Lin, Tao

63 publications

NeurIPS 2025 A Unified Approach to Submodular Maximization Under Noise Kshipra Bhawalkar, Yang Cai, Zhe Feng, Christopher Liaw, Tao Lin

ICLRW 2025 AI Systematically Rewires the Flow of Ideas Zhonghao He, Tianyi Qiu, Tao Lin, Moshe Glickman, Atoosa Kasirzadeh, John Wihbey, Max Kleiman-Weiner

CVPR 2025 CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology Yuxuan Sun, Yixuan Si, Chenglu Zhu, Xuan Gong, Kai Zhang, Pingyi Chen, Ye Zhang, Zhongyi Shui, Tao Lin, Lin Yang

NeurIPS 2025 CPathAgent: An Agent-Based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic Yuxuan Sun, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Bowen Ding, Tao Lin, Lin Yang

ICCV 2025 Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing Yongxin Guo, Lin Wang, Xiaoying Tang, Tao Lin

ICLR 2025 CollabEdit: Towards Non-Destructive Collaborative Knowledge Editing Jiamu Zheng, Jinghuai Zhang, Tianyu Du, Xuhong Zhang, Jianwei Yin, Tao Lin

ICLR 2025 DeFT: Decoding with Flash Tree-Attention for Efficient Tree-Structured LLM Inference Jinwei Yao, Kaiqi Chen, Kexun Zhang, Jiaxuan You, Binhang Yuan, Zeke Wang, Tao Lin

ICLR 2025 Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models Yongxin Guo, Zhenglin Cheng, Xiaoying Tang, Zhaopeng Tu, Tao Lin

ICLR 2025 ELICIT: LLM Augmentation via External In-Context Capability Futing Wang, Jianhao Yan, Yue Zhang, Tao Lin

ICLR 2025 Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies Yongxin Guo, Xiaoying Tang, Tao Lin

ICLR 2025 GIFT: Unlocking Full Potential of Labels in Distilled Dataset at Near-Zero Cost Xinyi Shang, Peng Sun, Tao Lin

ICLR 2025 Generalized Principal-Agent Problem with a Learning Agent Tao Lin, Yiling Chen

AAAI 2025 Learn How to Query from Unlabeled Data Streams in Federated Learning Yuchang Sun, Xinran Li, Tao Lin, Jun Zhang

ICLR 2025 PathGen-1.6m: 1.6 Million Pathology Image-Text Pairs Generation Through Multi-Agent Collaboration Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Kai Zhang, Zhongyi Shui, Jingxiong Li, Xuan Gong, Xinheng Lyu, Tao Lin, Lin Yang

ICCV 2025 STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding? Yun Li, Yiming Zhang, Tao Lin, Xiangrui Liu, Wenxiao Cai, Zheng Liu, Bo Zhao

NeurIPS 2024 Bias Detection via Signaling Yiling Chen, Tao Lin, Ariel D. Procaccia, Aaditya Ramdas, Itai Shapira

ICLRW 2024 CollabEdit: Towards Non-Destructive Collaborative Knowledge Editing Jiamu Zheng, Jinghuai Zhang, Futing Wang, Tianyu Du, Tao Lin

NeurIPS 2024 Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging Jiamian Wang, Zongliang Wu, Yulun Zhang, Xin Yuan, Tao Lin, Zhiqiang Tao

ICLRW 2024 DeFT: Flash Tree-Attention with IO-Awareness for Efficient Tree-Search-Based LLM Inference Jinwei Yao, Kexun Zhang, Kaiqi Chen, Jiaxuan You, Zeke Wang, Binhang Yuan, Tao Lin

NeurIPS 2024 Efficiency for Free: Ideal Data Are Transportable Representations Peng Sun, Yi Jiang, Tao Lin

ICML 2024 FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering Yongxin Guo, Xiaoying Tang, Tao Lin

ICLRW 2024 Federated Unlearning: A Perspective of Stability and Fairness Jiaqi Shao, Tao Lin, Xuanyu Cao, Bing Luo

NeurIPSW 2024 Improving Group Connectivity for Generalization of Federated Deep Learning Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Rui Ye, Tao Shen, Tao Lin, Chao Wu

ICLR 2024 Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-Tuning Haobo Song, Hao Zhao, Soumajit Majumder, Tao Lin

ICLR 2024 Learning Thresholds with Latent Values and Censored Feedback Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng

NeurIPSW 2024 Leveraging Large Language Models for Explaining Material Synthesis Mechanisms: The Foundation of Materials Discovery Yingming Pu, Liping Huang, Tao Lin, Hongyu Chen

ICML 2024 Multi-Sender Persuasion: A Computational Perspective Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen, David C. Parkes, Haifeng Xu

CVPR 2024 On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm Peng Sun, Bei Shi, Daiwei Yu, Tao Lin

ECCV 2024 Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors Tao Lin, Lijia Yu, Gaojie Jin, Renjue Li, Peng Wu, Lijun Zhang

ECCV 2024 PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology Yuxuan Sun, Hao Wu, Chenglu Zhu, Sunyi Zheng, Qizi Chen, Kai Zhang, Yunlong Zhang, Dan Wan, Xiaoxiao Lan, Mengyue Zheng, Jingxiong Li, Xinheng Lyu, Tao Lin, Lin Yang

ICLR 2024 Towards Robust Multi-Modal Reasoning via Model Selection Xiangyan Liu, Rongxue Li, Wei Ji, Tao Lin

NeurIPS 2024 User-Creator Feature Polarization in Recommender Systems with Dual Influence Tao Lin, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen, Yang Liu

NeurIPS 2023 DELTA: Diverse Client Sampling for Fasting Federated Learning Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang

ICML 2023 FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction Yongxin Guo, Xiaoying Tang, Tao Lin

AAAI 2023 From Monopoly to Competition: Optimal Contests Prevail Xiaotie Deng, Yotam Gafni, Ron Lavi, Tao Lin, Hongyi Ling

ICCV 2023 No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu

ICML 2023 On Pitfalls of Test-Time Adaptation Hao Zhao, Yuejiang Liu, Alexandre Alahi, Tao Lin

ICLRW 2023 On Pitfalls of Test-Time Adaptation Hao Zhao, Yuejiang Liu, Alexandre Alahi, Tao Lin

ICML 2023 Online Restless Bandits with Unobserved States Bowen Jiang, Bo Jiang, Jian Li, Tao Lin, Xinbing Wang, Chenghu Zhou

IJCAI 2023 Prediction with Incomplete Data Under Agnostic Mask Distribution Shift Yichen Zhu, Jian Yuan, Bo Jiang, Tao Lin, Haiming Jin, Xinbing Wang, Chenghu Zhou

ICML 2023 Revisiting Weighted Aggregation in Federated Learning with Neural Networks Zexi Li, Tao Lin, Xinyi Shang, Chao Wu

NeurIPS 2023 Sample Complexity of Forecast Aggregation Tao Lin, Yiling Chen

ICLR 2023 Test-Time Robust Personalization for Federated Learning Liangze Jiang, Tao Lin

NeurIPS 2022 Adversarial Training for High-Stakes Reliability Daniel Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Benjamin Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas

NeurIPSW 2022 Decentralized Stochastic Optimization with Client Sampling Ziwei Liu, Anastasia Koloskova, Martin Jaggi, Tao Lin

AAAI 2022 How Many Representatives Do We Need? the Optimal Size of a Congress Voting on Binary Issues Manon Revel, Tao Lin, Daniel Halpern

NeurIPS 2021 An Improved Analysis of Gradient Tracking for Decentralized Machine Learning Anastasiia Koloskova, Tao Lin, Sebastian U Stich

ICML 2021 Consensus Control for Decentralized Deep Learning Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich

ICML 2021 Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data Tao Lin, Sai Praneeth Karimireddy, Sebastian Stich, Martin Jaggi

NeurIPS 2021 RelaySum for Decentralized Deep Learning on Heterogeneous Data Thijs Vogels, Lie He, Anastasiia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U Stich, Martin Jaggi

ICCVW 2021 The Multi-Modal Video Reasoning and Analyzing Competition Haoran Peng, He Huang, Li Xu, Tianjiao Li, Jun Liu, Hossein Rahmani, Qiuhong Ke, Zhicheng Guo, Cong Wu, Rongchang Li, Mang Ye, Jiahao Wang, Jiaxu Zhang, Yuanzhong Liu, Tao He, Fuwei Zhang, Xianbin Liu, Tao Lin

NeurIPS 2020 A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling Xiaotie Deng, Ron Lavi, Tao Lin, Qi Qi, Wenwei Wang, Xiang Yan

ICLR 2020 Decentralized Deep Learning with Arbitrary Communication Compression Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi

ICLR 2020 Don't Use Large Mini-Batches, Use Local SGD Tao Lin, Sebastian U. Stich, Kumar Kshitij Patel, Martin Jaggi

ICLR 2020 Dynamic Model Pruning with Feedback Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi

NeurIPS 2020 Ensemble Distillation for Robust Model Fusion in Federated Learning Tao Lin, Lingjing Kong, Sebastian U Stich, Martin Jaggi

ICML 2020 Extrapolation for Large-Batch Training in Deep Learning Tao Lin, Lingjing Kong, Sebastian Stich, Martin Jaggi

CVPRW 2020 Generalized Class Incremental Learning Fei Mi, Lingjing Kong, Tao Lin, Kaicheng Yu, Boi Faltings

NeurIPS 2020 Learning Utilities and Equilibria in Non-Truthful Auctions Hu Fu, Tao Lin

NeurIPS 2020 On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk

ICML 2019 Exploring Interpretable LSTM Neural Networks over Multi-Variable Data Tian Guo, Tao Lin, Nino Antulov-Fantulin

NeurIPS 2018 Training DNNs with Hybrid Block Floating Point Mario Drumond, Tao Lin, Martin Jaggi, Babak Falsafi

IJCAI 2017 Hybrid Neural Networks for Learning the Trend in Time Series Tao Lin, Tian Guo, Karl Aberer