About me
I am currently a 3rd year PhD student at the Gaoling School of Artificial Intelligence, Renmin University of China, mentored by Prof. Zhicheng Dou. I earned my bachelor’s degree (2019-2023) at Nankai University.
I’m currently a RedStar research intern focusing on foundation agent research at Xiaohongshu Inc. I have published 20+ papers in top-tier AI conferences and journals (8 first-author papers), including NeurIPS, ICML, ICLR, ACL, EMNLP, AAAI, SIGIR, WWW, and TOIS.
Citations:
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Project Stars:
Research Interests:
- Omni-Modal Agents: Building real-world omni-modal AI assistants (OmniGAIA);
- Foundation Agents: Developing general-purpose agentic LLMs (DeepAgent, AEPO, Tool-Star);
- Deep Research: Enhancing long-horizon reasoning with web information seeking (WebThinker, Search-o1, HiRA);
- Retrieval-Augmented LLMs: Improving large language models with knowledge retrieval (RetroLLM, CorpusLM, UniGen).
I aim to build Real-World AI Agents that are reliable, capable, and genuinely helpful in everyday life.
🔥 News
- 2026.05: 🎤 Invited talk on “Reason, Search, and Act: Towards Real-World AI Agents” at MLNLP Community. [Link]
- 2026.04: 🚀 Released Agent-World, scaling real-world environment synthesis for evolving general agent intelligence! Check out our demo! [Demo]
- 2026.03: 🎉 DeepAgent has reached 1k stars! A General Reasoning Agent with Scalable Toolsets. [Demo]
- 2026.02: 🚀 Released OmniGAIA: Towards native omni-modal AI agents. [Demo]
- 2026.01: 🎉 DeepAgent and AEPO selected for Oral Presentation at WWW 2026!
- 2025.09: 🎉 WebThinker accepted by NeurIPS 2025! (1.2k+ stars, 100+ citations). A powerful deep research agent that can think, search, and write autonomously. [Demo]
- 2025.08: 🎉 Search-o1 selected for Oral Presentation at EMNLP 2025! (1k+ stars, 200+ citations). The first framework that performs interleaved reasoning and web-search for o1-like reasoning models.
- 2025.06: 💻 Joined Xiaohongshu as a RedStar research intern, focusing on general agents.
- 2025.05: 🎉 Four papers accepted by ACL 2025! Looking forward to seeing you in Vienna!
- 2024.03: 🎉 CorpusLM selected for Oral Presentation at SIGIR 2024! A unified LLM for retrieval and QA.
- 2025.02: 🎉 Our survey on Generative Information Retrieval (GenIR) accepted by ACM TOIS! See more details.
- 2023.12: 🎉 Our unified generative framework for retrieval and QA has been accepted by AAAI 2024! See more details.
💻 Experiences
- Incoming |
ByteDance Seed, Foundation LLM Team
Research Intern on General Agents (Seed-LLM Talent Program)
Mentors: Wanjun Zhong, Yujia Qin - 2025.06 - 2026.05 |
Xiaohongshu, Agent R&D Team
Research Intern on General Agents (RedStar Program)
Mentors: Wenxiang Jiao, Yuan Lu
📝 Selected Work
OmniGAIA: Towards Native Omni-Modal AI Agents
- Introduces OmniGAIA, a comprehensive benchmark for evaluating omni-modal agents on complex reasoning and tool-use across videos, images, and audios.
- Presents OmniAtlas, a native omni-modal reasoning agent with active perception and autonomous tool use.
DeepAgent: A General Reasoning Agent with Scalable Toolsets
- A general reasoning agent that can autonomously discover and use tools, while compressing memory to support long-horizon interactions.
- Introduces ToolPO, an end-to-end agentic RL training strategy that improves overall performance.
WebThinker: Empowering Large Reasoning Models with Deep Research Capability
- An reasoning agent designed to autonomously search, deeply explore web pages, and draft research reports, all within its thinking process.
Search-o1: Agentic Search-Enhanced Large Reasoning Models
- The first framework that enables o1-style reasoning models to autonomously search for and consult external information when they encounter missing or unfamiliar knowledge.
- RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation
Xiaoxi Li, Jiajie Jin, Yujia Zhou, Yongkang Wu, Zhonghua Li,
ACL 2025 Main
- From Matching to Generation: A Survey on Generative Information Retrieval
Xiaoxi Li, Jiajie Jin, Yujia Zhou, Yuyao Zhang, Peitian Zhang,
TOIS 2025 (JCR Q1, IF=9.1) (Most Influential arXiv IR Papers in 2024 – Top 11/All)
- CorpusLM: Towards a Unified Language Model on Corpus for Knowledge-intensive Tasks
Xiaoxi Li, Zhicheng Dou, Yujia Zhou, Fangchao Liu.
SIGIR 2024 (Oral)
- UniGen: A Unified Generative Framework for Retrieval and Question Answering with Large Language Models
Xiaoxi Li, Yujia Zhou, Zhicheng Dou.
AAAI 2024
- Hierarchical Document Refinement for Long-context Retrieval-augmented Generation
Jiajie Jin, Xiaoxi Li, Guanting Dong, Yuyao Zhang, Yutao Zhu,
ACL 2025 Main (Oral)
- RAG-Critic: Leveraging Automated Critic-Guided Agentic Workflow for Retrieval Augmented Generation
Guanting Dong, Jiajie Jin, Xiaoxi Li, Yutao Zhu, Zhicheng Dou,
ACL 2025 Main - Agentic Entropy-Balanced Policy Optimization
Guanting Dong, Licheng Bao, Zhongyuan Wang, Kangzhi Zhao, Xiaoxi Li,
WWW 2026 (Oral)
- ImplicitRM: Unbiased Reward Modeling from Implicit Preference Data for LLM alignment
Hao Wang, Haocheng Yang, Licheng Pan, Lei Shen, Xiaoxi Li,
ICML 2026 - HiRA: A Hierarchical Reasoning Framework for Decoupled Planning and Execution in Deep Search
Jiajie Jin, Xiaoxi Li, Guanting Dong, Yuyao Zhang, Yutao Zhu,
SIGIR 2026
- Tool-Star: Empowering LLM-Brained Multi-Tool Reasoner via Reinforcement Learning
Guanting Dong, Yifei Chen, Xiaoxi Li, Jiajie Jin, Hongjin Qian,
SIGIR 2026
📖 Educations
- 2023.09 - Present |
Ph.D. in Artificial Intelligence
Gaoling School of Artificial Intelligence, Renmin University of China - 2019.09 - 2023.06 |
B.Sc. in Intelligence Science and Technology
College of Artificial Intelligence, Nankai University
🎤 Invited Talks
- 2026.05: “Reason, Search, and Act: Towards Real-World AI Agents”, MLNLP Community. [Link]
- 2026.03: “Reason, Search, and Act: Towards Real-World AI Agents”, CCIR PhD Forum.
- 2025.04: “WebThinker: Empowering Large Reasoning Models with Deep Research Capability”, MLNLP Community. [Link]
📚 Academic Services
- PC Member: ACL Rolling Review, NeurIPS, ICML, ICLR, SIGIR, AAAI (Silver Reviewer Award @ ICML’26)
- Journal Reviewer: ACM Computing Surveys, TOIS