Chen, Tianlong

157 publications

NeurIPS 2025 $\texttt{BetaConform}$: Efficient MAP Estimation of LLM Ensemble Judgment Performance with Prior Transfer Huaizhi Qu, Inyoung Choi, Zhen Tan, Song Wang, Sukwon Yun, Qi Long, Faizan Siddiqui, Kwonjoon Lee, Tianlong Chen

ICML 2025 $\texttt{I}$^2$MoE$: Interpretable Multimodal Interaction-Aware Mixture-of-Experts Jiayi Xin, Sukwon Yun, Jie Peng, Inyoung Choi, Jenna L. Ballard, Tianlong Chen, Qi Long

TMLR 2025 A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning Prateek Yadav, Colin Raffel, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni

ICLR 2025 Adapt-$\infty$: Scalable Continual Multimodal Instruction Tuning via Dynamic Data Selection Adyasha Maharana, Jaehong Yoon, Tianlong Chen, Mohit Bansal

AAAI 2025 BrainMAP: Learning Multiple Activation Pathways in Brain Networks Song Wang, Zhenyu Lei, Zhen Tan, Jiaqi Ding, Xinyu Zhao, Yushun Dong, Guorong Wu, Tianlong Chen, Chen Chen, Aiying Zhang, Jundong Li

NeurIPS 2025 BrainMoE: Cognition Joint Embedding via Mixture-of-Expert Towards Robust Brain Foundation Model Ziquan Wei, Tingting Dan, Tianlong Chen, Guorong Wu

AAAI 2025 Breaking the Resource Monopoly from Industries: Sustainable and Reliable LLM Serving by Recycling Outdated and Resource-Constrained GPUs Tianlong Chen

ICLR 2025 Composable Interventions for Language Models Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Jayant Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen

ICLR 2025 Cut the Crap: An Economical Communication Pipeline for LLM-Based Multi-Agent Systems Guibin Zhang, Yanwei Yue, Zhixun Li, Sukwon Yun, Guancheng Wan, Kun Wang, Dawei Cheng, Jeffrey Xu Yu, Tianlong Chen

AAAI 2025 DLF: Disentangled-Language-Focused Multimodal Sentiment Analysis Pan Wang, Qiang Zhou, Yawen Wu, Tianlong Chen, Jingtong Hu

ICLRW 2025 DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs Zhen Tan, Daize Dong, Xinyu Zhao, Jianing Cai, Jie Peng, Yu Cheng, Tianlong Chen

DMLR 2025 Deep Learning for Accurate Diagnosis of Viral Infections Through scRNA-Seq Analysis: A Comprehensive Benchmark Study Ziwei Yang, Xuxi Chen, Biqing Zhu, Tianlong Chen, Zhangyang Wang

ICML 2025 G-Designer: Architecting Multi-Agent Communication Topologies via Graph Neural Networks Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng

ICLRW 2025 G-Designer: Architecting Multi-Agent Communication Topologies via Graph Neural Networks Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng

ICLR 2025 Graph Sparsification via Mixture of Graphs Guibin Zhang, Xiangguo Sun, Yanwei Yue, Chonghe Jiang, Kun Wang, Tianlong Chen, Shirui Pan

NeurIPS 2025 IndustryEQA: Pushing the Frontiers of Embodied Question Answering in Industrial Scenarios Yifan Li, Yuhang Chen, Anh Dao, Lichi Li, Zhongyi Cai, Zhen Tan, Tianlong Chen, Yu Kong

AAAI 2025 Mapping from Meaning: Addressing the Miscalibration of Prompt-Sensitive Language Models Kyle Cox, Jiawei Xu, Yikun Han, Rong Xu, Tianhao Li, Chi-Yang Hsu, Tianlong Chen, Walter Gerych, Ying Ding

ICML 2025 Modalities Contribute Unequally: Enhancing Medical Multi-Modal Learning Through Adaptive Modality Token Re-Balancing Jie Peng, Jenna L. Ballard, Mohan Zhang, Sukwon Yun, Jiayi Xin, Qi Long, Yanyong Zhang, Tianlong Chen

NeurIPS 2025 Mozart: Modularized and Efficient MoE Training on 3.5d Wafer-Scale Chiplet Architectures Shuqing Luo, Ye Han, Pingzhi Li, Jiayin Qin, Jie Peng, Yang Katie Zhao, Yu Cao, Tianlong Chen

NeurIPS 2025 Multi-Agent Debate for LLM Judges with Adaptive Stability Detection Tianyu Hu, Zhen Tan, Song Wang, Huaizhi Qu, Tianlong Chen

ICML 2025 Occult: Optimizing Collaborative Communications Across Experts for Accelerated Parallel MoE Training and Inference Shuqing Luo, Pingzhi Li, Jie Peng, Yang Zhao, Yu Cao, Yu Cheng, Tianlong Chen

NeurIPS 2025 One Token Embedding Is Enough to Deadlock Your Large Reasoning Model Mohan Zhang, Yihua Zhang, Jinghan Jia, Zhangyang Wang, Sijia Liu, Tianlong Chen

ICLR 2025 PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches Rana Shahroz, Pingzhi Li, Sukwon Yun, Zhenyu Wang, Shahriar Nirjon, Chau-Wai Wong, Tianlong Chen

ICLR 2025 Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility Martin Kuo, Jingyang Zhang, Jianyi Zhang, Minxue Tang, Louis DiValentin, Aolin Ding, Jingwei Sun, William Chen, Amin Hass, Tianlong Chen, Yiran Chen, Hai Li

TMLR 2025 Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning Andy Li, Aiden Durrant, Milan Markovic, Tianjin Huang, Souvik Kundu, Tianlong Chen, Lu Yin, Georgios Leontidis

CPAL 2025 Sparse MoE as a New Treatment: Addressing Forgetting, Fitting, Learning Issues in Multi-Modal Multi-Task Learning Jie Peng, Sukwon Yun, Kaixiong Zhou, Ruida Zhou, Thomas Hartvigsen, Yanyong Zhang, Zhangyang Wang, Tianlong Chen

AAAI 2025 Sparse Transfer Learning Accelerates and Enhances Certified Robustness: A Comprehensive Study Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang

ICLRW 2025 Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam Tianjin Huang, Haotian Hu, Zhenyu Zhang, Gaojie Jin, Xiang Li, Li Shen, Tianlong Chen, Lu Liu, Qingsong Wen, Zhangyang Wang, Shiwei Liu

ICCV 2025 Towards Stabilized and Efficient Diffusion Transformers Through Long-Skip-Connections with Spectral Constraints Guanjie Chen, Xinyu Zhao, Yucheng Zhou, Xiaoye Qu, Tianlong Chen, Yu Cheng

AAAI 2025 Tuning-Free Accountable Intervention for LLM Deployment - A Metacognitive Approach Zhen Tan, Jie Peng, Song Wang, Lijie Hu, Tianlong Chen, Huan Liu

AAAI 2025 Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen

CVPRW 2025 Window Token Concatenation for Efficient Visual Large Language Models Yifan Li, Wentao Bao, Botao Ye, Zhen Tan, Tianlong Chen, Huan Liu, Yu Kong

CPAL 2025 You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-Offs at Inference Time Xiaotian Han, Tianlong Chen, Kaixiong Zhou, Zhimeng Jiang, Zhangyang Wang, Xia Hu

ICML 2024 $\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts Guanjie Chen, Xinyu Zhao, Tianlong Chen, Yu Cheng

NeurIPS 2024 $\texttt{Model-GLUE}$: Democratized LLM Scaling for a Large Model Zoo in the Wild Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen

ICLRW 2024 Composing Knowledge and Compression Interventions for Language Models Arinbjörn Kolbeinsson, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Jayant Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen

CPAL 2024 Cross-Quality Few-Shot Transfer for Alloy Yield Strength Prediction: A New Materials Science Benchmark and a Sparsity-Oriented Optimization Framework Xuxi Chen, Tianlong Chen, Everardo Yeriel Olivares, Kate Elder, Scott McCall, Aurelien Perron, Joseph McKeown, Bhavya Kailkhura, Zhangyang Wang, Brian Gallagher

NeurIPSW 2024 Demo: An Exploration of LLM-Guided Conversation in Reminiscence Therapy Jinhao Duan, Xinyu Zhao, Zhuoxuan Zhang, Eunhye Grace Ko, Lily Boddy, Chenan Wang, Tianhao Li, Alexander Rasgon, Junyuan Hong, Min Kyung Lee, Chenxi Yuan, Qi Long, Ying Ding, Tianlong Chen, Kaidi Xu

ICLRW 2024 Demystify the Secret Function in Protein Sequence via Conditional Diffusion Models Yaoyao Xu, Xuxi Chen, Tong Wang, Huan He, Tianlong Chen, Manolis Kellis

ICML 2024 Evolution-Inspired Loss Functions for Protein Representation Learning Chengyue Gong, Adam Klivans, James Madigan Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz

ICLRW 2024 Evolution-Inspired Loss Functions for Protein Representation Learning Chengyue Gong, Adam Klivans, James Madigan Loy, Tianlong Chen, Qiang Liu, Daniel Jesus Diaz

ECCV 2024 Facial Affective Behavior Analysis with Instruction Tuning Yifan Li, Anh Dao, Wentao Bao, Zhen Tan, Tianlong Chen, Huan Liu, Yu Kong

NeurIPS 2024 Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts Sukwon Yun, Inyoung Choi, Jie Peng, Yangfan Wu, Jingxuan Bao, Qiyiwen Zhang, Jiayi Xin, Qi Long, Tianlong Chen

NeurIPS 2024 GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning Guibin Zhang, Haonan Dong, Yuchen Zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang

NeurIPS 2024 GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu

CPAL 2024 HRBP: Hardware-Friendly Regrouping Towards Block-Based Pruning for Sparse CNN Training Haoyu Ma, Chengming Zhang, Lizhi Xiang, Xiaolong Ma, Geng Yuan, Wenkai Zhang, Shiwei Liu, Tianlong Chen, Dingwen Tao, Yanzhi Wang, Zhangyang Wang, Xiaohui Xie

ICLR 2024 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

ECCV 2024 Mew: Multiplexed Immunofluorescence Image Analysis Through an Efficient Multiplex Network Sukwon Yun, Jie Peng, Alexandro E Trevino, Chanyoung Park, Tianlong Chen

CVPR 2024 Molecular Data Programming: Towards Molecule Pseudo-Labeling with Systematic Weak Supervision Xin Juan, Kaixiong Zhou, Ninghao Liu, Tianlong Chen, Xin Wang

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

ICMLW 2024 Pre-Training of Single-Cell Language Models Through Genetic Pathway Learning Xuxi Chen, Zhangyang Wang, Marinka Zitnik, Manolis Kellis, Tianlong Chen

ICLRW 2024 Privacy-Preserving Fine-Tuning of Large Language Models Through Flatness Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei

ICML 2024 Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen

ICML 2024 Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All at Once Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang

ICLR 2024 Sparse MoE with Language Guided Routing for Multilingual Machine Translation Xinyu Zhao, Xuxi Chen, Yu Cheng, Tianlong Chen

NeurIPSW 2024 Sparse Transfer Learning Accelerates and Enhances Certified Robustness: A Comprehensive Study Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang

AAAI 2024 Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention Zhen Tan, Tianlong Chen, Zhenyu Zhang, Huan Liu

CVPR 2024 TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models Yushi Huang, Ruihao Gong, Jing Liu, Tianlong Chen, Xianglong Liu

ICML 2024 Two Heads Are Better than One: Boosting Graph Sparse Training via Semantic and Topological Awareness Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen

TMLR 2024 Unlearning Sensitive Information in Multimodal LLMs: Benchmark and Attack-Defense Evaluation Vaidehi Patil, Yi-Lin Sung, Peter Hase, Jie Peng, Tianlong Chen, Mohit Bansal

CVPRW 2023 Accelerable Lottery Tickets with the Mixed-Precision Quantization Zhangheng Li, Yu Gong, Zhenyu Zhang, Xingyun Xue, Tianlong Chen, Yi Liang, Bo Yuan, Zhangyang Wang

ICCV 2023 AdaMV-MoE: Adaptive Multi-Task Vision Mixture-of-Experts Tianlong Chen, Xuxi Chen, Xianzhi Du, Abdullah Rashwan, Fan Yang, Huizhong Chen, Zhangyang Wang, Yeqing Li

WACV 2023 Attend Who Is Weak: Pruning-Assisted Medical Image Localization Under Sophisticated and Implicit Imbalances Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang

TMLR 2023 Can Pruning Improve Certified Robustness of Neural Networks? Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang

ICLRW 2023 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

ECML-PKDD 2023 Enhancing Adversarial Training via Reweighting Optimization Trajectory Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy

ICCV 2023 Enhancing NeRF Akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts Wenyan Cong, Hanxue Liang, Peihao Wang, Zhiwen Fan, Tianlong Chen, Mukund Varma, Yi Wang, Zhangyang Wang

ICLR 2023 Graph Domain Adaptation via Theory-Grounded Spectral Regularization Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

ICML 2023 Graph Ladling: Shockingly Simple Parallel GNN Training Without Intermediate Communication Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

NeurIPS 2023 H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang "Atlas" Wang, Beidi Chen

ICMLW 2023 H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Re, Clark Barrett, Zhangyang Wang, Beidi Chen

ICLR 2023 HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew Ellington, Alex Dimakis, Adam Klivans

ICML 2023 Instant Soup: Cheap Pruning Ensembles in a Single Pass Can Draw Lottery Tickets from Large Models Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

ICLR 2023 Is Attention All That NeRF Needs? Mukund Varma T, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

AISTATS 2023 Learning to Generalize Provably in Learning to Optimize Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang

ICML 2023 Learning to Optimize Differentiable Games Xuxi Chen, Nelson Vadori, Tianlong Chen, Zhangyang Wang

ICLR 2023 M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang

ICLR 2023 More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 Using Sparsity Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang

AAAI 2023 Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang

ICCV 2023 Robust Mixture-of-Expert Training for Convolutional Neural Networks Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu

ICLR 2023 Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang

ICLR 2023 Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang

NeurIPS 2023 The Emergence of Essential Sparsity in Large Pre-Trained Models: The Weights That Matter Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang "Atlas" Wang

MLJ 2023 Troubleshooting Image Segmentation Models with Human-in-the-Loop Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma

NeurIPSW 2023 scCLIP: Multi-Modal Single-Cell Contrastive Learning Integration Pre-Training Lei Xiong, Tianlong Chen, Manolis Kellis

NeurIPS 2022 A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

NeurIPS 2022 Advancing Model Pruning via Bi-Level Optimization Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu

TMLR 2022 Adversarial Feature Augmentation and Normalization for Visual Recognition Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Jingjing Liu, Zhangyang Wang

ICLR 2022 Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang

ICLR 2022 Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable Shaojin Ding, Tianlong Chen, Zhangyang Wang

CVPR 2022 Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations Tianlong Chen, Peihao Wang, Zhiwen Fan, Zhangyang Wang

NeurIPS 2022 Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

AutoML 2022 AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks Duc N.M Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

ICLR 2022 Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen

CVPR 2022 CADTransformer: Panoptic Symbol Spotting Transformer for CAD Drawings Zhiwen Fan, Tianlong Chen, Peihao Wang, Zhangyang Wang

TMLR 2022 Can You Win Everything with a Lottery Ticket? Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang

ICML 2022 Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang

ECCV 2022 DNA: Improving Few-Shot Transfer Learning with Low-Rank Decomposition and Alignment Ziyu Jiang, Tianlong Chen, Xuxi Chen, Yu Cheng, Luowei Zhou, Lu Yuan, Ahmed Awadallah, Zhangyang Wang

ICML 2022 Data-Efficient Double-Win Lottery Tickets from Robust Pre-Training Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang

ICLR 2022 Deep Ensembling with No Overhead for Either Training or Testing: The All-Round Blessings of Dynamic Sparsity Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

NeurIPSW 2022 HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew Ellington, Alex Dimakis, Adam Klivans

ICLR 2022 Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining Miao Lu, Xiaolong Luo, Tianlong Chen, Wuyang Chen, Dong Liu, Zhangyang Wang

JMLR 2022 Learning to Optimize: A Primer and a Benchmark Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin

ICML 2022 Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness Tianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu, Pin-Yu Chen, Zhangyang Wang

NeurIPS 2022 M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-Task Learning with Model-Accelerator Co-Design Hanxue Liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang

ICML 2022 Neural Implicit Dictionary Learning via Mixture-of-Expert Training Peihao Wang, Zhiwen Fan, Tianlong Chen, Zhangyang Wang

NeurIPS 2022 Old Can Be Gold: Better Gradient Flow Can Make Vanilla-GCNs Great Again Ajay Jaiswal, Peihao Wang, Tianlong Chen, Justin Rousseau, Ying Ding, Zhangyang Wang

ICLR 2022 Optimizer Amalgamation Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang

AAAI 2022 Playing Lottery Tickets with Vision and Language Zhe Gan, Yen-Chun Chen, Linjie Li, Tianlong Chen, Yu Cheng, Shuohang Wang, Jingjing Liu, Lijuan Wang, Zicheng Liu

ECCV 2022 Point Cloud Domain Adaptation via Masked Local 3D Structure Prediction Hanxue Liang, Hehe Fan, Zhiwen Fan, Yi Wang, Tianlong Chen, Yu Cheng, Zhangyang Wang

CVPR 2022 Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang

TMLR 2022 Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang

NeurIPS 2022 Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection Without Clean Datasets Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang

WACV 2022 Sandwich Batch Normalization: A Drop-in Replacement for Feature Distribution Heterogeneity Xinyu Gong, Wuyang Chen, Tianlong Chen, Zhangyang Wang

ECCV 2022 Scalable Learning to Optimize: A Learned Optimizer Can Train Big Models Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Chen, Ahmed Awadallah, Zhangyang Wang

NeurIPS 2022 Sparse Winning Tickets Are Data-Efficient Image Recognizers Mukund Varma T, Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

ICLR 2022 Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen, Zhenyu Zhang, Pengjun Wang, Santosh Balachandra, Haoyu Ma, Zehao Wang, Zhangyang Wang

ICLR 2022 Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang

CVPR 2022 The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang

ICLR 2022 The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy

ICML 2022 Training Your Sparse Neural Network Better with Any Mask Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen, Ying Ding, Zhangyang Wang

ICLR 2022 Unified Visual Transformer Compression Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang

ICML 2022 Universality of Winning Tickets: A Renormalization Group Perspective William T Redman, Tianlong Chen, Zhangyang Wang, Akshunna S. Dogra

LoG 2022 You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu

CVPRW 2021 "BNN - BN = ?": Training Binary Neural Networks Without Batch Normalization Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

ICML 2021 A Unified Lottery Ticket Hypothesis for Graph Neural Networks Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang

NeurIPS 2021 Chasing Sparsity in Vision Transformers: An End-to-End Exploration Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang

NeurIPS 2021 Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang

ICML 2021 Efficient Lottery Ticket Finding: Less Data Is More Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang

ICLR 2021 GANs Can Play Lottery Tickets Too Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen

ICML 2021 Graph Contrastive Learning Automated Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang

NeurIPS 2021 Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang

ICLR 2021 Learning a Minimax Optimizer: A Pilot Study Jiayi Shen, Xiaohan Chen, Howard Heaton, Tianlong Chen, Jialin Liu, Wotao Yin, Zhangyang Wang

ICLR 2021 Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang

ICLR 2021 Robust Overfitting May Be Mitigated by Properly Learned Smoothening Tianlong Chen, Zhenyu Zhang, Sijia Liu, Shiyu Chang, Zhangyang Wang

NeurIPS 2021 Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? Xiaolong Ma, Geng Yuan, Xuan Shen, Tianlong Chen, Xuxi Chen, Xiaohan Chen, Ning Liu, Minghai Qin, Sijia Liu, Zhangyang Wang, Yanzhi Wang

ICML 2021 Self-Damaging Contrastive Learning Ziyu Jiang, Tianlong Chen, Bobak J Mortazavi, Zhangyang Wang

NeurIPS 2021 Sparse Training via Boosting Pruning Plasticity with Neuroregeneration Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

ICML 2021 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm Mingkang Zhu, Tianlong Chen, Zhangyang Wang

CVPR 2021 The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang

CVPR 2021 Troubleshooting Blind Image Quality Models in the Wild Zhihua Wang, Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma

ICLR 2021 Undistillable: Making a Nasty Teacher That CANNOT Teach Students Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Chenyu You, Xiaohui Xie, Zhangyang Wang

NeurIPS 2021 You Are Caught Stealing My Winning Lottery Ticket! Making a Lottery Ticket Claim Its Ownership Xuxi Chen, Tianlong Chen, Zhenyu Zhang, Zhangyang Wang

WACV 2020 Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification Ye Yuan, Wuyang Chen, Tianlong Chen, Yang Yang, Zhou Ren, Zhangyang Wang, Gang Hua

CVPRW 2020 Focus Longer to See Better: Recursively Refined Attention for Fine-Grained Image Classification Prateek Shroff, Tianlong Chen, Yunchao Wei, Zhangyang Wang

NeurIPS 2020 Graph Contrastive Learning with Augmentations Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

ECCV 2020 HALO: Hardware-Aware Learning to Optimize Chaojian Li, Tianlong Chen, Haoran You, Zhangyang Wang, Yingyan Lin

ICLR 2020 I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma

NeurIPS 2020 Once-for-All Adversarial Training: In-Situ Tradeoff Between Robustness and Accuracy for Free Haotao Wang, Tianlong Chen, Shupeng Gui, TingKuei Hu, Ji Liu, Zhangyang Wang

NeurIPS 2020 Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang

ICML 2020 Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang

NeurIPS 2020 The Lottery Ticket Hypothesis for Pre-Trained BERT Networks Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin

NeurIPS 2020 Training Stronger Baselines for Learning to Optimize Tianlong Chen, Weiyi Zhang, Zhou Jingyang, Shiyu Chang, Sijia Liu, Lisa Amini, Zhangyang Wang

ICLR 2020 Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference Ting-Kuei Hu, Tianlong Chen, Haotao Wang, Zhangyang Wang

ICML 2020 When Does Self-Supervision Help Graph Convolutional Networks? Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen

ICCVW 2019 Cross-Modal Person Search: A Coarse-to-Fine Framework Using Bi-Directional Text-Image Matching Xiaojing Yu, Tianlong Chen, Yang Yang, Michael Mugo, Zhangyang Wang

NeurIPS 2019 Learning to Optimize in Swarms Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen