Publications

You can also find my articles on my Google Scholar profile. # denotes equal contribution; * denotes corresponding author; † denotes project lead.

Tech Report

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]

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]

Conference Papers

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]

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

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]