About Me

I’m currently a 3rd-year Ph.D. candidate in the Department of Automation at Tsinghua University. Prior to this, I earned my B.Eng. degree from the School of Automation Science and Engineering, Xi’an Jiaotong University in 2023. I worked closely with Shuai Zhang and Zhengqi Wen. I am fortunate to collaborate with Zheng Lian, Haoran Luo, Zhengxi Lu, and Fan Zhang.

My research interests focus on LLM / MLLM reasoning, planning, and agentic reinforcement learning. From 2024 to early 2025, my work mainly focus on high-quality and efficient reasoning for LLMs. My current research investigates post-training techniques for general agents, including agent skills, on-policy distillation (OPD), and reinforcement learning (RL).

🐈 Collaboration: I am looking for motivated collaborators interested in the above topics. If you would like to explore these directions together, feel free to contact me. UG/MSc students are also welcomed! 🌱

🔥 News

📝 Selected Publication（Full List）

* Equal contribution. † Corresponding author.

🤖 Agentic Post Training

ACL 2026

SPARK: Strategic Policy-Aware Exploration via Dynamic Branching for Long-Horizon Agentic Learning

Jinyang Wu, Shuo Yang, Changpeng Yang, Yuhao Shen, Shuai Zhang, Zhengqi Wen, Jianhua Tao

Paper HF – Code BIB

• We propose a policy-aware branching framework that allocates exploration budget to critical decision states, improving sample efficiency for long-horizon agentic RL.

ACL 2026

Atlas: Orchestrating Heterogeneous Models and Tools for Multi-Domain Complex Reasoning

Jinyang Wu, Guocheng Zhai, Ruihan Jin, Jiahao Yuan, Yuhao Shen, Shuai Zhang, Zhengqi Wen, Jianhua Tao

Paper HF – BIB

• We introduce a dual-path framework for dynamic tool usage, combining cluster-based routing with RL-based multi-step routing for cross-domain reasoning.

Preprint

Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles

Jinyang Wu, Guocheng Zhai, Ruihan Jin, Yuhao Shen, Zhengxi Lu, Fan Zhang, Haoran Luo, Zheng Lian, Zhengqi Wen, Jianhua Tao

Paper HF – Code BIB

• We formulate model-skill orchestration as a sequential decision process and train a lightweight policy to compose frozen expert models and skills for multimodal tasks.

Preprint

OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning

Shuo Yang*, Jinyang Wu*,†, Zhengxi Lu, Yuhao Shen, Fan Zhang, Lang Feng, Shuai Zhang, Haoran Luo, Zheng Lian, Zhengqi Wen, Jianhua Tao

Paper HF – Code BIB

• We extract hierarchical skill supervision from completed on-policy trajectories and convert hindsight skill signals into dense token-level advantages for agent training.

Preprint

SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization

Zhengxi Lu, Zhiyuan Yao, Jinyang Wu, Chengcheng Han, Qi Gu, Xunliang Cai, Weiming Lu, Jun Xiao, Yueting Zhuang, Yongliang Shen

Paper HF – Code BIB

• We study skill internalization for agents, gradually withdrawing runtime skill context so the policy can acquire reusable behaviors into its parameters.

• Preprint TACO: Tool-Augmented Credit Optimization for Agentic Tool Use, Mingkuan Feng*, Jinyang Wu*,†, Hao Gu, Fangrui Lv, Ruihan Jin, Chuyuan Zhang, Zhengqi Wen, Jianhua Tao  HF BIB
• Preprint SDAR: Self-Distilled Agentic Reinforcement Learning, Zhengxi Lu, Zhiyuan Yao, Zhuowen Han, Zi-Han Wang, Jinyang Wu, Qi Gu, Xunliang Cai, Weiming Lu, Jun Xiao, Yueting Zhuang, Yongliang Shen  HF Code BIB
• Preprint OdysseyArena: Benchmarking Large Language Models For Long-Horizon, Active and Inductive Interactions, Fangzhi Xu, Hang Yan, Qiushi Sun, Jinyang Wu, Zixian Huang, Muye Huang, Jingyang Gong, Zichen Ding, Kanzhi Cheng, Yian Wang, Xinyu Che, Zeyi Sun, Jian Zhang, Zhangyue Yin, Haoran Luo, Xuanjing Huang, Ben Kao, Jun Liu, Qika Lin  HF Code BIB
• Preprint Orchestra-o1: Omnimodal Agent Orchestration, Fan Zhang, Vireo Zhang, Shengju Qian, Haoxuan Li, Hao Wu, Jinyang Wu, Donghao Zhou, Zhihong Zhu, Zheng Lian, Xin Wang, Pheng-Ann Heng  HF Code BIB
• Preprint RobotEQ: Transitioning from Passive Intelligence to Active Intelligence in Embodied AI, Kuofei Fang, Xinyi Che, Haomin Ouyang, Shufan Zhang, Xuehao Wang, Qi Liu, Liyi Liu, Chenqi Zhang, Wenxi Cai, Wenyu Dai, Jinyang Wu, Fan Zhang, Haoyu Chen, Bin He, Zheng Lian  HF BIB

🧠 LLM Reasoning

ACL 2026

Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models

Jinyang Wu, Mingkuan Feng, Shuai Zhang, Feihu Che, Zhengqi Wen, Chonghua Liao, Ling Yang, Haoran Luo, Zheng Lian, Jianhua Tao

Paper HF – Code BIB

• We shift in-context reasoning from example-level imitation to reusable thought patterns, enabling automated and efficient reasoning guidance.

ACL 2026

TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning

Jinyang Wu, Chonghua Liao, Mingkuan Feng, Shuai Zhang, Zhengqi Wen, Haoran Luo, Ling Yang, Huazhe Xu, Jianhua Tao

Paper HF – BIB

• We augment policy optimization with structured templates, improving high-quality rollout generation and stabilizing RL training for reasoning.

AAAI 2026

AStar: Boosting Multimodal Reasoning with Automated Structured Thinking

Jinyang Wu, Mingkuan Feng, Guocheng Zhai, Shuai Zhang, Zheng Lian, Fangrui Lv, Pengpeng Shao, Ruihan Jin, Zhengqi Wen, Jianhua Tao

Paper HF – BIB AAAI 2026 Oral

• We build a training-free structured thinking method for multimodal reasoning, retrieving reusable thought cards at test time to guide MLLMs.

ACL 2026

Double: Breaking the Acceleration Limit via Double Retrieval Speculative Parallelism

Yuhao Shen, Tianyu Liu, Junyi Shen, Jinyang Wu, Quan Kong, Li Huan, Cong Wang

Paper HF – Code BIB ACL 2026 Oral & Best Paper Candidate

• We bridge speculative decoding and retrieval-based guidance to push inference acceleration beyond conventional parallel speculative decoding limits.

ACL 2025

Pandora’s Box or Aladdin’s Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models

Jinyang Wu, Shuai Zhang, Feihu Che, Mingkuan Feng, Pengpeng Shao, Jianhua Tao

Paper HF – Code BIB

• We define a linguistic taxonomy of RAG noise and build NoiserBench to study when retrieval noise harms or surprisingly helps LLM reasoning.

• ACL 2026 Two-Stage Regularization-Based Structured Pruning for LLMs, Mingkuan Feng*, Jinyang Wu*, Siyuan Liu, Shuai Zhang, Ruihan Jin, Feihu Che, Pengpeng Shao, Zhengqi Wen, Jianhua Tao  Code BIB
• ICLR 2026 Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs, Ruihan Jin, Pengpeng Shao, Zhengqi Wen, Jinyang Wu†, Mingkuan Feng, Shuo Yang, Chu Yuan Zhang, Jianhua Tao  BIB
• ICLR 2026 Attend to the Active: Structure-Aware Dynamic Attention in LLMs for Compositional Instruction Following, Fangrui Lv, Yulei Qin, Ruixin Hong, Liang Jian, Jinyang Wu, Ke Li, Xing Sun, Changshui Zhang  BIB
• AAAI 2026 From Imitation to Discrimination: Toward A Generalized Curriculum Advantage Mechanism Enhancing Cross-Domain Reasoning Tasks, Changpeng Yang*, Jinyang Wu*, Yuchen Liu, Shuai Zhang, Yang Li, Qiliang Liang, Hongzhen Wang, Shuai Nie, Jiaming Xu, Runyu Shi, Ying Huang, Guoquan Zhang  HF BIB
• EMNLP 2025 RadialRouter: Structured Representation for Efficient and Robust Large Language Models Routing, Ruihan Jin, Pengpeng Shao, Zhengqi Wen, Jinyang Wu, Mingkuan Feng, Shuai Zhang, Jianhua Tao  BIB
• Preprint DReSS: Data-driven Regularized Structured Streamlining for Large Language Models, Mingkuan Feng, Jinyang Wu, Shuai Zhang, Pengpeng Shao, Ruihan Jin, Zhengqi Wen, Jianhua Tao, Feihu Che  BIB
• Preprint AffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition, Zheng Lian, Fan Zhang, Lan Chen, Yazhou Zhang, Rui Liu, Jinyang Wu, Haoyu Chen, Xiaobai Li, Xiaojiang Peng, Bin He, Jianhua Tao  BIB

🧬 Biomedical AI

• Briefings in Bioinformatics 2023 KGETCDA: An Efficient Representation Learning Framework Based on Knowledge Graph Encoder from Transformer for Predicting circRNA-Disease Associations, Jinyang Wu, Zhiwei Ning, Yidong Ding, Ying Wang, Qinke Peng, Laiyi Fu
• IEEE JBHI 2023 BertNDA: A Model Based on Graph-BERT and Multi-Scale Information Fusion for ncRNA-Disease Association Prediction, Zhiwei Ning, Jinyang Wu, Yidong Ding, Ying Wang, Qinke Peng, Laiyi Fu

👨‍🏫 Teaching

• Teaching Assistant, Affective Computing, graduate course.
• Teaching Assistant, Intelligent Speech Processing, undergraduate interdisciplinary innovation training course.

🎖 Honors and Awards

• 2026: Outstanding Student Cadre, Tsinghua University.
• 2026: Merit Student, Tsinghua University.
• 2025: Outstanding Teaching Assistant, Tsinghua University.
• 2025: First-Class Scholarship of Tsinghua University.
• 2024: Second-Class Scholarship of Tsinghua University.
• 2023: Outstanding Graduate, Shaanxi Province.
• 2023: Outstanding Graduate, Xi’an Jiaotong University.
• 2022: First Prize, Chinese Mathematics Competitions.
• 2021: National Scholarship, Ministry of Education of China.

📖 Educations

• 2023.09 - now: Ph.D. student in Pattern Recognition and Machine Learning, Tsinghua University.
• 2019.09 - 2023.06: B.Eng. in Automation, Xi’an Jiaotong University.

🧑‍⚖️ Academic Services

Journal Reviewer

• Expert Systems With Applications (ESWA).
• ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM).

Conference Reviewer

• Top-tier ML/AI Conferences: NeurIPS (2025–2026), ICML (2026), ICLR (2026), AAAI (2026–2027).
• Top-tier CV Conferences: CVPR (2026), ECCV (2026).
• Top-tier NLP Conferences: ACL ARR (2026).

💬 Invited Talks

• 2025.12: I gave an invited talk on memory usage, hosted by the Metaverse Technical Committee of the Chinese Association for Artificial Intelligence.
• 2025.05: I gave an invited talk on in-context reasoning at the 7th Beijing Universities Artificial Intelligence Academic Forum.