Mingli Song, Gang Chen Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister ChatEval: Towards Better LLM-Based Evaluators Through Multi-Agent Debate
Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, Zhiyuan Liu CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents
Siyuan Qi, Shuo Chen, Yexin Li, Xiangyu Kong, Junqi Wang, Bangcheng Yang, Pring Wong, Yifan Zhong, Xiaoyuan Zhang, Zhaowei Zhang, Nian Liu, Yaodong Yang, Song-Chun Zhu CLAP: Collaborative Adaptation for Patchwork Learning
Sen Cui, Abudukelimu Wuerkaixi, Weishen Pan, Jian Liang, Lei Fang, Changshui Zhang, Fei Wang Class Incremental Learning via Likelihood Ratio Based Task Prediction
Haowei Lin, Yijia Shao, Weinan Qian, Ningxin Pan, Yiduo Guo, Bing Liu Classification with Conceptual Safeguards
Hailey Joren, Charles Thomas Marx, Berk Ustun Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Shengyi Huang, Jiayi Weng, Rujikorn Charakorn, Min Lin, Zhongwen Xu, Santiago Ontanon CLEX: Continuous Length Extrapolation for Large Language Models
Guanzheng Chen, Xin Li, Zaiqiao Meng, Shangsong Liang, Lidong Bing CLIP the Bias: How Useful Is Balancing Data in Multimodal Learning?
Ibrahim Alabdulmohsin, Xiao Wang, Andreas Peter Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction
Size Wu, Wenwei Zhang, Lumin Xu, Sheng Jin, Xiangtai Li, Wentao Liu, Chen Change Loy Closing the Curious Case of Neural Text Degeneration
Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal CNN Kernels Can Be the Best Shapelets
Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li CO2: Efficient Distributed Training with Full Communication-Computation Overlap
Weigao Sun, Zhen Qin, Weixuan Sun, Shidi Li, Dong Li, Xuyang Shen, Yu Qiao, Yiran Zhong CoBIT: A Contrastive Bi-Directional Image-Text Generation Model
Haoxuan You, Mandy Guo, Zhecan Wang, Kai-Wei Chang, Jason Michael Baldridge, Jiahui Yu COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
Anne Harrington, Vasha DuTell, Mark Hamilton, Ayush Tewari, Simon Stent, William T. Freeman, Ruth Rosenholtz Code Representation Learning at Scale
Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, Bing Xiang CoLiDE: Concomitant Linear DAG Estimation
Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper COLLIE: Systematic Construction of Constrained Text Generation Tasks
Shunyu Yao, Howard Chen, Austin W. Hanjie, Runzhe Yang, Karthik R Narasimhan CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
Sreyan Ghosh, Ashish Seth, Sonal Kumar, Utkarsh Tyagi, Chandra Kiran Reddy Evuru, Ramaneswaran S, S Sakshi, Oriol Nieto, Ramani Duraiswami, Dinesh Manocha Compositional Generative Inverse Design
Tailin Wu, Takashi Maruyama, Long Wei, Tao Zhang, Yilun Du, Gianluca Iaccarino, Jure Leskovec Compositional Preference Models for Aligning LMs
Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Marc Dymetman Compressing LLMs: The Truth Is Rarely Pure and Never Simple
Ajay Kumar Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang Concept Bottleneck Generative Models
Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho Conditional Variational Diffusion Models
Gabriel Della Maggiora, Luis Alberto Croquevielle, Nikita Deshpande, Harry Horsley, Thomas Heinis, Artur Yakimovich Confidence-Aware Reward Optimization for Fine-Tuning Text-to-Image Models
Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dj Dvijotham, Jinwoo Shin, Kimin Lee Confidential-DPproof: Confidential Proof of Differentially Private Training
Ali Shahin Shamsabadi, Gefei Tan, Tudor Ioan Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller Conformal Inductive Graph Neural Networks
Soroush H. Zargarbashi, Aleksandar Bojchevski Conformal Language Modeling
Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn, Tommi S. Jaakkola, Regina Barzilay Conformal Prediction via Regression-as-Classification
Etash Kumar Guha, Shlok Natarajan, Thomas Möllenhoff, Mohammad Emtiyaz Khan, Eugene Ndiaye Conformal Risk Control
Anastasios Nikolas Angelopoulos, Stephen Bates, Adam Fisch, Lihua Lei, Tal Schuster Confronting Reward Model Overoptimization with Constrained RLHF
Ted Moskovitz, Aaditya K Singh, Dj Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca Dragan, Stephen Marcus McAleer Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yujiu Yang Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, Stefano Ermon Consistent Algorithms for Multi-Label Classification with Macro-at-$k$ Metrics
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski Constraint-Free Structure Learning with Smooth Acyclic Orientations
Riccardo Massidda, Francesco Landolfi, Martina Cinquini, Davide Bacciu Context Is Environment
Sharut Gupta, Stefanie Jegelka, David Lopez-Paz, Kartik Ahuja Context-Aware Meta-Learning
Christopher Fifty, Dennis Duan, Ronald Guenther Junkins, Ehsan Amid, Jure Leskovec, Christopher Re, Sebastian Thrun Contextual Bandits with Online Neural Regression
Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee Continuous Invariance Learning
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Edward Milsom, Ben Anson, Laurence Aitchison Coordinate-Aware Modulation for Neural Fields
Joo Chan Lee, Daniel Rho, Seungtae Nam, Jong Hwan Ko, Eunbyung Park COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL
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Mahan Fathi, Clement Gehring, Jonathan Pilault, David Kanaa, Pierre-Luc Bacon, Ross Goroshin CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
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Haowen Wang, Tao Sun, Congyun Jin, Yingbo Wang, Yibo Fan, Yunqi Xu, Yuliang Du, Cong Fan Cycle Consistency Driven Object Discovery
Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio DAFA: Distance-Aware Fair Adversarial Training
Hyungyu Lee, Saehyung Lee, Hyemi Jang, Junsung Park, Ho Bae, Sungroh Yoon DAM: Towards a Foundation Model for Forecasting
Luke Nicholas Darlow, Qiwen Deng, Ahmed Hassan, Martin Asenov, Rajkarn Singh, Artjom Joosen, Adam Barker, Amos Storkey Data Debugging with Shapley Importance over Machine Learning Pipelines
Bojan Karlaš, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang Data Filtering Networks
Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T Toshev, Vaishaal Shankar DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
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Jaemin Cho, Yushi Hu, Jason Michael Baldridge, Roopal Garg, Peter Anderson, Ranjay Krishna, Mohit Bansal, Jordi Pont-Tuset, Su Wang De Novo Protein Design Using Geometric Vector Field Networks
Weian Mao, Muzhi Zhu, Zheng Sun, Shuaike Shen, Lin Yuanbo Wu, Hao Chen, Chunhua Shen Debiased Collaborative Filtering with Kernel-Based Causal Balancing
Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, Peng Cui Debiasing Algorithm Through Model Adaptation
Tomasz Limisiewicz, David Mareček, Tomáš Musil Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor Tsang, Yong Liu Deceptive Fairness Attacks on Graphs via Meta Learning
Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo, Hanghang Tong Decodable and Sample Invariant Continuous Object Encoder
Dehao Yuan, Furong Huang, Cornelia Fermuller, Yiannis Aloimonos Decoding Natural Images from EEG for Object Recognition
Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao Decoupling Regularization from the Action Space
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-Training Tasks
Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li Deep Confident Steps to New Pockets: Strategies for Docking Generalization
Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E Vogt Deep Neural Network Initialization with Sparsity Inducing Activations
Ilan Price, Nicholas Daultry Ball, Adam Christopher Jones, Samuel Chun Hei Lam, Jared Tanner Deep Neural Networks Tend to Extrapolate Predictably
Katie Kang, Amrith Setlur, Claire Tomlin, Sergey Levine Deep Reinforcement Learning for Modelling Protein Complexes
Ziqi Gao, Tao Feng, Jiaxuan You, Chenyi Zi, Yan Zhou, Chen Zhang, Jia Li Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks
Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerik, Jonathan Scholz, David Held Deep Temporal Graph Clustering
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Changyou Chen, Han Ding, Bunyamin Sisman, Yi Xu, Ouye Xie, Benjamin Z. Yao, Son Dinh Tran, Belinda Zeng Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
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Eran Rosenbluth, Jan Tönshoff, Martin Ritzert, Berke Kisin, Martin Grohe Divide and Not Forget: Ensemble of Selectively Trained Experts in Continual Learning
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Chen Gan, Zihao Yin, Kelei He, Yang Gao, Junfeng Zhang DMV3D: Denoising Multi-View Diffusion Using 3D Large Reconstruction Model
Yinghao Xu, Hao Tan, Fujun Luan, Sai Bi, Peng Wang, Jiahao Li, Zifan Shi, Kalyan Sunkavalli, Gordon Wetzstein, Zexiang Xu, Kai Zhang DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
Xianjun Yang, Wei Cheng, Yue Wu, Linda Ruth Petzold, William Yang Wang, Haifeng Chen DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genomes
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Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak, Matthias Bethge, Wieland Brendel DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James R. Glass, Pengcheng He Domain Randomization via Entropy Maximization
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Yin Fang, Ningyu Zhang, Zhuo Chen, Lingbing Guo, Xiaohui Fan, Huajun Chen Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
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Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom, Mehdi S. M. Sajjadi, Thomas Kipf DOS: Diverse Outlier Sampling for Out-of-Distribution Detection
Wenyu Jiang, Hao Cheng, MingCai Chen, Chongjun Wang, Hongxin Wei DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li, Zhangyang Wang DP-SGD Without Clipping: The Lipschitz Neural Network Way
Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux DQ-LoRe: Dual Queries with Low Rank Approximation Re-Ranking for In-Context Learning
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Jie Xiao, Ruili Feng, Han Zhang, Zhiheng Liu, Zhantao Yang, Yurui Zhu, Xueyang Fu, Kai Zhu, Yu Liu, Zheng-Jun Zha DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
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Yu-Ju Tsai, Yu-Lun Liu, Lu Qi, Kelvin C.K. Chan, Ming-Hsuan Yang Dual-Encoders for Extreme Multi-Label Classification
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Hang Xu, Kai Li, Haobo Fu, Qiang Fu, Junliang Xing, Jian Cheng Dynamic Neural Response Tuning
Tian Qiu, Wenxiang Xu, Lin Chen, Linyun Zhou, Zunlei Feng, Mingli Song Dynamic Sparse No Training: Training-Free Fine-Tuning for Sparse LLMs
Yuxin Zhang, Lirui Zhao, Mingbao Lin, Sun Yunyun, Yiwu Yao, Xingjia Han, Jared Tanner, Shiwei Liu, Rongrong Ji Dynamic Sparse Training with Structured Sparsity
Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou Dynamics-Informed Protein Design with Structure Conditioning
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Jonathan Brokman, Roy Betser, Rotem Turjeman, Tom Berkov, Ido Cohen, Guy Gilboa Enhancing Small Medical Learners with Privacy-Preserving Contextual Prompting
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Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend Entropy Is Not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors
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Tim Ruben Davidson, Veniamin Veselovsky, Michal Kosinski, Robert West Evaluating Large Language Models at Evaluating Instruction Following
Zhiyuan Zeng, Jiatong Yu, Tianyu Gao, Yu Meng, Tanya Goyal, Danqi Chen Evaluating Representation Learning on the Protein Structure Universe
Arian Rokkum Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi, Simon V Mathis, Charles Harris, Jian Tang, Jianlin Cheng, Pietro Lio, Tom Leon Blundell EventRPG: Event Data Augmentation with Relevance Propagation Guidance
Mingyuan Sun, Donghao Zhang, Zongyuan Ge, Wang Jiaxu, Jia Li, Zheng Fang, Renjing Xu Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Bowen Song, Qiang Lou, Jian Jiao, Denis X Charles EX-Graph: A Pioneering Dataset Bridging Ethereum and X
Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He Expected Flow Networks in Stochastic Environments and Two-Player Zero-Sum Games
Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin Explaining Kernel Clustering via Decision Trees
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Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi Exploring Diffusion Time-Steps for Unsupervised Representation Learning
Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric I-Chao Chang, Hanwang Zhang Exploring Target Representations for Masked Autoencoders
Xingbin Liu, Jinghao Zhou, Tao Kong, Xianming Lin, Rongrong Ji Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow
Hanyu Zhou, Yi Chang, Haoyue Liu, Yan Wending, Yuxing Duan, Zhiwei Shi, Luxin Yan Exposing Text-Image Inconsistency Using Diffusion Models
Mingzhen Huang, Shan Jia, Zhou Zhou, Yan Ju, Jialing Cai, Siwei Lyu Expressive Losses for Verified Robustness via Convex Combinations
Alessandro De Palma, Rudy R Bunel, Krishnamurthy Dj Dvijotham, M. Pawan Kumar, Robert Stanforth, Alessio Lomuscio Expressivity of ReLU-Networks Under Convex Relaxations
Maximilian Baader, Mark Niklas Mueller, Yuhao Mao, Martin Vechev Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World
Chunshu Wu, Ruibing Song, Chuan Liu, Yunan Yang, Ang Li, Michael Huang, Tong Geng Facing the Elephant in the Room: Visual Prompt Tuning or Full Finetuning?
Cheng Han, Qifan Wang, Yiming Cui, Wenguan Wang, Lifu Huang, Siyuan Qi, Dongfang Liu Fair and Efficient Contribution Valuation for Vertical Federated Learning
Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael Friedlander, Yong Zhang Fair Classifiers That Abstain Without Harm
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Depen Morwani, Benjamin L. Edelman, Costin-Andrei Oncescu, Rosie Zhao, Sham M. Kakade Feature-Aligned N-BEATS with Sinkhorn Divergence
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Di Wu, Jun Bai, Yiliao Song, Junjun Chen, Wei Zhou, Yong Xiang, Atul Sajjanhar FedLoGe: Joint Local and Generic Federated Learning Under Long-Tailed Data
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Rafael Alberto Rivera Soto, Kailin Koch, Aleem Khan, Barry Y. Chen, Marcus Bishop, Nicholas Andrews Few-Shot Hybrid Domain Adaptation of Image Generator
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Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan GROOT: Learning to Follow Instructions by Watching Gameplay Videos
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Philip Amortila, Dylan J Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments
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Zihan Zhang, Jason D. Lee, Yuxin Chen, Simon Shaolei Du How Connectivity Structure Shapes Rich and Lazy Learning in Neural Circuits
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Todd SheaBrown, Guillaume Lajoie How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
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Mihaela C Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
Lorenzo Pacchiardi, Alex James Chan, Sören Mindermann, Ilan Moscovitz, Alexa Yue Pan, Yarin Gal, Owain Evans, Jan M. Brauner How to Fine-Tune Vision Models with SGD
Ananya Kumar, Ruoqi Shen, Sebastien Bubeck, Suriya Gunasekar Human Feedback Is Not Gold Standard
Tom Hosking, Phil Blunsom, Max Bartolo Human Motion Diffusion as a Generative Prior
Yoni Shafir, Guy Tevet, Roy Kapon, Amit Haim Bermano Hybrid Directional Graph Neural Network for Molecules
Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Xu Yinghui, Yuan Qi, Furao Shen Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
Bowen Shi, Xiaopeng Zhang, Yaoming Wang, Jin Li, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Rühle, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah Hybrid Sharing for Multi-Label Image Classification
Zihao Yin, Chen Gan, Kelei He, Yang Gao, Junfeng Zhang HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee, Jaemin Yoo, Kijung Shin Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
Changbin Li, Kangshuo Li, Yuzhe Ou, Lance M. Kaplan, Audun Jøsang, Jin-Hee Cho, Dong Hyun Jeong, Feng Chen HyperAttention: Long-Context Attention in Near-Linear Time
Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David Woodruff, Amir Zandieh Hypergraph Dynamic System
Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion
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Yong Liu, Tengge Hu, Haoran Zhang, Haixu Wu, Shiyu Wang, Lintao Ma, Mingsheng Long Jointly Training Large Autoregressive Multimodal Models
Emanuele Aiello, Lili Yu, Yixin Nie, Armen Aghajanyan, Barlas Oguz JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling
Jingyang Zhang, Shiwei Li, Yuanxun Lu, Tian Fang, David Neil McKinnon, Yanghai Tsin, Long Quan, Yao Yao Jumanji: A Diverse Suite of Scalable Reinforcement Learning Environments in JAX
Clément Bonnet, Daniel Luo, Donal John Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence Illing Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries Petrus Smit, Nathan Grinsztajn, Raphael Boige, Cemlyn Neil Waters, Mohamed Ali Ali Mimouni, Ulrich Armel Mbou Sob, Ruan John de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, Alexandre Laterre Kalman Filter for Online Classification of Non-Stationary Data
Michalis Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jorg Bornschein Kernelised Normalising Flows
Eshant English, Matthias Kirchler, Christoph Lippert KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Ghosh Peshawaria, Ranjita Naik, Besmira Nushi Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models
Shangbin Feng, Weijia Shi, Yuyang Bai, Vidhisha Balachandran, Tianxing He, Yulia Tsvetkov Knowledge Fusion of Large Language Models
Fanqi Wan, Xinting Huang, Deng Cai, Xiaojun Quan, Wei Bi, Shuming Shi KoLA: Carefully Benchmarking World Knowledge of Large Language Models
Jifan Yu, Xiaozhi Wang, Shangqing Tu, Shulin Cao, Daniel Zhang-Li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Kaifeng Yun, Linlu Gong, Nianyi Lin, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan Yao, Ning Ding, Lei Hou, Zhiyuan Liu, Xu Bin, Jie Tang, Juanzi Li Koopman-Based Generalization Bound: New Aspect for Full-Rank Weights
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, Taiji Suzuki KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement
Zhangyang Gao, Cheng Tan, Xingran Chen, Yijie Zhang, Jun Xia, Siyuan Li, Stan Z. Li L2P-MIP: Learning to Presolve for Mixed Integer Programming
Chang Liu, Zhichen Dong, Haobo Ma, Weilin Luo, Xijun Li, Bowen Pang, Jia Zeng, Junchi Yan Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Tony Chen, Miao Xu Label-Free Node Classification on Graphs with Large Language Models (LLMs)
Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin, Haiyang Zhang, Hui Liu, Jiliang Tang Label-Noise Robust Diffusion Models
Byeonghu Na, Yeongmin Kim, HeeSun Bae, Jung Hyun Lee, Se Jung Kwon, Wanmo Kang, Il-chul Moon LabelDP-Pro: Learning with Label Differential Privacy via Projections
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang Lagrangian Flow Networks for Conservation Laws
Fabricio Arend Torres, Marcello Massimo Negri, Marco Inversi, Jonathan Aellen, Volker Roth LaneSegNet: mAP Learning with Lane Segment Perception for Autonomous Driving
Tianyu Li, Peijin Jia, Bangjun Wang, Li Chen, Kun Jiang, Junchi Yan, Hongyang Li Language Model Beats Diffusion - Tokenizer Is Key to Visual Generation
Lijun Yu, Jose Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G Hauptmann, Boqing Gong, Ming-Hsuan Yang, Irfan Essa, David A Ross, Lu Jiang Language Model Cascades: Token-Level Uncertainty and Beyond
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar Language Model Detectors Are Easily Optimized Against
Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D Manning, Chelsea Finn, Stefano Ermon Language Model Inversion
John Xavier Morris, Wenting Zhao, Justin T Chiu, Vitaly Shmatikov, Alexander M Rush Language Model Self-Improvement by Reinforcement Learning Contemplation
Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li, Xiong-Hui Chen, Jiacheng Xu, Zongzhang Zhang, Yang Yu Language Modeling Is Compression
Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness Language-Informed Visual Concept Learning
Sharon Lee, Yunzhi Zhang, Shangzhe Wu, Jiajun Wu LanguageBind: Extending Video-Language Pretraining to N-Modality by Language-Based Semantic Alignment
Bin Zhu, Bin Lin, Munan Ning, Yang Yan, Jiaxi Cui, Wang HongFa, Yatian Pang, Wenhao Jiang, Junwu Zhang, Zongwei Li, Cai Wan Zhang, Zhifeng Li, Wei Liu, Li Yuan Large Content and Behavior Models to Understand, Simulate, and Optimize Content and Behavior
Ashmit Khandelwal, Aditya Agrawal, Aanisha Bhattacharyya, Yaman Kumar, Somesh Singh, Uttaran Bhattacharya, Ishita Dasgupta, Stefano Petrangeli, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy Large Language Models Are Efficient Learners of Noise-Robust Speech Recognition
Yuchen Hu, Chen Chen, Chao-Han Huck Yang, Ruizhe Li, Chao Zhang, Pin-Yu Chen, EngSiong Chng Large Language Models as Analogical Reasoners
Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou Large Language Models as Automated Aligners for Benchmarking Vision-Language Models
Yuanfeng Ji, Chongjian Ge, Weikai Kong, Enze Xie, Zhengying Liu, Zhenguo Li, Ping Luo Large Language Models as Generalizable Policies for Embodied Tasks
Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Rin Metcalf, Walter Talbott, Natalie Mackraz, R Devon Hjelm, Alexander T Toshev Large Language Models as Optimizers
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, Xinyun Chen Large Language Models as Tool Makers
Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou Large Language Models Cannot Self-Correct Reasoning yet
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, Denny Zhou Large Language Models to Enhance Bayesian Optimization
Tennison Liu, Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar Large Multilingual Models Pivot Zero-Shot Multimodal Learning Across Languages
Jinyi Hu, Yuan Yao, Chongyi Wang, Shan Wang, Yinxu Pan, Qianyu Chen, Tianyu Yu, Hanghao Wu, Yue Zhao, Haoye Zhang, Xu Han, Yankai Lin, Jiao Xue, Dahai Li, Zhiyuan Liu, Maosong Sun Large-Scale Training of Foundation Models for Wearable Biosignals
Salar Abbaspourazad, Oussama Elachqar, Andrew Miller, Saba Emrani, Udhyakumar Nallasamy, Ian Shapiro Large-Vocabulary 3D Diffusion Model with Transformer
Ziang Cao, Fangzhou Hong, Tong Wu, Liang Pan, Ziwei Liu Latent 3D Graph Diffusion
Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang, Yang Shen Latent Trajectory Learning for Limited Timestamps Under Distribution Shift over Time
Qiuhao Zeng, Changjian Shui, Long-Kai Huang, Peng Liu, Xi Chen, Charles Ling, Boyu Wang Layer-Wise Linear Mode Connectivity
Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi LCOT: Linear Circular Optimal Transport
Rocio P Diaz Martin, Ivan Vladimir Medri, Yikun Bai, Xinran Liu, Kangbai Yan, Gustavo Rohde, Soheil Kolouri LDReg: Local Dimensionality Regularized Self-Supervised Learning
Hanxun Huang, Ricardo J. G. B. Campello, Sarah Monazam Erfani, Xingjun Ma, Michael E. Houle, James Bailey Learning 3D Particle-Based Simulators from RGB-D Videos
William F Whitney, Tatiana Lopez-Guevara, Tobias Pfaff, Yulia Rubanova, Thomas Kipf, Kim Stachenfeld, Kelsey R Allen Learning Dynamic Representations of the Functional Connectome in Neurobiological Networks
Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley, Eviatar Yemini, Steven W. Zucker Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer
Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho, Kookjin Lee, Nayong Kim, Kiseok Chang, ChangSeung Woo, Ilho Kim, SeokWoo Lee, Joon Young Yang, Sooyoung Yoon, Noseong Park Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer Learning Grounded Action Abstractions from Language
Lionel Wong, Jiayuan Mao, Pratyusha Sharma, Zachary S Siegel, Jiahai Feng, Noa Korneev, Joshua B. Tenenbaum, Jacob Andreas Learning Interactive Real-World Simulators
Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Leslie Pack Kaelbling, Dale Schuurmans, Pieter Abbeel Learning Interpretable Control Inputs and Dynamics Underlying Animal Locomotion
Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin, Christian K. Machens, Michael Orger, Adrien Jouary Learning Invariant Representations of Time-Homogeneous Stochastic Dynamical Systems
Vladimir R Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil Learning Multi-Agent Communication with Contrastive Learning
Yat Long Lo, Biswa Sengupta, Jakob Nicolaus Foerster, Michael Noukhovitch Learning Optimal Contracts: How to Exploit Small Action Spaces
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti Learning over Molecular Conformer Ensembles: Datasets and Benchmarks
Yanqiao Zhu, Jeehyun Hwang, Keir Adams, Zhen Liu, Bozhao Nan, Brock Stenfors, Yuanqi Du, Jatin Chauhan, Olaf Wiest, Olexandr Isayev, Connor W. Coley, Yizhou Sun, Wei Wang Learning Performance-Improving Code Edits
Alexander G Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh Learning Planning Abstractions from Language
Weiyu Liu, Geng Chen, Joy Hsu, Jiayuan Mao, Jiajun Wu Learning Thresholds with Latent Values and Censored Feedback
Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng Learning to Act from Actionless Videos Through Dense Correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du, Shao-Hua Sun, Joshua B. Tenenbaum Learning to Design Protein-Protein Interactions with Enhanced Generalization
Anton Bushuiev, Roman Bushuiev, Petr Kouba, Anatolii Filkin, Marketa Gabrielova, Michal Gabriel, Jiri Sedlar, Tomas Pluskal, Jiri Damborsky, Stanislav Mazurenko, Josef Sivic Learning to Jointly Understand Visual and Tactile Signals
Yichen Li, Yilun Du, Chao Liu, Chao Liu, Francis Williams, Michael Foshey, Benjamin Eckart, Jan Kautz, Joshua B. Tenenbaum, Antonio Torralba, Wojciech Matusik Learning to Make Adherence-Aware Advice
Guanting Chen, Xiaocheng Li, Chunlin Sun, Hanzhao Wang Learning to Reject Meets Long-Tail Learning
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum, Neha Gupta, Sanjiv Kumar Learning to Reject with a Fixed Predictor: Application to Decontextualization
Christopher Mohri, Daniel Andor, Eunsol Choi, Michael Collins, Anqi Mao, Yutao Zhong Learning with Language-Guided State Abstractions
Andi Peng, Ilia Sucholutsky, Belinda Z. Li, Theodore Sumers, Thomas L. Griffiths, Jacob Andreas, Julie Shah Learning with Mixture of Prototypes for Out-of-Distribution Detection
Haodong Lu, Dong Gong, Shuo Wang, Jason Xue, Lina Yao, Kristen Moore Leave-One-Out Distinguishability in Machine Learning
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri Leftover Lunch: Advantage-Based Offline Reinforcement Learning for Language Models
Ashutosh Baheti, Ximing Lu, Faeze Brahman, Ronan Le Bras, Maarten Sap, Mark Riedl LEGO-Prover: Neural Theorem Proving with Growing Libraries
Haiming Wang, Huajian Xin, Chuanyang Zheng, Zhengying Liu, Qingxing Cao, Yinya Huang, Jing Xiong, Han Shi, Enze Xie, Jian Yin, Zhenguo Li, Xiaodan Liang LEMON: Lossless Model Expansion
Yite Wang, Jiahao Su, Hanlin Lu, Cong Xie, Tianyi Liu, Jianbo Yuan, Haibin Lin, Ruoyu Sun, Hongxia Yang Lemur: Harmonizing Natural Language and Code for Language Agents
Yiheng Xu, Hongjin Su, Chen Xing, Boyu Mi, Qian Liu, Weijia Shi, Binyuan Hui, Fan Zhou, Yitao Liu, Tianbao Xie, Zhoujun Cheng, Siheng Zhao, Lingpeng Kong, Bailin Wang, Caiming Xiong, Tao Yu Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
Junyoung Seo, Wooseok Jang, Min-Seop Kwak, Hyeonsu Kim, Jaehoon Ko, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, Seungryong Kim Let Models Speak Ciphers: Multiagent Debate Through Embeddings
Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang Let's Verify Step by Step
Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection
Sifan Zhou, Liang Li, Xinyu Zhang, Bo Zhang, Shipeng Bai, Miao Sun, Ziyu Zhao, Xiaobo Lu, Xiangxiang Chu LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin Lifting Architectural Constraints of Injective Flows
Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann, Ullrich Koethe Light Schrödinger Bridge
Alexander Korotin, Nikita Gushchin, Evgeny Burnaev Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds
Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu, Furong Huang, Tudor Dumitras LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Gabriel Grand, Lionel Wong, Matthew Bowers, Theo X. Olausson, Muxin Liu, Joshua B. Tenenbaum, Jacob Andreas Linearity of Relation Decoding in Transformer Language Models
Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau Lipschitz Singularities in Diffusion Models
Zhantao Yang, Ruili Feng, Han Zhang, Yujun Shen, Kai Zhu, Lianghua Huang, Yifei Zhang, Yu Liu, Deli Zhao, Jingren Zhou, Fan Cheng LipSim: A Provably Robust Perceptual Similarity Metric
Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy, Farshad Khorrami, Siddharth Garg LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading
Yochai Yemini, Aviv Shamsian, Lior Bracha, Sharon Gannot, Ethan Fetaya Listen, Think, and Understand
Yuan Gong, Hongyin Luo, Alexander H. Liu, Leonid Karlinsky, James R. Glass LLCP: Learning Latent Causal Processes for Reasoning-Based Video Question Answer
Guangyi Chen, Yuke Li, Xiao Liu, Zijian Li, Eman Al Suradi, Donglai Wei, Kun Zhang Llemma: An Open Language Model for Mathematics
Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen Marcus McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck LLM Augmented LLMs: Expanding Capabilities Through Composition
Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Sriram Ganapathy, Abhishek Bapna, Prateek Jain, Partha Talukdar LLM-Assisted Code Cleaning for Training Accurate Code Generators
Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, Ion Stoica LLM-Grounded Video Diffusion Models
Long Lian, Baifeng Shi, Adam Yala, Trevor Darrell, Boyi Li LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models
Ahmad Faiz, Sotaro Kaneda, Ruhan Wang, Rita Chukwunyere Osi, Prateek Sharma, Fan Chen, Lei Jiang LMSYS-Chat-1m: A Large-Scale Real-World LLM Conversation Dataset
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang Local Graph Clustering with Noisy Labels
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang Local Search GFlowNets
Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park Locality-Aware Graph Rewiring in GNNs
Federico Barbero, Ameya Velingker, Amin Saberi, Michael M. Bronstein, Francesco Di Giovanni Localizing and Editing Knowledge in Text-to-Image Generative Models
Samyadeep Basu, Nanxuan Zhao, Vlad I Morariu, Soheil Feizi, Varun Manjunatha LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao Logical Languages Accepted by Transformer Encoders with Hard Attention
Pablo Barcelo, Alexander Kozachinskiy, Anthony Widjaja Lin, Vladimir Podolskii LogicMP: A Neuro-Symbolic Approach for Encoding First-Order Logic Constraints
Weidi Xu, Jingwei Wang, Lele Xie, Jianshan He, Hongting Zhou, Taifeng Wang, Xiaopei Wan, Jingdong Chen, Chao Qu, Wei Chu Long-Tailed Diffusion Models with Oriented Calibration
Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao, Xiangfeng Wang, Mingyuan Zhou, Ya Zhang, Yanfeng Wang Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data
Young-Jae Park, Minseok Seo, Doyi Kim, Hyeri Kim, Sanghoon Choi, Beomkyu Choi, Jeongwon Ryu, Sohee Son, Hae-Gon Jeon, Yeji Choi LongLoRA: Efficient Fine-Tuning of Long-Context Large Language Models
Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia Look, Remember and Reason: Grounded Reasoning in Videos with Language Models
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza, Mingu Lee, Pulkit Madan, Roland Memisevic Looped Transformers Are Better at Learning Learning Algorithms
Liu Yang, Kangwook Lee, Robert D Nowak, Dimitris Papailiopoulos LOQA: Learning with Opponent Q-Learning Awareness
Milad Aghajohari, Juan Agustin Duque, Tim Cooijmans, Aaron Courville LRM: Large Reconstruction Model for Single Image to 3D
Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, Hao Tan LUT-GEMM: Quantized Matrix Multiplication Based on LUTs for Efficient Inference in Large-Scale Generative Language Models
Gunho Park, Baeseong Park, Minsub Kim, Sungjae Lee, Jeonghoon Kim, Beomseok Kwon, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee MaGIC: Multi-Modality Guided Image Completion
Hao Wang, Yongsheng Yu, Tiejian Luo, Heng Fan, Libo Zhang Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, Bernard Ghanem MagicDrive: Street View Generation with Diverse 3D Geometry Control
Ruiyuan Gao, Kai Chen, Enze Xie, Lanqing Hong, Zhenguo Li, Dit-Yan Yeung, Qiang Xu Magnushammer: A Transformer-Based Approach to Premise Selection
Maciej Mikuła, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Albert Q. Jiang, Jin Peng Zhou, Christian Szegedy, Łukasz Kuciński, Piotr Miłoś, Yuhuai Wu Making Llama SEE and Draw with SEED Tokenizer
Yuying Ge, Sijie Zhao, Ziyun Zeng, Yixiao Ge, Chen Li, Xintao Wang, Ying Shan Making Pre-Trained Language Models Great on Tabular Prediction
Jiahuan Yan, Bo Zheng, Hongxia Xu, Yiheng Zhu, Danny Chen, Jimeng Sun, Jian Wu, Jintai Chen MAmmoTH: Building Math Generalist Models Through Hybrid Instruction Tuning
Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, Wenhu Chen Manifold Diffusion Fields
Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista Manifold Preserving Guided Diffusion
Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon Mask-Based Modeling for Neural Radiance Fields
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang, Yan Lu, Dong Liu Masked Audio Generation Using a Single Non-Autoregressive Transformer
Alon Ziv, Itai Gat, Gael Le Lan, Tal Remez, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Yossi Adi Masks, Signs, and Learning Rate Rewinding
Advait Harshal Gadhikar, Rebekka Burkholz Massively Scalable Inverse Reinforcement Learning in Google Maps
Matt Barnes, Matthew Abueg, Oliver F. Lange, Matt Deeds, Jason Trader, Denali Molitor, Markus Wulfmeier, Shawn O'Banion Mastering Memory Tasks with World Models
Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Ke Wang, Houxing Ren, Aojun Zhou, Zimu Lu, Sichun Luo, Weikang Shi, Renrui Zhang, Linqi Song, Mingjie Zhan, Hongsheng Li Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem
Albert Xu, Jhih-Yi Hsieh, Bhaskar Vundurthy, Nithya Kemp, Eliana Cohen, Lu Li, Howie Choset MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao Matrix Manifold Neural Networks++
Xuan Son Nguyen, Shuo Yang, Aymeric Histace Matryoshka Diffusion Models
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly Maximum Entropy Heterogeneous-Agent Reinforcement Learning
Jiarong Liu, Yifan Zhong, Siyi Hu, Haobo Fu, Qiang Fu, Xiaojun Chang, Yaodong Yang Maximum Entropy Model Correction in Reinforcement Learning
Amin Rakhsha, Mete Kemertas, Mohammad Ghavamzadeh, Amir-massoud Farahmand MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data
Jiaxin Yin, Yuanyuan Qiao, Zitang Zhou, Xiangchao Wang, Jie Yang Meaning Representations from Trajectories in Autoregressive Models
Tian Yu Liu, Matthew Trager, Alessandro Achille, Pramuditha Perera, Luca Zancato, Stefano Soatto Measuring Vision-Language STEM Skills of Neural Models
Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan, Ming Zhang, Chenguang Wang Mechanistically Analyzing the Effects of Fine-Tuning on Procedurally Defined Tasks
Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Krueger Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis
Ziyue Jiang, Jinglin Liu, Yi Ren, Jinzheng He, Zhenhui Ye, Shengpeng Ji, Qian Yang, Chen Zhang, Pengfei Wei, Chunfeng Wang, Xiang Yin, Zejun Ma, Zhou Zhao Memorization in Self-Supervised Learning Improves Downstream Generalization
Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes, Nicolas Papernot, Franziska Boenisch Memory-Consistent Neural Networks for Imitation Learning
Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen MERT: Acoustic Music Understanding Model with Large-Scale Self-Supervised Training
Yizhi Li, Ruibin Yuan, Ge Zhang, Yinghao Ma, Xingran Chen, Hanzhi Yin, Chenghao Xiao, Chenghua Lin, Anton Ragni, Emmanouil Benetos, Norbert Gyenge, Roger Dannenberg, Ruibo Liu, Wenhu Chen, Gus Xia, Yemin Shi, Wenhao Huang, Zili Wang, Yike Guo, Jie Fu MetaGPT: Meta Programming for a Multi-Agent Collaborative Framework
Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng, Jinlin Wang, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, Lingfeng Xiao, Chenglin Wu, Jürgen Schmidhuber MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use
Yue Huang, Jiawen Shi, Yuan Li, Chenrui Fan, Siyuan Wu, Qihui Zhang, Yixin Liu, Pan Zhou, Yao Wan, Neil Zhenqiang Gong, Lichao Sun Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
Congpei Qiu, Tong Zhang, Yanhao Wu, Wei Ke, Mathieu Salzmann, Sabine Süsstrunk MINT: Evaluating LLMs in Multi-Turn Interaction with Tools and Language Feedback
Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, Heng Ji Mixed-Type Tabular Data Synthesis with Score-Based Diffusion in Latent Space
Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis Mixture of LoRA Experts
Xun Wu, Shaohan Huang, Furu Wei Mixture of Weak and Strong Experts on Graphs
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Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou MMICL: Empowering Vision-Language Model with Multi-Modal In-Context Learning
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Dong Wei, Huaijiang Sun, Bin Li, Xiaoning Sun, Shengxiang Hu, Weiqing Li, Jianfeng Lu NetInfoF Framework: Measuring and Exploiting Network Usable Information
Meng-Chieh Lee, Haiyang Yu, Jian Zhang, Vassilis N. Ioannidis, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos Neur2RO: Neural Two-Stage Robust Optimization
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Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo Neural Field Classifiers via Target Encoding and Classification Loss
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Yuhui Xu, Lingxi Xie, Xiaotao Gu, Xin Chen, Heng Chang, Hengheng Zhang, Zhengsu Chen, Xiaopeng Zhang, Qi Tian Quality-Diversity Through AI Feedback
Herbie Bradley, Andrew Dai, Hannah Benita Teufel, Jenny Zhang, Koen Oostermeijer, Marco Bellagente, Jeff Clune, Kenneth Stanley, Gregory Schott, Joel Lehman Querying Easily Flip-Flopped Samples for Deep Active Learning
Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Jinwoo Shin, Chang D. Yoo Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango, Fabio Ferreira, Arlind Kadra, Frank Hutter, Josif Grabocka R-MAE: Regions Meet Masked Autoencoders
Duy Kien Nguyen, Yanghao Li, Vaibhav Aggarwal, Martin R. Oswald, Alexander Kirillov, Cees G. M. Snoek, Xinlei Chen RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Richard James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih Raidar: geneRative AI Detection via Rewriting
Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering
Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng, Fu-En Yang, Chien-Yi Wang, Yung-Hsuan Lai, Yu-Chiang Frank Wang RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Parth Sarthi, Salman Abdullah, Aditi Tuli, Shubh Khanna, Anna Goldie, Christopher D Manning Real3D-Portrait: One-Shot Realistic 3D Talking Portrait Synthesis
Zhenhui Ye, Tianyun Zhong, Yi Ren, Jiaqi Yang, Weichuang Li, Jiawei Huang, Ziyue Jiang, Jinzheng He, Rongjie Huang, Jinglin Liu, Chen Zhang, Xiang Yin, Zejun Ma, Zhou Zhao Reasoning with Latent Diffusion in Offline Reinforcement Learning
Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John Dolan, Jeff Schneider, Glen Berseth REBAR: Retrieval-Based Reconstruction for Time-Series Contrastive Learning
Maxwell Xu, Alexander Moreno, Hui Wei, Benjamin Marlin, James Matthew Rehg Recursive Generalization Transformer for Image Super-Resolution
Zheng Chen, Yulun Zhang, Jinjin Gu, Linghe Kong, Xiaokang Yang REFACTOR: Learning to Extract Theorems from Proofs
Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger Baker Grosse Relay Diffusion: Unifying Diffusion Process Across Resolutions for Image Synthesis
Jiayan Teng, Wendi Zheng, Ming Ding, Wenyi Hong, Jianqiao Wangni, Zhuoyi Yang, Jie Tang ReLoRA: High-Rank Training Through Low-Rank Updates
Vladislav Lialin, Sherin Muckatira, Namrata Shivagunde, Anna Rumshisky ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models
Seyed Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta, Carlo C del Mundo, Oncel Tuzel, Golnoosh Samei, Mohammad Rastegari, Mehrdad Farajtabar Remote Sensing Vision-Language Foundation Models Without Annotations via Ground Remote Alignment
Utkarsh Mall, Cheng Perng Phoo, Meilin Kelsey Liu, Carl Vondrick, Bharath Hariharan, Kavita Bala Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos Nikolakakis, Amin Karbasi, Dionysios Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas Repelling Random Walks
Isaac Reid, Eli Berger, Krzysztof Marcin Choromanski, Adrian Weller Replay Across Experiments: A Natural Extension of Off-Policy RL
Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen, Tuomas Haarnoja, Sandy Huang, Guy Lever, Ben Moran, Tim Hertweck, Leonard Hasenclever, Martin Riedmiller, Nicolas Heess, Markus Wulfmeier Representation Deficiency in Masked Language Modeling
Yu Meng, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao, Han Fang, Marjan Ghazvininejad, Jiawei Han, Luke Zettlemoyer ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation
Bo Zhang, Xinyu Cai, Jiakang Yuan, Donglin Yang, Jianfei Guo, Xiangchao Yan, Renqiu Xia, Botian Shi, Min Dou, Tao Chen, Si Liu, Junchi Yan, Yu Qiao Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective
Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo, Tsung-Yi Ho Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski Rethinking Model Ensemble in Transfer-Based Adversarial Attacks
Huanran Chen, Yichi Zhang, Yinpeng Dong, Xiao Yang, Hang Su, Jun Zhu Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
Shih-Hsin Wang, Yung-Chang Hsu, Justin Baker, Andrea L. Bertozzi, Jack Xin, Bao Wang Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
Zehao Dong, Muhan Zhang, Philip Payne, Michael A Province, Carlos Cruchaga, Tianyu Zhao, Fuhai Li, Yixin Chen Retrieval Is Accurate Generation
Bowen Cao, Deng Cai, Leyang Cui, Xuxin Cheng, Wei Bi, Yuexian Zou, Shuming Shi Retrieval Meets Long Context Large Language Models
Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, Bryan Catanzaro Retrieval-Enhanced Contrastive Vision-Text Models
Ahmet Iscen, Mathilde Caron, Alireza Fathi, Cordelia Schmid Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization
Animesh Basak Chowdhury, Marco Romanelli, Benjamin Tan, Ramesh Karri, Siddharth Garg Retro-Fallback: Retrosynthetic Planning in an Uncertain World
Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández-Lobato RetroBridge: Modeling Retrosynthesis with Markov Bridges
Ilia Igashov, Arne Schneuing, Marwin Segler, Michael M. Bronstein, Bruno Correia Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
Weiran Yao, Shelby Heinecke, Juan Carlos Niebles, Zhiwei Liu, Yihao Feng, Le Xue, R N Rithesh, Zeyuan Chen, Jianguo Zhang, Devansh Arpit, Ran Xu, Phil L Mui, Huan Wang, Caiming Xiong, Silvio Savarese RETSim: Resilient and Efficient Text Similarity
Marina Zhang, Owen Skipper Vallis, Aysegul Bumin, Tanay Vakharia, Elie Bursztein Reverse Diffusion Monte Carlo
Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation
Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Phung, Lizhen Qu Revisiting Link Prediction: A Data Perspective
Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages
Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, Dacheng Tao Reward Model Ensembles Help Mitigate Overoptimization
Thomas Coste, Usman Anwar, Robert Kirk, David Krueger Ring-a-Bell! How Reliable Are Concept Removal Methods for Diffusion Models?
Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie, Chih-Hsun Lin, Jia You Chen, Bo Li, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang Robot Fleet Learning via Policy Merging
Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula
Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo Robust Model-Based Optimization for Challenging Fitness Landscapes
Saba Ghaffari, Ehsan Saleh, Alex Schwing, Yu-Xiong Wang, Martin D. Burke, Saurabh Sinha Robust NAS Under Adversarial Training: Benchmark, Theory, and Beyond
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher Robust Similarity Learning with Difference Alignment Regularization
Shuo Chen, Gang Niu, Chen Gong, Okan Koc, Jian Yang, Masashi Sugiyama Robust Training of Federated Models with Extremely Label Deficiency
Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu, Bo Han Robustifying State-Space Models for Long Sequences via Approximate Diagonalization
Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Chegini, Wenxiao Wang, Soheil Feizi RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Jiayuan Gu, Sean Kirmani, Paul Wohlhart, Yao Lu, Montserrat Gonzalez Arenas, Kanishka Rao, Wenhao Yu, Chuyuan Fu, Keerthana Gopalakrishnan, Zhuo Xu, Priya Sundaresan, Peng Xu, Hao Su, Karol Hausman, Chelsea Finn, Quan Vuong, Ted Xiao S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
Safa Messaoud, Billel Mokeddem, Zhenghai Xue, Linsey Pang, Bo An, Haipeng Chen, Sanjay Chawla Safe and Robust Watermark Injection with a Single OoD Image
Shuyang Yu, Junyuan Hong, Haobo Zhang, Haotao Wang, Zhangyang Wang, Jiayu Zhou Safe Collaborative Filtering
Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
Yinan Zheng, Jianxiong Li, Dongjie Yu, Yujie Yang, Shengbo Eben Li, Xianyuan Zhan, Jingjing Liu Safe RLHF: Safe Reinforcement Learning from Human Feedback
Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, Yaodong Yang SafeDreamer: Safe Reinforcement Learning with World Models
Weidong Huang, Jiaming Ji, Chunhe Xia, Borong Zhang, Yaodong Yang Safety-Tuned LLaMAs: Lessons from Improving the Safety of Large Language Models That Follow Instructions
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Rottger, Dan Jurafsky, Tatsunori Hashimoto, James Zou SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang SALMON: Self-Alignment with Instructable Reward Models
Zhiqing Sun, Yikang Shen, Hongxin Zhang, Qinhong Zhou, Zhenfang Chen, David Daniel Cox, Yiming Yang, Chuang Gan SALMONN: Towards Generic Hearing Abilities for Large Language Models
Changli Tang, Wenyi Yu, Guangzhi Sun, Xianzhao Chen, Tian Tan, Wei Li, Lu Lu, Zejun Ma, Chao Zhang Sample-Efficient Quality-Diversity by Cooperative Coevolution
Ke Xue, Ren-Jian Wang, Pengyi Li, Dong Li, Jianye Hao, Chao Qian SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji SaProt: Protein Language Modeling with Structure-Aware Vocabulary
Jin Su, Chenchen Han, Yuyang Zhou, Junjie Shan, Xibin Zhou, Fajie Yuan Scalable and Effective Implicit Graph Neural Networks on Large Graphs
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao Scalable Diffusion for Materials Generation
Sherry Yang, KwangHwan Cho, Amil Merchant, Pieter Abbeel, Dale Schuurmans, Igor Mordatch, Ekin Dogus Cubuk Scalable Language Model with Generalized Continual Learning
Bohao Peng, Zhuotao Tian, Shu Liu, Ming-Chang Yang, Jiaya Jia Scalable Neural Network Kernels
Arijit Sehanobish, Krzysztof Marcin Choromanski, Yunfan Zhao, Kumar Avinava Dubey, Valerii Likhosherstov ScaleCrafter: Tuning-Free Higher-Resolution Visual Generation with Diffusion Models
Yingqing He, Shaoshu Yang, Haoxin Chen, Xiaodong Cun, Menghan Xia, Yong Zhang, Xintao Wang, Ran He, Qifeng Chen, Ying Shan Scaling Convex Neural Networks with Burer-Monteiro Factorization
Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci Scaling Laws for Associative Memories
Vivien Cabannes, Elvis Dohmatob, Alberto Bietti Scaling Laws for Sparsely-Connected Foundation Models
Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci Scaling Laws of RoPE-Based Extrapolation
Xiaoran Liu, Hang Yan, Chenxin An, Xipeng Qiu, Dahua Lin Score Models for Offline Goal-Conditioned Reinforcement Learning
Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, Robin Rombach SE(3)-Stochastic Flow Matching for Protein Backbone Generation
Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael M. Bronstein, Alexander Tong SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution
Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Xiaoyun Zhang, Yu Qiao, Xiao-Ming Wu, Chao Dong SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction
Xinyuan Chen, Yaohui Wang, Lingjun Zhang, Shaobin Zhuang, Xin Ma, Jiashuo Yu, Yali Wang, Dahua Lin, Yu Qiao, Ziwei Liu Select to Perfect: Imitating Desired Behavior from Large Multi-Agent Data
Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Nicolaus Foerster, Joao F. Henriques Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda, Venkatesh Babu Radhakrishnan Selective Visual Representations Improve Convergence and Generalization for Embodied AI
Ainaz Eftekhar, Kuo-Hao Zeng, Jiafei Duan, Ali Farhadi, Aniruddha Kembhavi, Ranjay Krishna Self-Alignment with Instruction Backtranslation
Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason E Weston, Mike Lewis Self-Consuming Generative Models Go MAD
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard Baraniuk Self-Supervised Dataset Distillation for Transfer Learning
Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang Self-Supervised Heterogeneous Graph Learning: A Homophily and Heterogeneity View
Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu Self-Supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment
Bowen Gao, Yinjun Jia, YuanLe Mo, Yuyan Ni, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan Self-Supervised Representation Learning from Random Data Projectors
Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs SemiReward: A General Reward Model for Semi-Supervised Learning
Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li Sentence-Level Prompts Benefit Composed Image Retrieval
Yang Bai, Xinxing Xu, Yong Liu, Salman Khan, Fahad Khan, Wangmeng Zuo, Rick Siow Mong Goh, Chun-Mei Feng Set Learning for Accurate and Calibrated Models
Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus Robert Muller Sharpness-Aware Data Poisoning Attack
Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang SILO Language Models: Isolating Legal Risk in a Nonparametric Datastore
Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer Simple Hierarchical Planning with Diffusion
Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji Single Motion Diffusion
Sigal Raab, Inbal Leibovitch, Guy Tevet, Moab Arar, Amit Haim Bermano, Daniel Cohen-Or Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang SKILL-MIX: A Flexible and Expandable Family of Evaluations for AI Models
Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora Skip-Attention: Improving Vision Transformers by Paying Less Attention
Shashanka Venkataramanan, Amir Ghodrati, Yuki M Asano, Fatih Porikli, Amir Habibian SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman SLiMe: Segment like Me
Aliasghar Khani, Saeid Asgari, Aditya Sanghi, Ali Mahdavi Amiri, Ghassan Hamarneh Small-Scale Proxies for Large-Scale Transformer Training Instabilities
Mitchell Wortsman, Peter J Liu, Lechao Xiao, Katie E Everett, Alexander A Alemi, Ben Adlam, John D Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith Social-Transmotion: Promptable Human Trajectory Prediction
Saeed Saadatnejad, Yang Gao, Kaouther Messaoud, Alexandre Alahi SOHES: Self-Supervised Open-World Hierarchical Entity Segmentation
Shengcao Cao, Jiuxiang Gu, Jason Kuen, Hao Tan, Ruiyi Zhang, Handong Zhao, Ani Nenkova, Liangyan Gui, Tong Sun, Yu-Xiong Wang Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-Based Self-Verification
Aojun Zhou, Ke Wang, Zimu Lu, Weikang Shi, Sichun Luo, Zipeng Qin, Shaoqing Lu, Anya Jia, Linqi Song, Mingjie Zhan, Hongsheng Li Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap Space Group Constrained Crystal Generation
Rui Jiao, Wenbing Huang, Yu Liu, Deli Zhao, Yang Liu SpaCE: The Spatial Confounding Environment
Mauricio Tec, Ana Trisovic, Michelle Audirac, Sophie Mirabai Woodward, Jie Kate Hu, Naeem Khoshnevis, Francesca Dominici Sparse Autoencoders Find Highly Interpretable Features in Language Models
Robert Huben, Hoagy Cunningham, Logan Riggs Smith, Aidan Ewart, Lee Sharkey SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation
Qianxu Wang, Haotong Zhang, Congyue Deng, Yang You, Hao Dong, Yixin Zhu, Leonidas Guibas Sparsistency for Inverse Optimal Transport
Francisco Andrade, Gabriel Peyré, Clarice Poon Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers
Yizhou Jiang, Kunlin Hu, Tianren Zhang, Haichuan Gao, Yuqian Liu, Ying Fang, Feng Chen Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin, Maria Florina Balcan, Pradeep Kumar Ravikumar Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM
Eliya Nachmani, Alon Levkovitch, Roy Hirsch, Julian Salazar, Chulayuth Asawaroengchai, Soroosh Mariooryad, Ehud Rivlin, Rj Skerry-Ryan, Michelle Tadmor Ramanovich SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
Tim Dettmers, Ruslan A. Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh Spurious Feature Diversification Improves Out-of-Distribution Generalization
Lin Yong, Lu Tan, Yifan Hao, Ho Nam Wong, Hanze Dong, Weizhong Zhang, Yujiu Yang, Tong Zhang Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine Stable Anisotropic Regularization
William Rudman, Carsten Eickhoff STARC: A General Framework for Quantifying Differences Between Reward Functions
Joar Max Viktor Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave, Alessandro Abate State Representation Learning Using an Unbalanced Atlas
Li Meng, Morten Goodwin, Anis Yazidi, Paal E. Engelstad Statistical Rejection Sampling Improves Preference Optimization
Tianqi Liu, Yao Zhao, Rishabh Joshi, Misha Khalman, Mohammad Saleh, Peter J Liu, Jialu Liu Stochastic Gradient Descent for Gaussian Processes Done Right
Jihao Andreas Lin, Shreyas Padhy, Javier Antoran, Austin Tripp, Alexander Terenin, Csaba Szepesvari, José Miguel Hernández-Lobato, David Janz Structural Fairness-Aware Active Learning for Graph Neural Networks
Haoyu Han, Xiaorui Liu, Li Ma, MohamadAli Torkamani, Hui Liu, Jiliang Tang, Makoto Yamada Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding
Yuanhao Xiong, Long Zhao, Boqing Gong, Ming-Hsuan Yang, Florian Schroff, Ting Liu, Cho-Jui Hsieh, Liangzhe Yuan Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
Yihuan Mao, Chengjie Wu, Xi Chen, Hao Hu, Ji Jiang, Tianze Zhou, Tangjie Lv, Changjie Fan, Zhipeng Hu, Yi Wu, Yujing Hu, Chongjie Zhang Submodular Reinforcement Learning
Manish Prajapat, Mojmir Mutny, Melanie Zeilinger, Andreas Krause Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri Mikulus Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari Sufficient Conditions for Offline Reactivation in Recurrent Neural Networks
Nanda H Krishna, Colin Bredenberg, Daniel Levenstein, Blake Aaron Richards, Guillaume Lajoie Supervised Knowledge Makes Large Language Models Better In-Context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Wei Ye, Xing Xie, Weizhu Chen, Yue Zhang SuRe: Summarizing Retrievals Using Answer Candidates for Open-Domain QA of LLMs
Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin SWAP-NAS: Sample-Wise Activation Patterns for Ultra-Fast NAS
Yameng Peng, Andy Song, Haytham M. Fayek, Vic Ciesielski, Xiaojun Chang SWE-Bench: Can Language Models Resolve Real-World GitHub Issues?
Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik R Narasimhan Synaptic Weight Distributions Depend on the Geometry of Plasticity
Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards SyncDreamer: Generating Multiview-Consistent Images from a Single-View Image
Yuan Liu, Cheng Lin, Zijiao Zeng, Xiaoxiao Long, Lingjie Liu, Taku Komura, Wenping Wang T-MARS: Improving Visual Representations by Circumventing Text Feature Learning
Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J Zico Kolter, Aditi Raghunathan TabR: Tabular Deep Learning Meets Nearest Neighbors
Yury Gorishniy, Ivan Rubachev, Nikolay Kartashev, Daniil Shlenskii, Akim Kotelnikov, Artem Babenko TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin Tag2Text: Guiding Vision-Language Model via Image Tagging
Xinyu Huang, Youcai Zhang, Jinyu Ma, Weiwei Tian, Rui Feng, Yuejie Zhang, Yaqian Li, Yandong Guo, Lei Zhang TAIL: Task-Specific Adapters for Imitation Learning with Large Pretrained Models
Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor Tailoring Self-Rationalizers with Multi-Reward Distillation
Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V Le, Denny Zhou TapMo: Shape-Aware Motion Generation of Skeleton-Free Characters
Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen, Xiaohang Zhan, Gang Yu, Ying Shan Teach LLMs to Phish: Stealing Private Information from Language Models
Ashwinee Panda, Christopher A. Choquette-Choo, Zhengming Zhang, Yaoqing Yang, Prateek Mittal Teaching Arithmetic to Small Transformers
Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, Kangwook Lee, Dimitris Papailiopoulos Teaching Language Models to Hallucinate Less with Synthetic Tasks
Erik Jones, Hamid Palangi, Clarisse Simões Ribeiro, Varun Chandrasekaran, Subhabrata Mukherjee, Arindam Mitra, Ahmed Hassan Awadallah, Ece Kamar Teaching Large Language Models to Self-Debug
Xinyun Chen, Maxwell Lin, Nathanael Schärli, Denny Zhou Tell Your Model Where to Attend: Post-Hoc Attention Steering for LLMs
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao TEMPO: Prompt-Based Generative Pre-Trained Transformer for Time Series Forecasting
Defu Cao, Furong Jia, Sercan O Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu Temporal Generalization Estimation in Evolving Graphs
Bin Lu, Tingyan Ma, Xiaoying Gan, Xinbing Wang, Yunqiang Zhu, Chenghu Zhou, Shiyu Liang Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell Test-Time Adaptation Against Multi-Modal Reliability Bias
Mouxing Yang, Yunfan Li, Changqing Zhang, Peng Hu, Xi Peng Text-to-3D with Classifier Score Distillation
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