Qu, Chao

20 publications

ICLR 2026 Count Counts: Motivating Exploration in LLM Reasoning with Count-Based Intrinsic Rewards Xuan Zhang, Ruixiao Li, Zhijian Zhou, Long Li, Yulei Qin, Ke Li, Xing Sun, Xiaoyu Tan, Chao Qu, Yuan Qi

ICLR 2026 The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward Long Li, Zhijian Zhou, Jiaran Hao, Jason Klein Liu, Yanting Miao, Wei Pang, Xiaoyu Tan, Wei Chu, Zhe Wang, Shirui Pan, Chao Qu, Yuan Qi

ICLR 2026 Uni-CoT: Towards Unified Chain-of-Thought Reasoning Across Text and Vision Luozheng Qin, Gong Jia, Yuqing Sun, Tianjiao Li, Haoyu Pan, Mengping Yang, Xiaomeng Yang, Chao Qu, Zhiyu Tan, Hao Li

NeurIPS 2025 Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities Jiayi Kuang, Haojing Huang, Yinghui Li, Xinnian Liang, Zhikun Xu, Yangning Li, Xiaoyu Tan, Chao Qu, Meishan Zhang, Ying Shen, Philip S. Yu

ICLR 2025 Equivariant Masked Position Prediction for Efficient Molecular Representation Junyi An, Chao Qu, Yun-Fei Shi, XinHao Liu, Qianwei Tang, Fenglei Cao, Yuan Qi

ICML 2025 One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs Yinghui Li, Jiayi Kuang, Haojing Huang, Zhikun Xu, Xinnian Liang, Yi Yu, Wenlian Lu, Yangning Li, Xiaoyu Tan, Chao Qu, Ying Shen, Hai-Tao Zheng, Philip S. Yu

ICLR 2025 Refine Knowledge of Large Language Models via Adaptive Contrastive Learning Yinghui Li, Haojing Huang, Jiayi Kuang, Yangning Li, Shu-Yu Guo, Chao Qu, Xiaoyu Tan, Hai-Tao Zheng, Ying Shen, Philip S. Yu

NeurIPS 2025 VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning Haozhe Wang, Chao Qu, Zuming Huang, Wei Chu, Fangzhen Lin, Wenhu Chen

ICLR 2024 Hybrid Directional Graph Neural Network for Molecules Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Xu Yinghui, Yuan Qi, Furao Shen

ICLR 2024 LogicMP: A Neuro-Symbolic Approach for Encoding First-Order Logic Constraints Weidi Xu, Jingwei Wang, Lele Xie, Jianshan He, Hongting Zhou, Taifeng Wang, Xiaopei Wan, Jingdong Chen, Chao Qu, Wei Chu

AAAI 2023 Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes Chao Qu, Xiaoyu Tan, Siqiao Xue, Xiaoming Shi, James Zhang, Hongyuan Mei

ICCV 2023 Gram-Based Attentive Neural Ordinary Differential Equations Network for Video Nystagmography Classification Xihe Qiu, Shaojie Shi, Xiaoyu Tan, Chao Qu, Zhijun Fang, Hailing Wang, Yongbin Gao, Peixia Wu, Huawei Li

ICML 2023 Provably Invariant Learning Without Domain Information Xiaoyu Tan, Lin Yong, Shengyu Zhu, Chao Qu, Xihe Qiu, Xu Yinghui, Peng Cui, Yuan Qi

ICCV 2021 Bayesian Deep Basis Fitting for Depth Completion with Uncertainty Chao Qu, Wenxin Liu, Camillo J. Taylor

WACV 2020 Depth Completion via Deep Basis Fitting Chao Qu, Ty Nguyen, Camillo Taylor

ICML 2019 Nonlinear Distributional Gradient Temporal-Difference Learning Chao Qu, Shie Mannor, Huan Xu

NeurIPS 2019 Value Propagation for Decentralized Networked Deep Multi-Agent Reinforcement Learning Chao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong

ICML 2018 Non-Convex Conditional Gradient Sliding Chao Qu, Yan Li, Huan Xu

ICML 2016 Fast Rate Analysis of Some Stochastic Optimization Algorithms Chao Qu, Huan Xu, Chong Ong

NeurIPS 2015 Subspace Clustering with Irrelevant Features via Robust Dantzig Selector Chao Qu, Huan Xu