Chen, Feng

87 publications

NeurIPS 2025 ACT as Human: Multimodal Large Language Model Data Annotation with Critical Thinking Lequan Lin, Dai Shi, Andi Han, Feng Chen, Qiuzheng Chen, Jiawen Li, Zhaoyang Li, Jiyuan Zhang, Zhenbang Sun, Junbin Gao

NeurIPS 2025 Adaptive Fission: Post-Training Encoding for Low-Latency Spike Neural Networks Yizhou Jiang, Feng Chen, Yihan Li, Yuqian Liu, Haichuan Gao, Tianren Zhang, Ying Fang

NeurIPS 2025 Alternating Gradient Flows: A Theory of Feature Learning in Two-Layer Neural Networks Daniel Kunin, Giovanni Luca Marchetti, Feng Chen, Dhruva Karkada, James B Simon, Michael R DeWeese, Surya Ganguli, Nina Miolane

TMLR 2025 Efficient Multi-Agent Cooperation Learning Through Teammate Lookahead Feng Chen, Xinwei Chen, Rong-Jun Qin, Cong Guan, Lei Yuan, Zongzhang Zhang, Yang Yu

NeurIPS 2025 EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving Shihan Dou, Ming Zhang, Chenhao Huang, Jiayi Chen, Feng Chen, Shichun Liu, Yan Liu, Chenxiao Liu, Cheng Zhong, Zongzhang Zhang, Tao Gui, Chao Xin, Wei Chengzhi, Lin Yan, Qi Zhang, Xuanjing Huang

AISTATS 2025 Evidential Uncertainty Probes for Graph Neural Networks Linlin Yu, Kangshuo Li, Pritom Kumar Saha, Yifei Lou, Feng Chen

WACV 2025 GMT: Guided Mask Transformer for Leaf Instance Segmentation Feng Chen, Sotirios A. Tsaftaris, Mario Valerio Giuffrida

AAAI 2025 GRICP: Granular-Ball Iterative Closest Point with Multikernel Correntropy for Point Cloud Fine Registration Yihao, Limei Hu, Feng Chen, Sen Zhao, Shukai Duan

CoRL 2025 HyperTASR: Hypernetwork-Driven Task-Aware Scene Representations for Robust Manipulation Li Sun, Jiefeng Wu, Feng Chen, Ruizhe Liu, Yanchao Yang

NeurIPS 2025 Informed Correctors for Discrete Diffusion Models Yixiu Zhao, Jiaxin Shi, Feng Chen, Shaul Druckmann, Lester Mackey, Scott Linderman

ICML 2025 Learning to Reuse Policies in State Evolvable Environments Ziqian Zhang, Bohan Yang, Lihe Li, Yuqi Bian, Ruiqi Xue, Feng Chen, Yi-Chen Li, Lei Yuan, Yang Yu

ICCV 2025 Neighboring Autoregressive Modeling for Efficient Visual Generation Yefei He, Yuanyu He, Shaoxuan He, Feng Chen, Hong Zhou, Kaipeng Zhang, Bohan Zhuang

ICCV 2025 OURO: A Self-Bootstrapped Framework for Enhancing Multimodal Scene Understanding Tianrun Xu, Guanyu Chen, Ye Li, Yuxin Xi, Zeyu Mu, Ruichen Wang, Tianren Zhang, Haichuan Gao, Feng Chen

ICLR 2025 Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function Linlin Yu, Bowen Yang, Tianhao Wang, Kangshuo Li, Feng Chen

NeurIPS 2025 Rethinking Fine-Tuning When Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning Feng Chen, Allan Raventos, Nan Cheng, Surya Ganguli, Shaul Druckmann

ICLRW 2025 Rethinking Fine-Tuning When Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning Feng Chen, Allan Raventos, Nan Cheng, Surya Ganguli, Shaul Druckmann

NeurIPS 2025 SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search Dong Li, Xujiang Zhao, Linlin Yu, Yanchi Liu, Wei Cheng, Zhengzhang Chen, Zhong Chen, Feng Chen, Chen Zhao, Haifeng Chen

CVPR 2025 Training-Free Dense-Aligned Diffusion Guidance for Modular Conditional Image Synthesis Zixuan Wang, Duo Peng, Feng Chen, Yuwei Yang, Yinjie Lei

ICML 2025 When Do Neural Networks Learn World Models? Tianren Zhang, Guanyu Chen, Feng Chen

ICLRW 2025 When Do Neural Networks Learn World Models? Tianren Zhang, Guanyu Chen, Feng Chen

ICML 2025 ZipAR: Parallel Autoregressive Image Generation Through Spatial Locality Yefei He, Feng Chen, Yuanyu He, Shaoxuan He, Hong Zhou, Kaipeng Zhang, Bohan Zhuang

ICCV 2025 ZipVL: Accelerating Vision-Language Models Through Dynamic Token Sparsity Yefei He, Feng Chen, Jing Liu, Wenqi Shao, Hong Zhou, Kaipeng Zhang, Bohan Zhuang

NeurIPSW 2024 Catching the Spikes: Heteroscedastic Uncertainty Quantification for Enhanced Malaria Prediction Feng Chen, Qi Qi, Jiayu Qiu, Kemeng Zhang, Xiang Li

NeurIPSW 2024 Catching the Spikes: Heteroscedastic Uncertainty Quantification for Enhanced Malaria Prediction Feng Chen, Qi Qi, Jiayu Qiu, Kemeng Zhang, Xiang Li

ECML-PKDD 2024 Dynamics Adaptive Safe Reinforcement Learning with a Misspecified Simulator Ruiqi Xue, Ziqian Zhang, Lihe Li, Feng Chen, Yi-Chen Li, Yang Yu, Lei Yuan

ICLRW 2024 Efficient Human-AI Coordination via Preparatory Language-Based Convention Cong Guan, Lichao Zhang, Chunpeng Fan, Yi-Chen Li, Feng Chen, Lihe Li, Yunjia Tian, Lei Yuan, Yang Yu

ICML 2024 Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize Tianren Zhang, Chujie Zhao, Guanyu Chen, Yizhou Jiang, Feng Chen

TMLR 2024 From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen

NeurIPS 2024 Get Rich Quick: Exact Solutions Reveal How Unbalanced Initializations Promote Rapid Feature Learning Daniel Kunin, Allan Raventós, Clémentine Dominé, Feng Chen, David Klindt, Andrew Saxe, Surya Ganguli

ICMLW 2024 Get Rich Quick: Exact Solutions Reveal How Unbalanced Initializations Promote Rapid Feature Learning Daniel Kunin, Allan Raventos, Clémentine Carla Juliette Dominé, Feng Chen, David Klindt, Andrew M Saxe, Surya Ganguli

ICLR 2024 Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty Changbin Li, Kangshuo Li, Yuzhe Ou, Lance M. Kaplan, Audun Jøsang, Jin-Hee Cho, Dong Hyun Jeong, Feng Chen

IJCAI 2024 Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu

TMLR 2024 M$^3$PL: Identifying and Exploiting View Bias of Prompt Learning Chujie Zhao, Tianren Zhang, Guanyu Chen, Yizhou Jiang, Feng Chen

TMLR 2024 One by One, Continual Coordinating with Humans via Hyper-Teammate Identification Cong Guan, Feng Chen, Ke Xue, Chunpeng Fan, Lichao Zhang, Ziqian Zhang, Pengyao Zhao, Zongzhang Zhang, Chao Qian, Lei Yuan, Yang Yu

ICML 2024 RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation Yufei Wang, Zhou Xian, Feng Chen, Tsun-Hsuan Wang, Yian Wang, Katerina Fragkiadaki, Zackory Erickson, David Held, Chuang Gan

ICLR 2024 Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers Yizhou Jiang, Kunlin Hu, Tianren Zhang, Haichuan Gao, Yuqian Liu, Ying Fang, Feng Chen

ICLR 2024 Uncertainty-Aware Graph-Based Hyperspectral Image Classification Linlin Yu, Yifei Lou, Feng Chen

ICCVW 2023 Adapting Vision Foundation Models for Plant Phenotyping Feng Chen, Mario Valerio Giuffrida, Sotirios A. Tsaftaris

NeurIPS 2023 DiffVL: Scaling up Soft Body Manipulation Using Vision-Language Driven Differentiable Physics Zhiao Huang, Feng Chen, Yewen Pu, Chunru Lin, Hao Su, Chuang Gan

NeurIPSW 2023 Enhancing Robustness of Foundation Model Representations Under Provenance-Related Distribution Shifts Xiruo Ding, Zhecheng Sheng, Brian Hur, Feng Chen, Serguei V. S. Pakhomov, Trevor Cohen

AAAI 2023 Fast Counterfactual Inference for History-Based Reinforcement Learning Haichuan Gao, Tianren Zhang, Zhile Yang, Yuqing Guo, Jinsheng Ren, Shangqi Guo, Feng Chen

NeurIPS 2023 Improvements on Uncertainty Quantification for Node Classification via Distance Based Regularization Russell Hart, Linlin Yu, Yifei Lou, Feng Chen

NeurIPSW 2023 Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu

CVPRW 2023 Multi-Object Tracking by Self-Supervised Learning Appearance Model Kaer Huang, Kanokphan Lertniphonphan, Feng Chen, Jian Li, Zhepeng Wang

NeurIPS 2023 Pretraining Task Diversity and the Emergence of Non-Bayesian In-Context Learning for Regression Allan Raventós, Mansheej Paul, Feng Chen, Surya Ganguli

ACML 2023 Prototypical Model with Information-Theoretic Loss Functions for Generalized Zero-Shot Learning Chunlin Ji, Zhan Xiong, Meiying Zhang, Huiwen Yang, Feng Chen, Hanchun Shen

AAAI 2023 Robust Multi-Agent Coordination via Evolutionary Generation of Auxiliary Adversarial Attackers Lei Yuan, Ziqian Zhang, Ke Xue, Hao Yin, Feng Chen, Cong Guan, Lihe Li, Chao Qian, Yang Yu

NeurIPS 2023 Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks Feng Chen, Daniel Kunin, Atsushi Yamamura, Surya Ganguli

ICLRW 2023 The Effects of Pretraining Task Diversity on In-Context Learning of Ridge Regression Allan Raventos, Mansheej Paul, Feng Chen, Surya Ganguli

AAAI 2023 Towards Deployment-Efficient and Collision-Free Multi-Agent Path Finding (Student Abstract) Feng Chen, Chenghe Wang, Fuxiang Zhang, Hao Ding, Qiaoyong Zhong, Shiliang Pu, Zongzhang Zhang

ICCV 2023 Uncertainty-Guided Learning for Improving Image Manipulation Detection Kaixiang Ji, Feng Chen, Xin Guo, Yadong Xu, Jian Wang, Jingdong Chen

ICLR 2023 Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite

AAAI 2022 A Nested Bi-Level Optimization Framework for Robust Few Shot Learning KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K. Iyer

AAAI 2022 Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs Chunpai Wang, Daniel B. Neill, Feng Chen

NeurIPS 2022 Efficient Multi-Agent Communication via Self-Supervised Information Aggregation Cong Guan, Feng Chen, Lei Yuan, Chenghe Wang, Hao Yin, Zongzhang Zhang, Yang Yu

CVPR 2022 Interacting Attention Graph for Single Image Two-Hand Reconstruction Mengcheng Li, Liang An, Hongwen Zhang, Lianpeng Wu, Feng Chen, Tao Yu, Yebin Liu

CoRL 2022 Iterative Interactive Modeling for Knotting Plastic Bags Chongkai Gao, Zekun Li, Haichuan Gao, Feng Chen

NeurIPS 2022 Learning to Branch with Tree MDPs Lara Scavuzzo, Feng Chen, Didier Chetelat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen Aardal

IJCAI 2022 Multi-Agent Concentrative Coordination with Decentralized Task Representation Lei Yuan, Chenghe Wang, Jianhao Wang, Fuxiang Zhang, Feng Chen, Cong Guan, Zongzhang Zhang, Chongjie Zhang, Yang Yu

NeurIPSW 2022 Multi-Agent Policy Transfer via Task Relationship Modeling Rong-Jun Qin, Feng Chen, Tonghan Wang, Lei Yuan, Xiaoran Wu, Yipeng Kang, Zongzhang Zhang, Chongjie Zhang, Yang Yu

ICML 2022 PLATINUM: Semi-Supervised Model Agnostic Meta-Learning Using Submodular Mutual Information Changbin Li, Suraj Kothawade, Feng Chen, Rishabh Iyer

ICLRW 2022 Subjective Learning for Conflicting Data Tianren Zhang, Yizhou Jiang, Xin Su, Shangqi Guo, Chongkai Gao, Feng Chen

CoRL 2022 Transferring Hierarchical Structures with Dual Meta Imitation Learning Chongkai Gao, Yizhou Jiang, Feng Chen

NeurIPSW 2022 Unmasking the Lottery Ticket Hypothesis: Efficient Adaptive Pruning for Finding Winning Tickets Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite

AISTATS 2021 Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu

AAAI 2021 A Double Phases Generation Network for Yes or No Question Generation (Student Abstract) Jiayuan Xie, Feng Chen, Yi Cai, Zehang Lin

NeurIPSW 2021 A Nested Bi-Level Optimization Framework for Robust Few Shot Learning Krishnateja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K Iyer

ICCVW 2021 Learning to Localise and Count with Incomplete Dot-Annotations Feng Chen, Michael P. Pound, Andrew P. French

ACML 2021 Local Aggressive Adversarial Attacks on 3D Point Cloud Yiming Sun, Feng Chen, Zhiyu Chen, Mingjie Wang

AAAI 2021 Multidimensional Uncertainty-Aware Evidential Neural Networks Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen

NeurIPS 2021 RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh Iyer

NeurIPS 2020 Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning Tianren Zhang, Shangqi Guo, Tian Tan, Xiaolin Hu, Feng Chen

NeurIPS 2020 Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu

ICML 2020 Task Understanding from Confusing Multi-Task Data Xin Su, Yizhou Jiang, Shangqi Guo, Feng Chen

NeurIPS 2020 Uncertainty Aware Semi-Supervised Learning on Graph Data Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho

NeurIPS 2019 Convolution with Even-Sized Kernels and Symmetric Padding Shuang Wu, Guanrui Wang, Pei Tang, Feng Chen, Luping Shi

ICML 2019 Stochastic Iterative Hard Thresholding for Graph-Structured Sparsity Optimization Baojian Zhou, Feng Chen, Yiming Ying

AAAI 2019 Uncovering Specific-Shape Graph Anomalies in Attributed Graphs Nannan Wu, Wenjun Wang, Feng Chen, Jianxin Li, Bo Li, Jinpeng Huai

ICLR 2018 Training and Inference with Integers in Deep Neural Networks Shuang Wu, Guoqi Li, Feng Chen, Luping Shi

IJCAI 2017 Query-Driven Discovery of Anomalous Subgraphs in Attributed Graphs Nannan Wu, Feng Chen, Jianxin Li, Jinpeng Huai, Bo Li

IJCAI 2016 A Generalized Matching Pursuit Approach for Graph-Structured Sparsity Feng Chen, Baojian Zhou

AAAI 2016 Efficient Nonparametric Subgraph Detection Using Tree Shaped Priors Nannan Wu, Feng Chen, Jianxin Li, Baojian Zhou, Naren Ramakrishnan

AAAI 2016 Topical Analysis of Interactions Between News and Social Media Ting Hua, Yue Ning, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan

AAAI 2013 A Generalized Student-T Based Approach to Mixed-Type Anomaly Detection Yen-Cheng Lu, Feng Chen, Yang Chen, Chang-Tien Lu

NeurIPS 2013 Variational Planning for Graph-Based MDPs Qiang Cheng, Qiang Liu, Feng Chen, Alex Ihler

AAAI 2012 Approximating the Sum Operation for Marginal-MAP Inference Qiang Cheng, Feng Chen, Jianwu Dong, Wenli Xu, Alexander Ihler

WACV 2012 Online Discriminative Object Tracking with Local Sparse Representation Qing Wang, Feng Chen, Wenli Xu, Ming-Hsuan Yang