ICLRW 2023

398 papers

$\mathrm{SE}(3)$ Frame Equivariance in Dynamics Modeling and Reinforcement Learning Linfeng Zhao, Jung Yeon Park, Xupeng Zhu, Robin Walters, Lawson L.S. Wong
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3D Graph Conditional Distributions via Semi-Equivariant Continuous Normalizing Flows Eyal Rozenberg, Ehud Rivlin, Daniel Freedman
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A Case Study on Designing Evaluations of ML Explanations with Simulated User Studies Ada Martin, Valerie Chen, Sérgio Jesus, Pedro Saleiro
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A Comprehensive Benchmark of Human-like Relational Reasoning for Text-to-Image Foundation Models Colin Conwell, Tomer Ullman
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A Framework for Fully Autonomous Design of Materials via Multiobjective Optimization and Active Learning: Challenges and Next Steps Tyler H Chang, Jakob R Elias, Stefan M. Wild, Santanu Chaudhuri, Joseph A. Libera
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A Framework for Grassroots Research Collaboration in Machine Learning and Global Health Christopher Brian Currin, Mercy Nyamewaa Asiedu, Chris Fourie, Benjamin Rosman, Houcemeddine Turki, Atnafu Lambebo Tonja, Jade Abbott, Marvellous Ajala, Sadiq Adewale Adedayo, Chris Chinenye Emezue, Daphne Machangara
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A Guide for Practical Use of ADMG Causal Data Augmentation Audrey Poinsot, Alessandro Leite
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A Kernel Density Estimation Based Quality Metric for Quality Assessment of Obstetric Ultrasound Video Jong Kwon, Jianbo Jiao, Alice Self, Alison Noble, Aris Papageorghiou
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A Kernel-Based View of Language Model Fine-Tuning Sadhika Malladi, Alexander Wettig, Dingli Yu, Danqi Chen, Sanjeev Arora
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A Machine Learning Approach to Generate Quantum Light Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer, Sivan Trajtenberg-Mills, Sarika Mishra, Shashi Prabhakar, Ravindra Pratap Singh, Daniel Freedman, Alex M. Bronstein, Ady Arie
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A Multi-Omics Visible Deep Network for Drug Activity Prediction Luigi Ferraro, Giovanni Scala, Luigi Cerulo, Emanuele Carosati, Michele Ceccarelli
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A Picture Is Worth a Thousand Words: Language Models Plan from Pixels Anthony Zhe Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
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A Tale of Two Circuits: Grokking as Competition of Sparse and Dense Subnetworks William Merrill, Nikolaos Tsilivis, Aman Shukla
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Accelerating Antimicrobial Peptide Discovery with Latent Sequence-Structure Model Danqing Wang, Zeyu Wen, Fei Ye, Lei Li, Hao Zhou
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Accelerating Neural Self-Improvement via Bootstrapping Kazuki Irie, Jürgen Schmidhuber
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Accelerating Policy Gradient by Estimating Value Function from Prior Computation in Deep Reinforcement Learning Md Masudur Rahman, Yexiang Xue
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Accurate Free Energy Estimations of Molecular Systems via Flow-Based Targeted Free Energy Perturbation Soo Jung Lee, Amr H Mahmoud, Markus Alexander Lill
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Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl
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ActiveLab: Active Learning with Re-Labeling by Multiple Annotators Hui Wen Goh, Jonas Mueller
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Adapting to the Low-Resource Double-Bind: Investigating Low-Compute Methods on Low-Resource African Languages Colin Leong, Herumb Shandilya, Bonaventure F. P. Dossou, Atnafu Lambebo Tonja, Joel Mathew, Abdul-Hakeem Omotayo, Oreen Yousuf, Zainab Akinjobi, Chris Chinenye Emezue, Shamsudeen Muhammad, Steven Kolawole, Younwoo Choi, Tosin Adewumi
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Adaptive Interventions for Global Health: A Case Study of Malaria Africa Perianez Santiago, Andrew Trister, Madhav Nekkar, Ana Fernandez del Rio, Pedro Alonso
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African Substrates Rather than European Lexifiers to Augment African-Diaspora Creole Translation Nathaniel Romney Robinson, Matthew Dean Stutzman, Stephen D. Richardson, David R Mortensen
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AfriNames: Most ASR Models "butcher" African Names Tobi Olatunji, Tejumade Afonja, Bonaventure F. P. Dossou, Atnafu Lambebo Tonja, Chris Chinenye Emezue, Amina Mardiyyah Rufai, Sahib Singh
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AfriSign: Machine Translation for African Sign Languages Shester Gueuwou, Kate Takyi, Mathias Müller, Marco Stanley Nyarko, Richard Adade, Rose-Mary Owusuaa Mensah Gyening
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AfroDigits: A Community-Driven Spoken Digit Dataset for African Languages Chris Chinenye Emezue, Sanchit Gandhi, Lewis Tunstall, Abubakar Abid, Joshua Meyer, Quentin Lhoest, Pete Allen, Patrick Von Platen, Douwe Kiela, Yacine Jernite, Julien Chaumond, Merve Noyan, Omar Sanseviero
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aiMotive Dataset: A Multimodal Dataset for Robust Autonomous Driving with Long-Range Perception Tamas Matuszka, Ivan Barton, Ádám Butykai, Péter Hajas, Dávid Kiss, Domonkos Kovács, Sándor Kunsági-Máté, Péter Lengyel, Gábor Németh, Levente Pető, Dezső Ribli, Dávid Szeghy, Szabolcs Vajna, Balint Viktor Varga
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Aligning Foundation Models for Language with Preferences Through $f$-Divergence Minimization Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman
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An Exploration of Conditioning Methods in Graph Neural Networks Yeskendir Koishekenov, Erik J Bekkers
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Analyzing Multimodal Objectives Through the Lens of Generative Diffusion Guidance Chaerin Kong, Nojun Kwak
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AROT-COV23: A Dataset of 500k Original Arabic Tweets on COVID-19 Cheng Xu, Nan Yan
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Augmentation Backdoors Joseph Rance, Yiren Zhao, Ilia Shumailov, Robert D. Mullins
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AWE: Adaptive Weight-Space Ensembling for Few-Shot Fine-Tuning Jean-Christophe Gagnon-Audet, Ricardo Pio Monti, David J. Schwab
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Backdoor Attacks Against Transformers with Attention Enhancement Weimin Lyu, Songzhu Zheng, Haibin Ling, Chao Chen
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BackdoorBox: A Python Toolbox for Backdoor Learning Yiming Li, Mengxi Ya, Yang Bai, Yong Jiang, Shu-Tao Xia
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Bayesian Regularization of Empirical MDPs Samarth Gupta, Daniel N. Hill, Lexing Ying, Inderjit S Dhillon
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Behavioral Cloning for Crystal Design Prashant Govindarajan, Santiago Miret, Jarrid Rector-Brooks, Mariano Phielipp, Janarthanan Rajendran, Sarath Chandar
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Benchmarking 3D Perception Robustness to Common Corruptions and Sensor Failure Lingdong Kong, Youquan Liu, Xin Li, Runnan Chen, Wenwei Zhang, Jiawei Ren, Liang Pan, Kai Chen, Ziwei Liu
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Benchmarking Bird's Eye View Detection Robustness to Real-World Corruptions Shaoyuan Xie, Lingdong Kong, Wenwei Zhang, Jiawei Ren, Liang Pan, Kai Chen, Ziwei Liu
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Beyond Confidence: Reliable Models Should Also Quantify Atypicality Mert Yuksekgonul, Linjun Zhang, James Zou, Carlos Guestrin
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Beyond Temporal Credit Assignment in Reinforcement Learning Sephora Madjiheurem, Kim Stachenfeld, Peter Battaglia, Jessica B Hamrick
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BITE: Textual Backdoor Attacks with Iterative Trigger Injection Jun Yan, Vansh Gupta, Xiang Ren
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Bootstrapped Representations in Reinforcement Learning Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G Bellemare, Will Dabney
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Breaking the Low-Resource Barrier for Dagbani ASR: From Data Collection to Modeling Paul Azunre, Naafi Dasana Ibrahim
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Broken Neural Scaling Laws Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger
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Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine
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Can Stochastic Weight Averaging Improve Generalization in Private Learning? Patrick Indri, Tamara Drucks, Thomas Gärtner
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CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs Konstantin Hemker, Zohreh Shams, Mateja Jamnik
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Chain-of-Thought Predictive Control Zhiwei Jia, Fangchen Liu, Vineet Thumuluri, Linghao Chen, Zhiao Huang, Hao Su
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CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets Zachary Novack, Julian McAuley, Zachary Chase Lipton, Saurabh Garg
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Classifier-Free Guidance Makes Image Captioning Models More Descriptive Simon Kornblith, Lala Li, Zirui Wang, Thao Nguyen
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CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover, Kai-Wei Chang
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CLEEGN: A Convolutional Neural Network for Plug-and-Play Automatic EEG Reconstruction Pin-Hua Lai, Wei-Chun Yang, Hsiang-Chieh Tsou, Chun-Shu Wei
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Clinical Trajectory Representations for Clustering Haobo Li, Alizée Pace, Martin Faltys, Gunnar Ratsch
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Clinically Relevant Unsupervised Online Representation Learning of ICU Waveforms Faris Faried Gulamali, Ashwin Shreekant Sawant, Ira Hofer, Matt Levin, Karandeep Singh, Benjamin S Glicksberg, Girish N Nadkarni
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Co-Imitation Learning Without Expert Demonstration Kun-Peng Ning, Hu Xu, Kun Zhu, Sheng-Jun Huang
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Compositional and Elemental Descriptors for Perovskite Materials Jiri Hostas, Maicon Pierre Lourenço, John Garcia, Hatef Shahmohamadi, Alain Tchagang, Karthik Shankar, Venkataraman Thangadurai, Dennis R. Salahub
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Concept Discovery and Dataset Exploration with Singular Value Decomposition Mara Graziani, An-phi Nguyen, Laura O'Mahony, Henning Müller, Vincent Andrearczyk
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Conformal Prediction Masks: Visualizing Uncertainty in Medical Imaging Gilad Kutiel, Regev Cohen, Michael Elad, Daniel Freedman, Ehud Rivlin
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Conservative Prediction via Transductive Confidence Minimization Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn
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Considerations for Distribution Shift Robustness in Health Arno Blaas, Andrew Miller, Luca Zappella, Joern-Henrik Jacobsen, Christina Heinze-Deml
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Constructing and Compressing Global Moment Descriptors from Local Atomic Environments Vahe Gharakhanyan, Max Shirokawa Aalto, Aminah Alsoulah, Nongnuch Artrith, Alexander Urban
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Controlled Assessment of CLIP-Style Language-Aligned Vision Models in Prediction of Brain & Behavioral Data Colin Conwell, Jacob S. Prince, Christopher J Hamblin, George A. Alvarez
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Controlling Dynamic Spatial Light Modulators Using Equivariant Neural Networks Sumukh Vasisht Shankar, Darrel D'Souza, Jonathan P Singer, Robin Walters
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Convolutional Neural Operators Bogdan Raonic, Roberto Molinaro, Tobias Rohner, Siddhartha Mishra, Emmanuel de Bezenac
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Cooperative Data-Driven Modeling: Continual Learning of Different Material Behavior Aleksandr Dekhovich, Ozgur Taylan Turan, Jiaxiang Yi, Miguel Anibal Bessa
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CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception Youngseok Kim, Sanmin Kim, Juyeb Shin, Jun Won Choi, Dongsuk Kum
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Cross-Domain Microscopy Cell Counting by Disentangled Transfer Learning Zuhui Wang
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Cross-Quality Few-Shot Transfer for Alloy Yield Strength Prediction: A New Material Science Benchmark and an Integrated Optimization Framework Xuxi Chen, Tianlong Chen, Everardo Yeriel Olivares, Kate Elder, Scott McCall, Aurelien Perron, Joseph McKeown, Bhavya Kailkhura, Zhangyang Wang, Brian Gallagher
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CrysGNN : Distilling Pre-Trained Knowledge to Enhance Property Prediction for Crystalline Materials. Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung-Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
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Crystal Structure Prediction by Joint Equivariant Diffusion on Lattices and Fractional Coordinates Rui Jiao, Wenbing Huang, Peijia Lin, Jiaqi Han, Pin Chen, Yutong Lu, Yang Liu
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DABS: Data-Agnostic Backdoor Attack at the Server in Federated Learning Wenqiang Sun, Sen Li, Yuchang Sun, Jun Zhang
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Deep Reinforcement Learning with Plasticity Injection Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto
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DeepEpiSolver: Unravelling Inverse Problems in Covid, HIV, Ebola and Disease Transmission Ritam Majumdar, Shirish Karande, Lovekesh Vig
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Denoising Diffusion Probabilistic Models to Predict the Number Density of Molecular Clouds in Astronomy Duo Xu, Jonathan Tan, Chia-Jung Hsu, Ye Zhu
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Designing Nonlinear Photonic Crystals for High-Dimensional Quantum State Engineering Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer, Sivan Trajtenberg-Mills, Sarika Mishra, Shashi Prabhakar, Ravindra Pratap Singh, Daniel Freedman, Alex M. Bronstein, Ady Arie
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Detecting Periodic Biases in Wearable-Based Illness Detection Models Amit Klein, Varun Kumar Viswanath, Benjamin Smarr, Edward Jay Wang
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DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stark, Menghua Wu, Gabriele Corso, Céline Marquet, Regina Barzilay, Tommi S. Jaakkola
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Differentiable Multi-Target Causal Bayesian Experimental Design Panagiotis Tigas, Yashas Annadani, Desi R. Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer
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Differentially Private Federated Few-Shot Image Classification Aliaksandra Shysheya, Marlon Tobaben, John F Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Beguelin, Richard E Turner, Antti Honkela
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Diffsurv: Differentiable Sorting for Censored Time-to-Event Data. Andre Vauvelle, Benjamin Wild, Aylin Cakiroglu, Roland Eils, Spiros Denaxas
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Diffusion Models Are Minimax Optimal Distribution Estimators Kazusato Oko, Shunta Akiyama, Taiji Suzuki
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Discovering Drag Reduction Strategies in Wall-Bounded Turbulent Flows Using Deep Reinforcement Learning Luca Guastoni, Jean Rabault, Philipp Schlatter, Ricardo Vinuesa, Hossein Azizpour
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Distribution Aware Active Learning via Gaussian Mixtures Younghyun Park, Dong-Jun Han, Jungwuk Park, Wonjeong Choi, Humaira Kousar, Jaekyun Moon
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Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation? Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke
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Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking? Yuejiang Yu, Shuqi Lu, Zhifeng Gao, Hang Zheng, Guolin Ke
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Do Embodied Agents Dream of Pixelated Sheep?: Embodied Decision Making Using Language Guided World Modelling Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, Roy Fox
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Do Models See Corruption as We See? an Item Response Theory Based Study in Computer Vision Charchit Sharma, Ayan Kumar Pahari, Deepak Vijaykeerthy, Vineeth N. Balasubramanian
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Do Tissue Source Sites Leave Identifiable Signatures in Whole Slide Images Beyond Staining? Muhammad Dawood, Piotr Keller, Fayyaz ul Amir Afsar Minhas
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Do Video-Language Foundation Models Have a Sense of Time? Piyush Nitin Bagad, Makarand Tapaswi, Cees G. M. Snoek
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DOG: Discriminator-Only Generation Franz Rieger, Joergen Kornfeld
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Domain-Aware Representation of Small Molecules for Explainable Property Prediction Models Sarveswara Rao Vangala, Sowmya Ramaswamy Krishnan, Navneet Bung, Rajgopal Srinivasan, Arijit Roy
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DORA: Exploring Outlier Representations in Deep Neural Networks Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus Robert Muller, Marina MC Höhne
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DP-Adam: Correcting DP Bias in Adam's Second Moment Estimation Qiaoyue Tang, Mathias Lécuyer
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Dynamic Pretraining of Vision-Language Models Aj Piergiovanni, Weicheng Kuo, Wei Li, Anelia Angelova
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DyNeMoC: A Semi-Supervised Architecture for Classifying Time Series Brain Data Abu Mohammad Shabbir Khan, Chetan Gohil, Pascal Notin, Joost van Amersfoort, Mark Woolrich, Yarin Gal
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E($3$) Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics Artur Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
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EDGI: Equivariant Diffusion for Planning with Embodied Agents Johann Brehmer, Joey Bose, Pim De Haan, Taco Cohen
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Effective Data Augmentation with Diffusion Models Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov
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Efficient Utilization of Pre-Trained Model for Learning with Noisy Labels Jongwoo Ko, Sumyeong Ahn, Se-Young Yun
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EigenFold: Generative Protein Structure Prediction with Diffusion Models Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi S. Jaakkola
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Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs George Pu, Anirudh Jain, Jihan Yin, Russell Kaplan
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Emulating Radiation Transport on Cosmological Scales Using a Denoising U-Net Mosima Masipa, Sultan Hassan, Mario Santos, Kyunghyun Cho, Gabriella Contardo
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Enabling Calibration in the Zero-Shot Inference of Large Vision-Language Models Will LeVine, Benjamin Pikus, Pranav Vishnu Raja, Fernando Amat
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Enhancing Healthcare Model Trustworthiness Through Theoretically Guaranteed One-Hidden-Layer CNN Purification Hanxiao Lu, Zeyu Huang, Ren Wang
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Enhancing Protein Language Model with Structure-Based Encoder and Pre-Training Zuobai Zhang, Minghao Xu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang
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Epigenomic Language Models Powered by Cerebras Meredith Trotter, Cuong Quoc Nguyen, Stephen Young, Rob Woodruff, Kim Branson
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Error Analysis of Tigrinya – English Machine Translation Systems Nuredin Ali Abdelkadir, Negasi Haile Abadi, Asmelash Teka Hadgu
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Error Discovery by Clustering Influence Embeddings Fulton Wang, Julius Adebayo, Sarah Tan, Diego Garcia-Olano, Narine Kokhlikyan
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EurNet: Efficient Multi-Range Relational Modeling of Protein Structure Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian
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Evaluating Prompt Tuning for Conditional Protein Sequence Generation Andrea Nathansen, Kevin Klein, Bernhard Y Renard, Melania Nowicka, Jakub M Bartoszewicz
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Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming Clemencia Siro, Tunde Oluwaseyi Ajayi
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Examining LLM's Awareness of the United Nations Sustainable Development Goals (SDGs) Mehdi Bahrami, Ramya Srinivasan
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ExBEHRT: Extended Transformer for Electronic Health Records Maurice Rupp, Oriane Peter, Thirupathi Pattipaka
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Expanding the Extrapolation Limits of Neural Network Force Fields Using Physics-Based Data Augmentation Yuliia Orlova, Gavin Keith Ridley, Frederick Zhao, Rafael Gomez-Bombarelli
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Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography Luca Franceschi, Cemre Zor, Muhammad Bilal Zafar, Gianluca Detommaso, Cedric Archambeau, Tamas Madl, Michele Donini, Matthias Seeger
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Explaintable: Explaining Large Scale Models Applied to Tabular Data Javier Sanguino Bautiste, Tim Engelmann, Natalia Pato Montemayor, Louis Hart, Giulia Lanzillotta, Gregor Bachmann, Thomas Hofmann
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Exploiting Category Names for Few-Shot Classification with Vision-Language Models Taihong Xiao, Zirui Wang, Liangliang Cao, Jiahui Yu, Shengyang Dai, Ming-Hsuan Yang
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Exploring a Gradient-Based Explainable AI Technique for Time-Series Data: A Case Study of Assessing Stroke Rehabilitation Exercises Min Hun Lee, Yi Jing Choy
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Exploring Chemical Space with Score-Based Out-of-Distribution Generation Seul Lee, Jaehyeong Jo, Sung Ju Hwang
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Exploring Demonstration Ensembling for In-Context Learning Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
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Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension Henry Kvinge, Davis Brown, Charles Godfrey
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Exploring Vulnerabilities of Semi-Supervised Learning to Simple Backdoor Attacks Marissa Catherine Connor, Vincent Emanuele
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Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim, Joshua Robinson, Stefanie Jegelka, Yaron Lipman, Haggai Maron
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Fairness-Aware Data Valuation for Supervised Learning José Pombal, Pedro Saleiro, Mario A. T. Figueiredo, Pedro Bizarro
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Fast Computation of Permutation Equivariant Layers with the Partition Algebra Charles Godfrey, Michael G. Rawson, Davis Brown, Henry Kvinge
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Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators Lennart Brocki, Neo Christopher Chung
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Feature-Interpretable Real Concept Drift Detection Pranoy Panda, Vineeth N. Balasubramanian, Gaurav Sinha
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Fedclip: Fast Generalization and Personalization for CLIP in Federated Learning Wang Lu, Xixu Hu, Jindong Wang, Xing Xie
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Federated Learning Aggregation via a Reinforcement Learning Policy Bear Häon, Adam Dunn, Jinman Kim, Chenyu Wang, Dongang Wang
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Federated Training of Dual Encoding Models on Small Non-Iid Client Datasets Raviteja Vemulapalli, Warren Richard Morningstar, Philip Andrew Mansfield, Hubert Eichner, Karan Singhal, Arash Afkanpour, Bradley Green
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Few-Shot Diagnosis of Chest X-Rays Using an Ensemble of Random Discriminative Subspaces Kshitiz, Garvit Garg, Angshuman Paul
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Fine-Tuning Multilingual Pretrained African Language Models Rozina Lucy Myoya, Fiskani Banda, Vukosi Marivate, Abiodun Modupe
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Flexible Small-Molecule Design and Optimization with Equivariant Diffusion Models Charles Harris, Kieran Didi, Arne Schneuing, Yuanqi Du, Arian Rokkum Jamasb, Michael M. Bronstein, Bruno Correia, Pietro Lio, Tom Leon Blundell
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FlexVDW: A Machine Learning Approach to Account for Protein Flexibility in Ligand Docking Patricia Adriana Suriana, Joseph M Paggi, Ron O. Dror
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ForecastPFN: Universal Forecasting for Healthcare Gurnoor Singh Khurana, Samuel Dooley, Siddartha Venkat Naidu, Colin White
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Forward and Inverse Design of High $T_C$ Superconductors with DFT and Deep Learning Daniel Wines, Kevin F Garrity, Tian Xie, Kamal Choudhary
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Fragment-Based Multi-View Molecular Contrastive Learning Seojin Kim, Jaehyun Nam, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin
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Gaussian Processes at the Helm(holtz): A More Fluid Model for Ocean Currents Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan James Giordano, Kaushik Srinivasan, Tamay Özgökmen, Junfei Zia, Tamara Broderick
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GCI: A (G)raph (C)oncept (I)nterpretation Framework Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Lio
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Generating Multi-Step Chemical Reaction Pathways with Black-Box Optimization Danny Reidenbach, Connor W. Coley, Kevin Yang
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Geometric Constraints Improve Inference of Sparsely Observed Stochastic Dynamics Dimitra Maoutsa
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Geometry-Based End-to-End Segmentation of Coronary Artery in Computed Tomography Angiograph Xiaoyu Yang, Lijian Xu, Simon Chun Ho Yu, Qing Xia, Hongsheng Li, Shaoting Zhang
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Geometry-Complete Diffusion for 3D Molecule Generation Alex Morehead, Jianlin Cheng
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GeValDi: Generative Validation of Discriminative Models Vivek Palaniappan, Matthew Ashman, Katherine M. Collins, Juyeon Heo, Adrian Weller, Umang Bhatt
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Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa Mercy Nyamewaa Asiedu, Awa Dieng, Abigail Oppong, Maria Nagawa, Oluwasanmi O Koyejo, Katherine A Heller
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GPT Detectors Are Biased Against Non-Native English Writers Weixin Liang, Mert Yuksekgonul, Yining Mao, Eric Wu, James Zou
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Graph Generation with Destination-Driven Diffusion Mixture Jaehyeong Jo, Dongki Kim, Sung Ju Hwang
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Graph-Informed Simulation-Based Inference for Models of Active Matter Namid Stillman, Silke Henkes, Roberto Mayor, Gilles Louppe
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GraphGUIDE: Interpretable and Controllable Conditional Graph Generation with Discrete Bernoulli Diffusion Alex M Tseng, Nathaniel Lee Diamant, Tommaso Biancalani, Gabriele Scalia
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Grounding Graph Network Simulators Using Physical Sensor Observations Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann
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Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners Seonghyeon Ye, Doyoung Kim, Joel Jang, Joongbo Shin, Minjoon Seo
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HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis Saheed Salahudeen Abdullahi, Falalu Ibrahim Lawan, Ahmad Mustapha Wali, Amina Abubakar Imam, Aliyu Rabiu Shuaibu, Yusuf Aliyu, Nur Bala Rabiu, Musa Bello, Shamsuddeen Umar Adamu, Saminu Mohammad Aliyu, Murja Sani Gadanya, Sanah Abdullahi Muaz, Mahmoud Said Ahmad, Abdulkadir Abdullahi, Abdulmalik Yusuf Jamoh
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HiGeN: HIERARCHICAL MULTI-RESOLUTION GRAPH GENERATIVE NETWORK Mahdi Karami, Jun Luo
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Holographic-(V)AE: An End-to-End SO(3)-Equivariant (Variational) Autoencoder in Fourier Space Gian Marco Visani, Michael Neal Pun, Arman Angaji, Armita Nourmohammad
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How Deep Convolutional Neural Networks Lose Spatial Information with Training Umberto Maria Tomasini, Leonardo Petrini, Francesco Cagnetta, Matthieu Wyart
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How Do Vision Transformers See Depth in Single Images? Peter Mortimer
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How Good Are Commercial Large Language Models on African Languages? Jessica Ojo, Kelechi Ogueji
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How to Backdoor Diffusion Models? Sheng-Yen Chou, Pin-Yu Chen, Tsung-Yi Ho
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How to Make Semi-Private Learning Effective Francesco Pinto, Yaxi Hu, Fanny Yang, Amartya Sanyal
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Hyperbolic Image-Text Representations Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Shanmukha Ramakrishna Vedantam
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Identifying Incorrect Annotations in Multi-Label Classification Data Aditya Thyagarajan, Elias Snorrason, Curtis G Northcutt, Jonas Mueller
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Igboner 2.0: Expanding Named Entity Recognition Datasets via Projection Chiamaka Ijeoma Chukwuneke, Paul Rayson, Ignatius Ezeani, Mo El-Haj, Doris Chinedu Asogwa, Chidimma Lilian Okpalla, Chinedu Emmanuel Mbonu
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IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters Xinshao Wang, Yang Hua, Elyor Kodirov, David A. Clifton, Neil M. Robertson
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Image Reconstruction from Event Cameras for Autonomous Driving Daniel Dauner
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Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods Harshit Sikchi, Amy Zhang, Scott Niekum
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Immunity Score Calibration Based on Vaccination Rebalancing Ferdous Nasri, Simon Cyrani, Lukas Wenner, Bernhard Y Renard
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Impossibility of Collective Intelligence Krikamol Muandet
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Improving Data Augmentation for Multi-Modality 3D Object Detection Wenwei Zhang, Zhe Wang, Chen Change Loy
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In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation Julian Bitterwolf, Maximilian Mueller, Matthias Hein
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In-Situ Anomaly Detection in Additive Manufacturing with Graph Neural Networks Sebastian Larsen, Paul A. Hooper
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Instruction-Finetuned Foundation Models for Multimodal Web Navigation Hiroki Furuta, Ofir Nachum, Kuang-Huei Lee, Yutaka Matsuo, Shixiang Shane Gu, Izzeddin Gur
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Language Models Are Visual Reasoning Coordinators Liangyu Chen, Bo Li, Sheng Shen, Jingkang Yang, Chunyuan Li, Kurt Keutzer, Trevor Darrell, Ziwei Liu
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Lexicon and Rule-Based Word Lemmatization Approach for Somali Language Shafie Abdi Mohamed, Muhidin A. Mohamed
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Long-Term Fairness with Unknown Dynamics Tongxin Yin, Reilly Raab, Mingyan Liu, Yang Liu
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Look Globally and Locally: Inter-Intra Contrastive Learning from Unlabeled Videos David Fan, Deyu Yang, Xinyu Li, Vimal Bhat, Rohith Mv
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Masked Trajectory Models for Prediction, Representation, and Control Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran
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Matbench Discovery - Can Machine Learning Identify Stable Crystals? Janosh Riebesell, Rhys Goodall, Anubhav Jain, Kristin Persson, Alpha Lee
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MatKB: Semantic Search for Polycrystalline Materials Synthesis Procedures Xianjun Yang, Stephen Wilson, Linda Petzold
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MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation Clement Vignac, Nagham Osman, Laura Toni, Pascal Frossard
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Modality-Aware Adaptation of Contrastive Language-Image Models Alexander Long, Thalaiyasingam Ajanthan, Anton van den Hengel
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Mode Connections for Clinical Incremental Learning:Lessons from the COVID-19 Pandemic Anshul Thakur, Chenyang Wang, Taha Ceritli, David Eyre, David A. Clifton
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Model-Based Adversarial Imitation Learning as Online Fine-Tuning Rafael Rafailov, Victor Kolev, Kyle Beltran Hatch, John D Martin, Mariano Phielipp, Jiajun Wu, Chelsea Finn
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Model-Based Unknown Input Estimation via Partially Observable Markov Decision Processes Wei Liu, Zhilu Lai, Charikleia Stoura, Kiran Bacsa, Eleni Chatzi
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MoDTI: Modular Framework for Evaluating Inductive Biases in DTI Modeling Roy Henha Eyono, Prudencio Tossou, Cas Wognum, Emmanuel Noutahi
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Molecular Fragment-Based Diffusion Model for Drug Discovery Daniel Levy, Jarrid Rector-Brooks
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MOTO: Offline to Online Fine-Tuning for Model-Based Reinforcement Learning Rafael Rafailov, Kyle Beltran Hatch, Victor Kolev, John D Martin, Mariano Phielipp, Chelsea Finn
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Multi-Environment Pretraining Enables Transfer to Action Limited Datasets David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum
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Multi-Scale Message Passing Neural PDE Solvers Léonard Equer, T. Konstantin Rusch, Siddhartha Mishra
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Multi-Scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data Gennady Voronov, Rose Lightheart, Joe Davison, Christoph A. Krettler, David Healey, Thomas Butler
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Multi-View Independent Component Analysis for Omics Data Integration Teodora Pandeva, Patrick Forré
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Multilevel Approach to Efficient Gradient Calculation in Stochastic Systems Joohwan Ko, Michael Poli, Stefano Massaroli, Woo Chang Kim
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Multilingual Automatic Speech Recognition for Kinyarwanda, Swahili, and Luganda: Advancing ASR in Select East African Languages Moayad Elamin, Yonas Chanie, Paul Ewuzie, Samuel Rutunda
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Multilingual Model and Data Resources for Text-to-Speech in Ugandan Languages Isaac Owomugisha, Benjamin Akera, Ernest Tonny Mwebaze, John Quinn
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Multimodal Subtask Graph Generation from Instructional Videos Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee
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Multiparameter Persistent Homology for Molecular Property Prediction Andac Demir, Bulent Kiziltan
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N2G: A Scalable Approach for Quantifying Interpretable Neuron Representation in LLMs Alex Foote, Neel Nanda, Esben Kran, Ioannis Konstas, Fazl Barez
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Natural Language Understanding for African Languages Pierrette MAHORO Mastel, Pierrette MAHORO Mastel, Ester Namara, Aime Munezero, Richard Kagame, Zihan Wang, Allan Anzagira, Akshat Gupta, Jema David Ndibwile
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Nature's Cost Function: Simulating Physics by Minimizing the Action Samuel James Greydanus, Timothy David Strang, Isabella Caruso
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Neural Integral Functionals Zheyuan Hu, Tianbo Li, Zekun Shi, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, Shuicheng Yan, Min Lin
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Neural MPC-Based Decision-Making Framework for Autonomous Driving in Multi-Lane Roundabout Yao Mu, Zhiqian Lan, Chang Liu, Ping Luo, Shengbo Eben Li
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Neural Networks Learn Representation Theory: Reverse Engineering How Networks Perform Group Operations Bilal Chughtai, Lawrence Chan, Neel Nanda
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Neural-Prior Stochastic Block Model O. Duranthon, Lenka Zdeborova
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Noise Injection as a Probe of Deep Learning Dynamics Noam Itzhak Levi, Itay Mimouni Bloch, Marat Freytsis, Tomer Volansky
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Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations Shashank Shekhar, Florian Bordes, Pascal Vincent, Ari S. Morcos
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Online Threats Detection in Hausa Language Abubakar Yakubu Zandam, Fatima Adam Muhammad, Isa Inuwa-Dutse
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PDExplain: Contextual Modeling of PDEs in the Wild Ori Linial, Orly Avner, Dotan Di Castro
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Predicting Fluid Dynamics in Physical-Informed Mesh-Reduced Space Yeping Hu, Bo Lei, Victor M Castillo
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Predicting Out-of-Distribution Error with Confidence Optimal Transport Yuzhe Lu, Zhenlin Wang, Runtian Zhai, Soheil Kolouri, Joseph Campbell, Katia P. Sycara
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Pretrained Vision Models for Predicting High-Risk Breast Cancer Stage Bonaventure F. P. Dossou, Yeno Gbenou, Miglanche Ghomsi
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Privately Customizing Prefinetuning to Better Match User Data in Federated Learning Charlie Hou, Hongyuan Zhan, Akshat Shrivastava, Sid Wang, Aleksandr Livshits, Giulia Fanti, Daniel Lazar
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Probing Optimisation in Physics-Informed Neural Networks Nayara Fonseca, Veronica Guidetti, Will Trojak
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Quantum Feature Maps for Graph Machine Learning on a Neutral Atom Quantum Processor Boris Albrecht, Constantin Dalyac, Lucas Leclerc, Luis Ortiz-Gutiérrez, Slimane Thabet, Mauro D'Arcangelo, Vincent Emanuel Elfving, Lucas Lassablière, Henrique Silvério, Bruno Ximenez, Louis-Paul Henry, Adrien Signoles, Loic Henriet
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Reconstructing Training Data from Multiclass Neural Networks Gon Buzaglo, Niv Haim, Gilad Yehudai, Gal Vardi, Michal Irani
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Reduce, Reuse, Recycle: Selective Reincarnation in Multi-Agent Reinforcement Learning Juan Claude Formanek, Callum Rhys Tilbury, Jonathan Phillip Shock, Kale-ab Tessera, Arnu Pretorius
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Relational Macrostate Theory Guides Artificial Intelligence to Learn Macro and Design Micro Yanbo Zhang, Sara Walker
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Removing Backdoor Behaviors with Unlabeled Data Lu Pang, Tao Sun, Haibin Ling, Chao Chen
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Rethinking the Necessity of Labels in Backdoor Removal Zidi Xiong, Dongxian Wu, Yifei Wang, Yisen Wang
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Robustifying Language Models with Test-Time Adaptation Noah Thomas McDermott, Junfeng Yang, Chengzhi Mao
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Secure Federated Learning Against Model Poisoning Attacks via Client Filtering Duygu Nur Yaldiz, Tuo Zhang, Salman Avestimehr
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Self-Generating Data for Goal-Conditioned Compositional Problems Ying Yuan, Yunfei Li, Yi Wu
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Simple Hardware-Efficient Long Convolutions for Sequence Modeling Daniel Y Fu, Elliot L Epstein, Eric Nguyen, Armin W Thomas, Michael Zhang, Tri Dao, Atri Rudra, Christopher Re
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SimuStruct: Simulated Structural Plate with Holes Dataset with Machine Learning Applications Bruno Alves Ribeiro, João Alves Ribeiro, Faez Ahmed, Hugo Penedones, Jorge Belinha, Luís Sarmento, Miguel Anibal Bessa, Sérgio Tavares
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SmilesFormer: Language Model for Molecular Design Joshua Owoyemi, Nazim Medzhidov
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Sound-Based Sleep Staging by Exploiting Real-World Unlabeled Data JongMok Kim, Daewoo Kim, Eunsung Cho, Hai Hong Tran, Joonki Hong, Dongheon Lee, JungKyung Hong, In-Young Yoon, Jeong-Whun Kim, Hyeryung Jang, Nojun Kwak
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Speech Recognition Datasets for Low-Resource Congolese Languages Ussen Abre Kimanuka, Ciira wa Maina, Osman Büyük
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Stability of Implicit Neural Networks for Long-Term Forecasting in Dynamical Systems Léon Migus, Julien Salomon, Patrick Gallinari
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STAGCN: Spatial-Temporal Attention Based Graph Convolutional Networks for COVID-19 Forecasting Nevasini Sasikumar, Krishna Sri Ipsit Mantri
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Stasis: Reinforcement Learning Simulators for Human-Centric Real-World Environments Georgios Efstathiadis, Patrick Emedom-Nnamdi, Arinbjörn Kolbeinsson, Jukka-Pekka Onnela, Junwei Lu
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Stationary Deep Reinforcement Learning with Quantum K-Spin Hamiltonian Regularization Xiao-Yang Liu, Zechu Li, Shixun Wu, Xiaodong Wang
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Structure-Based Drug Design via Semi-Equivariant Conditional Normalizing Flows Eyal Rozenberg, Ehud Rivlin, Daniel Freedman
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Studying Phase Transitions in Contrastive Learning with Physics-Inspired Datasets Ali Cy, Anugrah Chemparathy, Michael Han, Rumen Dangovski, Peter Y. Lu, Marin Soljacic
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Subnational Analysis of the Initial Phase of the COVID-19 Epidemic in Brazil T A Mellan, Henrique Hoeltgebaum, Swapnil Mishra, Charles Whittaker, Iwona Hawryluk, Axel Gandy, H Juliette T Unwin, Michaela A C Vollmer, Helen Coupland, Nuno Rodrigues Faria, Juan Vesga, Neil M Ferguson, Ricardo P Schnekenberg, Christl A Donelly, Harrison Zhu, Michael John Hutchinson, Oliver Ratmann, Melodie Monod, Seth Flaxman, Samir Bhatt
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Successor Feature Representations Chris Reinke, Xavier Alameda-Pineda
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Superhuman Fairness Omid Memarrast, Linh Vu, Brian D Ziebart
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SupSiam: Non-Contrastive Auxiliary Loss for Learning from Molecular Conformers Michael Maser, Ji Won Park, Joshua Yao-Yu Lin, Jae Hyeon Lee, Nathan C. Frey, Andrew Martin Watkins
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Swarm Reinforcement Learning for Adaptive Mesh Refinement Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Luise Kärger, Gerhard Neumann
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Symbolic Regression for PDEs Using Pruned Differentiable Programs Ritam Majumdar, Vishal Sudam Jadhav, Anirudh Deodhar, Shirish Karande, Lovekesh Vig, Venkataramana Runkana
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Synthetic Data Generator for Adaptive Interventions in Global Health Aditya Rastogi, Juan Francisco Garamendi, Ana Fernandez del Rio, Anna Guitart Atienza, Moiz Hassan Khan, Dexian Tang, Africa Perianez Santiago
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Synthetic Experience Replay Cong Lu, Philip J. Ball, Jack Parker-Holder
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TabRet: Pre-Training Transformer-Based Tabular Models for Unseen Columns Soma Onishi, Kenta Oono, Kohei Hayashi
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Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor
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Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Yiren Zhao, Pietro Lio
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Text-to-Image Diffusion Models Are Zero-Shot Classifiers Kevin Clark, Priyank Jaini
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TGRL: Teacher Guided Reinforcement Learning Algorithm for POMDPs Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal
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The Effects of Pretraining Task Diversity on In-Context Learning of Ridge Regression Allan Raventos, Mansheej Paul, Feng Chen, Surya Ganguli
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The END: An Equivariant Neural Decoder for Quantum Error Correction Evgenii Egorov, Roberto Bondesan, Max Welling
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The First Large Scale Collection of Diverse Hausa Language Datasets Isa Inuwa-Dutse
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The Independent Compositional Subspace Hypothesis for the Structure of CLIP's Last Layer Max Wolff, Wieland Brendel, Stuart Wolff
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The Power of Motifs as Inductive Bias for Learning Molecular Distributions Johanna Sommer, Leon Hetzel, David Lüdke, Fabian J Theis, Stephan Günnemann
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The Rl Perceptron: Dynamics of Policy Learning in High Dimensions Nishil Patel, Sebastian Lee, Stefano Sarao Mannelli, Sebastian Goldt, Andrew M Saxe
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The Role of Pre-Training Data in Transfer Learning Rahim Entezari, Mitchell Wortsman, Olga Saukh, M. Moein Shariatnia, Hanie Sedghi, Ludwig Schmidt
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The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien Cabannes, Bobak Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
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Think Before You Act: Unified Policy for Interleaving Language Reasoning with Actions Lina Mezghani, Piotr Bojanowski, Karteek Alahari, Sainbayar Sukhbaatar
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Tigrinya Dialect Identification Asfaw Gedamu Haileslasie, Asmelash Teka Hadgu, Solomon Teferra Abate
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Time Series as Images: Vision Transformer for Irregularly Sampled Time Series Zekun Li, Shiyang Li, Xifeng Yan
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Time-Dependent Iterative Imputation for Multivariate Longitudinal Clinical Data Omer Noy, Ron Shamir
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Towards a Unified Agent with Foundation Models Norman Di Palo, Arunkumar Byravan, Leonard Hasenclever, Markus Wulfmeier, Nicolas Heess, Martin Riedmiller
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Towards an Inductive Bias for Quantum Statistics in GANs Hugo Wallner, William R Clements
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Towards Antigenic Peptide Discovery with Better MHC-I Binding Prediction and Improved Benchmark Methodology Stanisław Giziński, Grzegorz Preibisch, Piotr Kucharski, Michał Tyrolski, Michał Rembalski, Piotr Grzegorczyk, Anna Gambin
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Towards Foundation Models with Mathematical Understanding Peter Belcak, Roger Wattenhofer
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Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer, Huan Sun
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Towards Understanding the Modality Gap in CLIP Peiyang Shi, Michael C. Welle, Mårten Björkman, Danica Kragic
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Training, Architecture, and Prior for Deterministic Uncertainty Methods Bertrand Charpentier, Chenxiang Zhang, Stephan Günnemann
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Transfer Learning with Diffusion Model for Polymer Property Prediction Gang Liu, Meng Jiang
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Trustworthy Model Evaluation on a Budget Iordanis Fostiropoulos, Bowman Noah Brown, Laurent Itti
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Understanding Health Effects of Particulate Matter Sources by Using Stochastic Machine Learning Models Georges Bucyibaruta, Monica Pirani, Marta Blangiardo, Gary Fuller, David Green, Anja Tremper, Christina Mitsakou
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Understanding HTML with Large Language Models Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin V Huang, Aakanksha Chowdhery, Sharan Narang, Noah Fiedel, Aleksandra Faust
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Understanding the Class-Specific Effects of Data Augmentations Polina Kirichenko, Randall Balestriero, Mark Ibrahim, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson
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Uni-Fold MuSSe: De Novo Protein Complex Prediction with Protein Language Models Jinhua Zhu, Zhenyu He, Ziyao Li, Guolin Ke, Linfeng Zhang
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Unlearning Backdoor Attacks in Federated Learning Chen Wu, Sencun Zhu, Prasenjit Mitra
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Unsupervised Object Interaction Learning with Counterfactual Dynamics Models Jongwook Choi, Sungtae Lee, Xinyu Wang, Sungryull Sohn, Honglak Lee
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Use TensorRT Network Definition API and Plugin to Deploy 3D Object Detection Algorithm SE-SSD Yibo Guo
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Variable Discretization for Self-Supervised Learning Chuang Niu, Wenjun Xia, Ge Wang
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Variational Modelling of Temporal Ehrs for Phenotypic Clustering Henrique Aguiar, Mauro Santos, Peter Watkinson, Tingting Zhu
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Variational Prompt Tuning Improves Generalization of Vision-Language Foundation Models Mohammad Mahdi Derakhshani, Enrique Sanchez, Adrian Bulat, Victor Guilherme Turrisi da Costa, Cees G. M. Snoek, Georgios Tzimiropoulos, Brais Martinez
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VoxMg: An Automatic Speech Recognition Dataset for Malagasy Falia Ramanantsoa
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What Contrastive Learning Learns Beyond Class-Wise Features? Xingyuming Liu, Yifei Wang, Yisen Wang
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What Happens to the Source Domain in Transfer Learning? Amal Alnouri, Bilal Alsallakh
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Where Are We in the Search for an Artificial Visual Cortex for Embodied Intelligence? Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier
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Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers Damai Dai, Yutao Sun, Li Dong, Yaru Hao, Shuming Ma, Zhifang Sui, Furu Wei
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Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition Through the Lens of Robustness Yanqi Cheng, Lihao Liu, Shujun Wang, Yueming Jin, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero
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Workshop Submission: Using Multimodal DNNs to Study Vision-Language Integration in the Brain Vighnesh Subramaniam, Colin Conwell, Christopher Wang, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu
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XMI-ICU: Explainable Machine Learning Model for Pseudo-Dynamic Prediction of Mortality and Heart Attack in the ICU Munib Mesinovic, Tingting Zhu
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Yoruba and Unicode: An Overview of a Problem Kolawole Olatubosun
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Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations Xinxi Lyu, Sewon Min, Iz Beltagy, Luke Zettlemoyer, Hannaneh Hajishirzi
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Zero Redundancy Distributed Learning with Differential Privacy Zhiqi Bu, Justin Chiu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis
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Ε Kú <MASK>: Integrating Yorùbá Cultural Greetings into Machine Translation Idris Akinade, Jesujoba Oluwadara Alabi, David Ifeoluwa Adelani, Clement Oyeleke Odoje, Dietrich Klakow
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