Weihang Su

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Department of Computer Science and Technology, Tsinghua University

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About me

Welcome to my homepage! I am Weihang Su (苏炜航), a fourth-year PhD student in the Department of Computer Science and Technology at Tsinghua University, where I am fortunate to be advised by Prof. Yiqun Liu and Assoc. Prof. Qingyao Ai.

During the early stage of my PhD, I explored a broad range of research problems at the intersection of Information Retrieval and Large Language Models, publishing 10+ first-author papers and contributing substantially as a second author to 10+ additional works across the following areas:

Since 2025, my research has gradually converged on a unified long-term agenda: How language models and agents acquire, use, and update external knowledge and capabilities.

Within this agenda, I view retrieval as a foundational mechanism because it enables LLMs and agents to access scalable, potentially unbounded external knowledge and capabilities beyond what can be stored in their parameters or accommodated within a fixed context window. My current work, therefore, focuses on retrieval-augmented systems, agent skills, procedural capabilities, and knowledge-intensive LLM applications.


To date, my research at the intersection of Information Retrieval and Large Language Models has received both academic recognition and broad impact. Recent highlights include the SIGIR 2024 Best Paper Award 🏆, and my work on Parametric RAG is currently the most-cited paper at SIGIR 2025 📈 (as of March 2026, according to Google Scholar). Beyond publications, I actively serve the research community as a PC member or reviewer for top-tier venues, including NeurIPS, ICML, ICLR, ACL, and SIGIR. I have also delivered tutorials on Dynamic and Parametric RAG at flagship conferences, including SIGIR 2025 and SIGIR-AP 2025, as the lead presenter.

My academic research is also closely connected to industrial practice. Since October 2025, I have been working as a research intern at ByteDance (TikTok), focusing on developing advanced AI Agents. In particular, I study how specialized agents and agent skills can be automatically constructed, organized, and deployed in agentic systems, with the goal of bridging cutting-edge LLM research and scalable real-world applications.

I am also highly passionate about mentoring undergraduate students. I have had the privilege of collaborating with many talented undergraduates, and together we have co-authored papers at premier conferences and journals such as ACL, SIGIR, EMNLP, TOIS, AAAI, and The Web Conference.

If you are an undergraduate student interested in my research areas and driven to pursue high-quality research, you are very welcome to apply for an internship with the THUIR group through official channels, or contact me directly via WeChat (rdfzswh) to explore potential collaboration.

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Selected Awards

Publications

Link to Google Scholar

The titles of my first-author papers are in bold (excluding co-first where the ranking is not first).

Paper Under Submission

Year 2026

Year 2025

Year 2024

Before 2024

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