About Me

I work at ByteDance Seed, as a senior research scientist and a member of TopSeed program. I am working on advancing the reasoning and agentic capabilities of Large Language Models (LLMs) and general Agent foundation models. As one of the algorithm leads for general agent optimization, I contribute to the ByteDance Seed model series (e.g., Seed 2.1 to Seed 1.5) and Doubao products, including building the Agent Task Mode/Expert Mode (豆包办公任务模式和专家模式). We are hiring research interns and looking for academic cooperation, please feel free to email me at wanjun@bytedance.com

Prior to that, I worked at Huawei Noah’s Ark Lab as a research scientist and a member of Huawei TopMind program. I received my Ph.D. degree from the School of Computer Science and Engineering in Sun Yat-sen University (SYSU), as a member of joint Ph.D. program between SYSU and Microsoft Research Asia (MSRA).

As a joint Ph.D. student, I was advised by Dr. Ming Zhou, Prof. Jian Yin and Prof. Jiahai Wang. I was a research intern in the Natural Language Computing Group of MSRA, and was mentored by Dr. Nan Duan

I won the Microsoft Research Fellowship Award (11 outstanding Ph.D. in Asia-Pacific area each year) in 2021, and is selected as a member of Huawei TopMind program in 2023.

I published over 50+ papers in top-tier AI conferences and journals, including NeurIPS, ICLR, ACL, EMNLP, TASLP, NAACL, AAAI, IJCAI, ISSTA, etc.

My Research Interests

• Large Language Model
• Agent Foundation Model and Reinforcement Learning
• Reasoning towards AGI

🔥 News

• 2026.06 Release Seed 2.1 series, a next-generation agent foundation model for real-world productivity. Grateful to contribute to the general agent optimization as one of the algorithm core contributors.
• 2026.06 Released the Office Task Mode of 豆包专业版 (Doubao Pro), where I was fortunate to contribute as one of the algorithm leads.
• 2026.04 Released Agent-World (paper), exploring scalable real-world environment synthesis for evolving general agent intelligence. Check out our demo!
• 2026.02 Release Seed 2.0 as a core contributor, the leading Agent foundation models!
• 2026.02 Release 豆包专家模式 (Doubao Expert Mode) — long-CoT reasoning that delivers expert-level answers to complex professional problems — and 豆包超能模式
• 2025.12 Release Seed 1.8 as a core contributor.
• 2025.09 Release UI-TARS-2, a multi-modal unified agent models capable of coding, tool using and GUI operation, achieving leading performance.
• 2025.04: 🎉 Joined ByteDance Seed Edge team as Senior Research Scientist focusing on Large Language Models and Agent foundation models!
• 2025.04 Released ReTool: A reinforcement learning-based multi-turn tool-use agent training framework!
• 2025.04: 🎉 Seed-VL-v1.5 technical report released, advancing multi-modal models with great understanding and reasoning capabilities!
• 2025.04: 🎉 Seed-Thinking-v1.5 technical report released, advancing superb reasoning models with reinforcement learning
• 2025.01: 🎉 Released UI-TARS: Industry’s open-source GUI+Game Agent foundation model with 6.2K+ GitHub stars!
• 2024.06: 🎉 Joined ByteDance TopSeed program as a Senior Research Scientist!

📖 Education

• 2018.09 - 2023.06, Ph.D. in Computer Science and Technology, Sun Yat-sen University (SYSU), Joint Ph.D. program with Microsoft Research Asia (MSRA)
• 2014.09 - 2018.06, Bachelor in Software Engineering, School of Data Science and Computer Science, Sun Yat-sen University (SYSU)

💼 Work Experience

• 2024.06 - Present,ByteDance Seed Edge Team - Senior Research Scientist
  • Role: Senior Research Scientist in LLMs and Agents, member of TopSeed program, one of the algorithm leads for general agent optimization
  • Project Experience:
    • Seed 1.8 & Seed 2.0 & Seed 2.1 (Leading next-generation Agent foundation models, core contributor)
    • Office Task Mode of 豆包专业版 (Doubao Pro) — as one of the algorithm leads
    • Doubao Expert Mode (long-CoT reasoning that delivers expert-level answers to complex professional problems, improving quality in STEM, coding, domain expertise and creative writing) & Super Mode (豆包专家模式 & 豆包超能模式)
    • Agent-World (scalable real-world environment synthesis for evolving general agent intelligence)
    • Seed-Thinking long chain-of-thought reasoning model
    • Seed-Agent foundation model:
      • UI-TARS & UI-TARS-2 (Industry-leading open-source GUI+Game Agent foundation models) training
      • ReTool (Agent multi-turn tool calling reinforcement learning training framework)
      • MCP-enhanced general Agent foundation model training
• 2023.06 - 2024.06, Huawei Noah’s Ark Lab - Speech & Semantic Lab - Research Scientist (TopMind Program)
  • Project Experience: Research scientist in Large Language Models, specializing in PanGu foundation model instruction tuning, data flywheel, Agent super-alignment and complex reasoning research and implementation.
• 2018.06 - 2023.06, Microsoft Research Asia - Joint Ph.D. Program Long-term Internship
  • Mentor: Dr. Nan Duan and Dr. Ming Zhou

💬 Academic Supervision

• Ph.D. Advisors: Dr. Ming Zhou (Microsoft Research Asia), Prof. Jian Yin (SYSU), Prof. Jiahai Wang (SYSU)
• Mentor at MSRA: Dr. Nan Duan (Natural Language Computing Group)

🔬 Research Internship

• 2018.06 - 2023.06, Research Intern, Natural Language Computing Group, Microsoft Research Asia (MSRA), Beijing
  • Long-term internship as part of joint Ph.D. program
  • Mentor: Dr. Nan Duan

🎖 Honors and Awards

• 2024 ByteDance TopSeed Program
• 2023 ACM Outstanding Doctoral Thesis Award (China-Guangzhou Chapter)
• 2023 Huawei TopMind Program
• 2021 Microsoft Research Fellowship Award (11 outstanding Ph.D. students in computer science in the Asia-Pacific region each year)
• 2021 Baidu Scholarship (Global Top 40)
• 2020 National Scholarship for Doctoral Students (Top 0.2%)
• 2016 First Prize Scholarship

🏆 Competition Awards

• 2023 1st Place - CVPR 2023 Ego4D Challenge for Episodic Memory Natural Language Queries
• 2022 3rd Place - ECCV 2022 Ego4D Challenge for Episodic Memory Natural Language Queries
• 2018 Outstanding Award - Global (Nanjing) AI Application Competition
• 2016 National Second Prize - National Mathematical Contest in Modeling
• 2018 3rd & 7th Place - FASHIONAI Global Challenge (Semi-finals)

📝 Publications

Works in Seed

• Seed Technical Report Seed2.1: A Next-Generation Agent Foundation Model for Real-World Productivity
• arXiv 2026 Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence, Guanting Dong, Jianqiao Lu, Junjie Huang, Wanjun Zhong, Liang Liu, Shijue Huang, Zhenghao Li, Yang Zhao, Xiao Song, et al.
• Seed Technical Report Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity
• Seed Technical Report Seed1.8 Model Card: Towards Generalized Real-World Agency
• Seed Technical Report UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
• Seed Technical Report Seed1.5-VL Technical Report
• Seed Technical Report Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning
• Seed Technical Report UI-TARS: Pioneering Automated GUI Interaction with Native Agents
• Sub. to NeurIPS 2025 Retool: Reinforcement learning for strategic tool use in llms, Jiazhan Feng, Shijue Huang, Xingwei Qu, Ge Zhang, Yujia Qin, Baoquan Zhong, Chengquan Jiang, Jinxin Chi, Wanjun Zhong
• Arxiv Autokaggle: A multi-agent framework for autonomous data science competitions, Ziming Li, Qianbo Zang, David Ma, Jiawei Guo, Tuney Zheng, Minghao Liu, Xinyao Niu, Yue Wang, Jian Yang, Jiaheng Liu, Wanjun Zhong, Wangchunshu Zhou, Wenhao Huang, Ge Zhang
• EMNLP 2025 Otc: Optimal tool calls via reinforcement learning, Hongru Wang, Cheng Qian, Wanjun Zhong, Xiusi Chen, Jiahao Qiu, Shijue Huang, Bowen Jin, Mengdi Wang, Kam-Fai Wong, Heng Ji

Large Language Model Reasoning

• Seed Technical Report Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning
• ICLR 2025 G-llava: Solving geometric problem with multi-modal large language model, Jiahui Gao, Renjie Pi, Jipeng Zhang, Jiacheng Ye, Wanjun Zhong, Yufei Wang, Lanqing Hong, Jianhua Han, Hang Xu, Zhenguo Li, Lingpeng Kong
• ACL 2025 Self-reasoning language models: Unfold hidden reasoning chains with few reasoning catalyst, Hongru Wang, Deng Cai, Wanjun Zhong, Shijue Huang, Jeff Z Pan, Zeming Liu, Kam-Fai Wong
• Information Processing & Management Adaptive-solver framework for dynamic strategy selection in large language model reasoning, Jianpeng Zhou, Wanjun Zhong, Yanlin Wang, Jiahai Wang
• AAAI 2025 Exploring iterative enhancement for improving learnersourced multiple-choice question explanations with large language models, Qiming Bao, Juho Leinonen, Alex Yuxuan Peng, Wanjun Zhong, Gaël Gendron, Timothy Pistotti, Alice Huang, Paul Denny, Michael Witbrock, Jiamou Liu

General Agent Model & System

Multi-modal Agent (GUI etc.)

• Seed Technical Report UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
• arXiv 2025 Game-TARS: Pretrained Foundation Models for Scalable Generalist Multimodal Game Agents, Zihao Wang, Xu Li, Yining Ye, Junjie Fang, Haoming Wang, Liang Liu, Shihao Liang, Jianqiao Lu, Zhenghao Wu, Jiazhan Feng, …, Wanjun Zhong, et al.
• Seed Technical Report UI-TARS: Pioneering Automated GUI Interaction with Native Agents, Yujia Qin, Yining Ye, Junjie Fang, Haoming Wang, Shihao Liang, Shizuo Tian, Junda Zhang, Jiahao Li, Yunxin Li, Shijue Huang, Wanjun Zhong, Kuanye Li, Jiale Yang, Yu Miao, Woyu Lin, Longxiang Liu, Xu Jiang, Qianli Ma, Jingyu Li, Xiaojun Xiao, Kai Cai, Chuang Li, Yaowei Zheng, Chaolin Jin, Chen Li, Xiao Zhou, Minchao Wang, Haoli Chen, Zhaojian Li, Haihua Yang, Haifeng Liu, Feng Lin, Tao Peng, Xin Liu, Guang Shi

Tool-Learning Agent

• Sub. to NeurIPS 2025 Retool: Reinforcement learning for strategic tool use in llms, Jiazhan Feng, Shijue Huang, Xingwei Qu, Ge Zhang, Yujia Qin, Baoquan Zhong, Chengquan Jiang, Jinxin Chi, Wanjun Zhong
• Arxiv Autokaggle: A multi-agent framework for autonomous data science competitions, Ziming Li, Qianbo Zang, David Ma, Jiawei Guo, Tuney Zheng, Minghao Liu, Xinyao Niu, Yue Wang, Jian Yang, Jiaheng Liu, Wanjun Zhong, Wangchunshu Zhou, Wenhao Huang, Ge Zhang
• EMNLP 2025 Otc: Optimal tool calls via reinforcement learning, Hongru Wang, Cheng Qian, Wanjun Zhong, Xiusi Chen, Jiahao Qiu, Shijue Huang, Bowen Jin, Mengdi Wang, Kam-Fai Wong, Heng Ji
• ACL 2024 Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios, Shijue Huang, Wanjun Zhong, Jianqiao Lu, Qi Zhu, Jiahui Gao, Weiwen Liu, Yutai Hou, Xingshan Zeng, Yasheng Wang, Lifeng Shang, Xin Jiang, Ruifeng Xu, Qun Liu

Code Agent

• Arxiv Agents in software engineering: Survey, landscape, and vision, Yanlin Wang, Wanjun Zhong, Yanxian Huang, Ensheng Shi, Min Yang, Jiachi Chen, Hui Li, Yuchi Ma, Qianxiang Wang, Zibin Zheng
• ICSME 2023 You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search, Yanlin Wang, Lianghong Guo, Ensheng Shi, Wenqing Chen, Jiachi Chen, Wanjun Zhong, Menghan Wang, Hui Li, Hongyu Zhang, Ziyu Lyu, Zibin Zheng
• ISSTA 24 - Outstanding Paper Award When to stop? towards efficient code generation in llms with excess token prevention, Lianghong Guo, Yanlin Wang, Ensheng Shi, Wanjun Zhong, Hongyu Zhang, Jiachi Chen, Ruikai Zhang, Yuchi Ma, Zibin Zheng

Agent Memory

• AAAI 2024 MemoryBank: Enhancing Large Language Models with Long-Term Memory, Wanjun Zhong, Lianghong Guo, Qiqi Gao, He Ye, Yanlin Wang

Agent-driven Training

• arXiv 2026 Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence, Guanting Dong, Jianqiao Lu, Junjie Huang, Wanjun Zhong, Liang Liu, Shijue Huang, Zhenghao Li, Yang Zhao, Xiao Song, et al.
• arXiv 2024 YODA: Teacher-Student Progressive Learning for Language Models, Jianqiao Lu, Wanjun Zhong, Yufei Wang, Zhijiang Guo, Qi Zhu, Wenyong Huang, Yanlin Wang, Fei Mi, Baojun Wang, Yasheng Wang, Lifeng Shang, Xin Jiang, Qun Liu (* equal contribution)

Benchmark and Evaluation

• NAACL 2024 AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models, Wanjun Zhong, Ruixiang Cui, Yiduo Guo, Yaobo Liang, Shuai Lu, Yanlin Wang, Amin Saied, Weizhu Chen, Nan Duan
• EMNLP 2024 CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models, Zexuan Qiu, Jingjing Li, Shijue Huang, Wanjun Zhong, Irwin King
• ACL 2024 Workshop PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering, Yiming Du, Hongru Wang, Zhengyi Zhao, Bin Liang, Baojun Wang, Wanjun Zhong, Zezhong Wang, Kam-Fai Wong
• ACL 2024 Followbench: A multi-level fine-grained constraints following benchmark for large language models, Yuxin Jiang, Yufei Wang, Xingshan Zeng, Wanjun Zhong, Liangyou Li, Fei Mi, Lifeng Shang, Xin Jiang, Qun Liu, Wei Wang

Self-Learning of LLMs

• AAAI 2025 Empowering Self-Learning of LLMs: Inner Knowledge Explicitation as a Catalyst, Shijue Huang, Wanjun Zhong, Deng Cai, Fanqi Wan, Chengyi Wang, Mingxuan Wang, Mu Qiao, Ruifeng Xu
• arXiv 2023 SELF: Language-driven self-evolution for large language model, Jianqiao Lu, Wanjun Zhong, Wenyong Huang, Yufei Wang, Fei Mi, Baojun Wang, Weichao Wang, Lifeng Shang, Qun Liu

General LLM Training

• arXiv 2023 Data management for large language models: A survey, Zige Wang, Wanjun Zhong, Yufei Wang, Qi Zhu, Fei Mi, Baojun Wang, Lifeng Shang, Xin Jiang, Qun Liu
• arXiv 2023 Aligning large language models with human: A survey, Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, Qun Liu
• ACL 2024 Learning to Edit: Aligning LLMs with Knowledge Editing, Yuxin Jiang, Yufei Wang, Chuhan Wu, Wanjun Zhong, Xingshan Zeng, Jiahui Gao, Liangyou Li, Xin Jiang, Lifeng Shang, Ruiming Tang, Qun Liu, Wei Wang

• ICSME 2023 You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search, Yanlin Wang, Lianghong Guo, Ensheng Shi, Wenqing Chen, Jiachi Chen, Wanjun Zhong, Menghan Wang, Hui Li, Hongyu Zhang, Ziyu Lyu, Zibin Zheng

• ACL 2023 CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding, Zhijian Hou, Wanjun Zhong, Leiji, Kun Yan, Difei Gao, Wing-Kwong Chan, Chong-Wah Ngo, Zheng Shou, Nan Duan (* equal contribution)

Previous Work Before 2023

Multi-Modal

• ICME 2023 Semantic Composition and Alignment with Cross-Modality-Aware Syntactic Hypergraph Convolutional Network for Video Question Answering, Zenan Xu, Wanjun Zhong, Qinliang Su, Zijing Ou, Fuwei Zhang (* equal contribution)
• ECCV Challenge 2022 An Efficient COarse-to-fiNE Alignment Framework @ Ego4D Natural Language Queries Challenge 2022, Zhijian Hou, Wanjun Zhong, Leiji, Kun Yan, Difei Gao, Wing-Kwong Chan, Chong-Wah Ngo, Zheng Shou, Nan Duan (* equal contribution) [code]

Knowledge-enhanced Language Model Reasoning

• ACL 2022 Disentangling Reasoning Capabilities from Language Models with Compositional Reasoning Transformers, Wanjun Zhong, Tingting Ma, Jiahai Wang, Jian Yin, Tiejun Zhao, Chin-Yew Lin, Nan Duan (* equal contribution)
• EMNLP 2022 Mixed-modality Representation Learning and Pre-training for Joint Table-and-Text Retrieval in OpenQA, JunJie Huang, Wanjun Zhong, Qian Liu, Ming Gong, Daxin Jiang, Nan Duan ( equal contribution) [code]
• NeurIPS 2022 LogiGAN: Learning Logical Reasoning via Adversarial Pre-training, Xinyu Pi, Wanjun Zhong, Yan Gao, Jian-guang Lou, Nan Duan (* equal contribution) [code]
• IJCAI 2022 (Oral) Reasoning over Hybrid Chain for Table-and-Text Open Domain Question Answering, Wanjun Zhong, Junjie Huang, Qian Liu, Ming Zhou, Jiahai Wang, Jian Yin, Nan Duan (* equal contribution) [code]
• NAACL 2022 ProQA: Structural Prompt-based Pre-training for Unified Question Answering, Wanjun Zhong, Yifan Gao, Ning Ding, Yujia Qin, Zhiyuan Liu, Ming Zhou, Jiahai Wang, Jian Yin, Nan Duan ( equal contribution) [code]
• TASLP 2022 From LSAT: The Progress and Challenges of Complex Reasoning, Siyuan Wang, Zhongkun Liu, Wanjun Zhong, Ming Zhou, Zhongyu Wei, Zhumin Chen, Nan Duan
• NAACL 2022 Analytical Reasoning of Text, Wanjun Zhong, Siyuan Wang, Duyu Tang, Zenan Xu, Daya Guo, Jiahai Wang, Jian Yin, Ming Zhou, Nan Duan [code]
• ACL 2022 Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Text, Siyuan Wang, Wanjun Zhong, Duyu Tang, Zhongyu Wei, Zhihao Fan, Daxin Jiang, Ming Zhou, Nan Duan [code]
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• EMNLP 2021 WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach, Junjie Huang, Duyu Tang, Wanjun Zhong, Shuai Lu, Linjun Shou, Ming Gong, Daxin Jiang, Nan Duan
• ACL 2021 UserAdapter: Few-Shot User Learning in Sentiment Analysis, Wanjun Zhong, Duyu Tang, Jiahai Wang, Jian Yin, Nan Duan
• ACL 2021 Syntax-Enhanced Pre-trained Model, Zenan Xu, Daya Guo, Duyu Tang, Qinliang Su, Linjun Shou, Ming Gong, Wanjun Zhong, Xiaojun Quan, Daxin Jiang, Nan Duan
• ACL 2021 Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge, Linmei Hu, Tianchi Yang, Luhao Zhang, Wanjun Zhong, Duyu Tang, Chuan Shi, Nan Duan, Ming Zhou
• EMNLP 2020 (Oral) Neural Deepfake Detection with Factual Structure of Text, Wanjun Zhong, Duyu Tang, Zenan Xu, Ruize Wang, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin [video]
• EMNLP 2020 Leveraging declarative knowledge in text and first-order logic for fine-grained propaganda detection, Ruize Wang, Duyu Tang, Nan Duan, Wanjun Zhong, Zhongyu Wei, Xuanjing Huang, Daxin Jiang, Ming Zhou
• ACL 2020 LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network, Wanjun Zhong, Duyu Tang, Zhangyin Feng, Nan Duan, Ming Zhou, Ming Gong, Linjun Shou, Daxin Jiang, Jiahai Wang, Jian Yin [video]
• ACL 2020 Reasoning Over Semantic-Level Graph for Fact Checking, Wanjun Zhong, Jingjing Xu, Duyu Tang, Zenan Xu, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin [video]
• NLPCC 2019 Improving Question Answering by Commonsense-Based Pre-Training, Wanjun Zhong, Duyu Tang, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin
• AI Open 2023 Improving Task Generalization via Unified Schema Prompt, Wanjun Zhong, Yifan Gao, Ning Ding, Zhiyuan Liu, Ming Zhou, Jiahai Wang, Jian Yin, Nan Duan
• arXiv 2020 A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts, Wanjun Zhong, Duyu Tang, Nan Duan, Ming Zhou, Jiahai Wang, Jian Yin