Posts by Collection

portfolio

publications

Subspace Clustering with Irrelevant Features via Robust Dantzig Selector

Chao Qu, Huan Xu

Conference on Neural Information Processing Systems (NeurIPS), 2015

[Paper]

Fast Rate Analysis of Some Stochastic Optimization Algorithms

Chao Qu, Chongjing Ong, Huan Xu

International Conference on Machine Learning (ICML), 2016

[Paper]

Non-convex Conditional Gradient Sliding

Chao Qu, Yan Li, Huan Xu

International Conference on Machine Learning (ICML), 2018

[Paper]

Nonlinear Distributional Gradient Temporal-Difference Learning

Chao Qu, Shie Mannor, Huan Xu

International Conference on Machine Learning (ICML), 2019

[Paper]

Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning

Chao Qu, Shie Mannor, Huan Xu, Junwu Xiong, Yuan Qi, Le Song

Conference on Neural Information Processing Systems (NeurIPS), 2019

[Paper]

A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud

Siqiao Xue^#, Chao Qu^#, Xiaoming Shi, Cong Liao, Shiyi Zhu, Xiaoyu Tan, Lintao Ma, Shiyu Wang, Shijun Wang, Yun Hu, Lei Lei, Yangfei Zheng, Jianguo Li, James Zhang

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022

[Paper]

Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes

Chao Qu^#, Xiaoyu Tan^#, Siqiao Xue, Xiaoming Shi, James Zhang, Hongyuan Mei

AAAI Conference on Artificial Intelligence (AAAI), 2023

[Paper]

Provably Invariance Learning without Domain Information

Xiaoyu Tan, LIN Yong, Shengyu Zhu, Chao Qu, Xihe Qiu, Xu Yinghui, Peng Cui, Yuan Qi

International Conference on Machine Learning (ICML), 2023

[Paper]

SaFER: A Robust and Efficient Framework for Fine-tuning BERT-based Classifier with Noisy Labels

Zhenting Qi, Xiaoyu Tan, Chao Qu, Yinghui Xu and Yuan Qi

Annual Meeting of the Association for Computational Linguistics (ACL), 2023, Industry Track

[Paper]

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

IEEE/CVF International Conference on Computer Vision (ICCV), 2023

[Paper]

PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching

Zhenting Qi, Xiaoyu Tan, Shaojie Shi, Chao Qu, Yinghui Xu, Yuan Qi

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023, Industry Track

[Paper]

Self-Criticism: Aligning Large Language Models with their Understanding of Helpfulness, Honesty, and Harmlessness

Xiaoyu Tan, Shaojie Shi, Xihe Qiu, Chao Qu, Zhenting Qi, Yinghui Xu, Yuan Qi

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023, Industry Track

[Paper]

Model-Based Off-Policy Deep Reinforcement Learning With Model-Embedding

Xiaoyu Tan^#, Chao Qu^#, Junwu Xiong, James Zhang, Xihe Qiu, Yaochu Jin

IEEE Transactions on Emerging Topics in Computational Intelligence

[Paper]

Hybrid Directional Graph Neural Network for Molecules

Junyi An, Chao Qu^*, Zhipeng Zhou, Fenglei Cao, Yinghui Xu, Yuan Qi, Furao Shen

International Conference on Learning Representations (ICLR), 2024, Spotlight (top 5%)

[Paper]

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

International Conference on Learning Representations (ICLR), 2024

[Paper] [Code]

Subequivariant Reinforcement Learning Framework for Coordinated Motion Control

Haoyu Wang, Xiaoyu Tan, Xihe Qiu^*, Chao Qu^*

IEEE International Conference on Robotics and Automation (ICRA), 2024

[Paper]

INF-34B: INF’s Open-Source Large Language Models

Jiaran Hao, Zili Wang, Siming Huang, Tianhao Cheng, LiuYihan Song, Ansheng You, Zhipeng Zhou, Xiaoyu Tan, Dakuan Lu, Xiaoming Shi, Chao Qu, Haozhe Wang, Yinghui Xu, Wei Chu, Yuan Qi

INF Technology Technical Report, 2024

[Paper] [Code] [Hugging Face]

ILTS: Inducing Intention Propagation in Decentralized Multi-Agent Tasks with Large Language Models

Xihe Qiu, Haoyu Wang, Xiaoyu Tan^*, Chao Qu^*

ACM International Conference on Information and Knowledge Management (CIKM), 2024

[Paper]

ULMR: Unlearning Large Language Models via Negative Response and Model Parameter Average

Shaojie Shi, Xiaoyu Tan, Xihe Qiu, Chao Qu, Kexin Nie, Yuan Cheng, Wei Chu, Xu Yinghui, Yuan Qi

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024, Industry Track

[Paper]

Adaptive Learning on User Segmentation: Universal to Specific Representation via Bipartite Neural Interaction

Xiaoyu Tan^#, Yongxin Deng^#, Chao Qu^#, Siqiao Xue, Xiaoming Shi, James Zhang, Xihe Qiu

International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-AP), 2024

[Paper]

Cognidual Framework: Self-Training Large Language Models within a Dual-System Theoretical Framework for Improving Cognitive Tasks

Yongxin Deng, Xihe Qiu, Xiaoyu Tan, Chao Qu, Jing Pan, Yuan Cheng, Yinghui Xu, Wei Chu

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

[Paper]

Equivariant Masked Position Prediction for Efficient Molecular Representation

Junyi An^#, Chao Qu^#, Yun-Fei Shi, XinHao Liu, Qianwei Tang, Fenglei Cao, Yuan Qi

International Conference on Learning Representations (ICLR), 2025

[Paper] [Code]

Meta-Agent-Workflow: Streamlining Tool Usage in LLMs through Workflow Construction, Retrieval, and Refinement

Xiaoyu Tan, Bin Li, Xihe Qiu, Chao Qu, Wei Chu, Yinghui Xu, Yuan Qi

The Web Conference (WWW), 2025

[Paper] [Code]

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

International Conference on Learning Representations (ICLR), 2025

[Paper]

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

International Conference on Machine Learning (ICML), 2025

[Paper] [Code]

Learning Autonomous Code Integration for Math Language Models

Haozhe Wang^#, Long Li^#, Chao Qu, Fengming Zhu, Weidi Xu, Wei Chu, Fangzhen Lin

Findings of the Association for Computational Linguistics (ACL Findings), 2025

[Paper]

MVP-LLMs: Optimizing Intervention Timing and Subsequent Decision Support for Mechanical Ventilation Parameter Control Using Large Language Models

Teqi Hao, Xiaoyu Tan, Bin Li, Xuemin Wang, Chao Qu, Yinghui Xu, Xihe Qiu

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025

[Paper]

Prolog-Driven Rule-Based Diagnostics with Large Language Models for Precise Clinical Decision Support

Xiaoyu Tan, Bin Li, Weidi Xu, Chao Qu, Wei Chu, Yinghui Xu, Yuan Qi, Xihe Qiu

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025

[Paper]

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

Conference on Neural Information Processing Systems (NeurIPS), 2025

[Paper]

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Haozhe Wang, Chao Qu, Zuming Huang, Wei Chu, Fangzhen Lin, Wenhu Chen

Conference on Neural Information Processing Systems (NeurIPS), 2025, spotlight

[Paper] [Code]

AURORA: Automated Training Framework of Universal Process Reward Models via Ensemble Prompting and Reverse Verification

Xiaoyu Tan^#, Tianchu Yao^#, Chao Qu^#, Bin Li, Minghao Yang, Dakuan Lu, Haozhe Wang, Xihe Qiu^*, Wei Chu, Yinghui Xu, Yuan Qi

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026

[Paper]

Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning

Xuan Zhang, Zhijian Zhou, Weidi Xu, Yanting Miao, Chao Qu^*, Yuan Qi^*

AAAI Conference on Artificial Intelligence (AAAI), 2026

[Paper] [Code]

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^*

International Conference on Learning Representations (ICLR), 2026

[Paper] [Code]

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^*

International Conference on Learning Representations (ICLR), 2026

[Paper] [Code]

Uni-CoT: Towards Unified Chain-of-Thought Reasoning Across Text and Vision

Luozheng Qin, Jia Gong, Yuqing Sun, Tianjiao Li, Mengping Yang, Xiaomeng Yang, Chao Qu, Zhiyu Tan, Hao Li

International Conference on Learning Representations (ICLR), 2026

[Paper] [Code]

Suiren-1.0 Technical Report: A Family of Molecular Foundation Models

Junyi An, Xinyu Lu, Yun-Fei Shi, Li-Cheng Xu, Nannan Zhang, Chao Qu, Yuan Qi, Fenglei Cao

Technical Report, 2026

[Paper] [Code] [Hugging Face]

SQL-ASTRA: Alleviating Sparse Feedback in Agentic SQL via Column-Set Matching and Trajectory Aggregation

Long Li^#, Zhijian Zhou^#, Jiangxuan Long, Peiyang Liu, Weidi Xu, Zhe Wang, Shirui Pan, Chao Qu^*

Findings of the Association for Computational Linguistics (ACL Findings), 2026

[Paper]

DisPPO: Quantile-Based Distributional Reinforcement Learning for Large Language Models

Zhijian Zhou^#, Long Li^#, Xuan Zhang, Zongkai Liu, Yanting Miao, Yuchen Liu, Deshu Chen, Ke Li, Xing Sun, Ruoxi Jiang^*, Xiaoyu Tan^*, Chao Qu^*†, Yuan Qi^*

International Conference on Machine Learning (ICML), 2026

[Paper] [Code]

Nested Spatio-Temporal Time Series Forecasting

YingHao Ai^#, Yukai Zhou^#, Ruoxi Jiang^*, Junyi An, Chao Qu^*, Zhijian Zhou, Shiyu Wang, Fenglei Cao, Zenglin Xu, Furao Shen^*, Yuan Qi^*

International Conference on Machine Learning (ICML), 2026

[Paper]

Start Classifying: Categorical Critics for LLM Reinforcement Learning

Zhijian Zhou^#, Long Li^#, Xuan Zhang, Zongkai Liu, Yulei Qin, Ke Li, Xing Sun, Xiaoyu Tan^*, Chao Qu^*†, Yuan Qi^*

Conference on Language Modeling (COLM), 2026

[Paper] [Code]

Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning

Xuan Zhang, Zhijian Zhou, Lingfeng Qiao, Yulei Qin, Ke Li, Xing Sun, Xiaoyu Tan, Chao Qu^*, Yuan Qi^*

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026

[Paper] [Code]

TRACE-GRPO: Teacher-Refined Advantage Credit Estimation for Long-Horizon Agentic RL

Yuchen Liu, Tianchu Yao, Yinghao Zhang, Xigui Li, Deshu Chen, Zehui Ling, Xin Guo, Yuan Cheng, Lintao Ma, Chao Qu^*, Yuan Qi^*

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026

[Paper] [Code]

DyJR: Preserving Local Policy Plasticity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay

Long Li, Zhijian Zhou, Tianyi Wang, Weidi Xu, Zuming Huang, Wei Chu, Zhe Wang, Shirui Pan, Chao Qu^*, Yuan Qi

Conference on Neural Information Processing Systems (NeurIPS), 2026

Equivariant Spherical Transformer for Efficient Molecular Modeling

Junyi An, Xinyu Lu, Yun-Fei Shi, Peijia Lin, Qianwei Tang, Li-Cheng Xu, Chao Qu^*, Fenglei Cao^*, Yuan Qi^*

Conference on Neural Information Processing Systems (NeurIPS), 2026

[Paper]

Chao Qu

Posts by Collection

portfolio

publications

Subspace Clustering with Irrelevant Features via Robust Dantzig Selector

Fast Rate Analysis of Some Stochastic Optimization Algorithms

Non-convex Conditional Gradient Sliding

Nonlinear Distributional Gradient Temporal-Difference Learning

Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning

A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud

Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes

Provably Invariance Learning without Domain Information

SaFER: A Robust and Efficient Framework for Fine-tuning BERT-based Classifier with Noisy Labels

Gram-based Attentive Neural Ordinary Differential Equations Network for Video Nystagmography Classification

PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching

Self-Criticism: Aligning Large Language Models with their Understanding of Helpfulness, Honesty, and Harmlessness

Model-Based Off-Policy Deep Reinforcement Learning With Model-Embedding

Hybrid Directional Graph Neural Network for Molecules

LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints

Subequivariant Reinforcement Learning Framework for Coordinated Motion Control

INF-34B: INF’s Open-Source Large Language Models

ILTS: Inducing Intention Propagation in Decentralized Multi-Agent Tasks with Large Language Models

ULMR: Unlearning Large Language Models via Negative Response and Model Parameter Average

Adaptive Learning on User Segmentation: Universal to Specific Representation via Bipartite Neural Interaction

Cognidual Framework: Self-Training Large Language Models within a Dual-System Theoretical Framework for Improving Cognitive Tasks

Equivariant Masked Position Prediction for Efficient Molecular Representation

Meta-Agent-Workflow: Streamlining Tool Usage in LLMs through Workflow Construction, Retrieval, and Refinement

Refine Knowledge of Large Language Models via Adaptive Contrastive Learning

One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs

Learning Autonomous Code Integration for Math Language Models

MVP-LLMs: Optimizing Intervention Timing and Subsequent Decision Support for Mechanical Ventilation Parameter Control Using Large Language Models

Prolog-Driven Rule-Based Diagnostics with Large Language Models for Precise Clinical Decision Support

Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

AURORA: Automated Training Framework of Universal Process Reward Models via Ensemble Prompting and Reverse Verification

Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning

The Choice of Divergence: A Neglected Key to Mitigating Diversity Collapse in Reinforcement Learning with Verifiable Reward

Count counts: Motivating Exploration in LLM Reasoning with Count-Based Intrinsic Rewards

Uni-CoT: Towards Unified Chain-of-Thought Reasoning Across Text and Vision

Suiren-1.0 Technical Report: A Family of Molecular Foundation Models

SQL-ASTRA: Alleviating Sparse Feedback in Agentic SQL via Column-Set Matching and Trajectory Aggregation

DisPPO: Quantile-Based Distributional Reinforcement Learning for Large Language Models

Nested Spatio-Temporal Time Series Forecasting

Start Classifying: Categorical Critics for LLM Reinforcement Learning

Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning

TRACE-GRPO: Teacher-Refined Advantage Credit Estimation for Long-Horizon Agentic RL

DyJR: Preserving Local Policy Plasticity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay

Equivariant Spherical Transformer for Efficient Molecular Modeling

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