Hi, I am a First year master student at THUNLP lab, Tsinghua University, advised by Zhiyuan_Liu. working on computer science、Tool-Learning、Agent. I believe the future will not invent itself.
Recent News
- (02/2025) reach 1000 citations on Google-Scholar
- (08/2024) Intern at Bytedance
- (02/2024) Teaching Assistant of NLP, Tsinghua
- (02/2024) Teaching Assistant of Program Design Basics, Tsinghua ( DebugBench techniques in education)
- (01/2024) Teaching Assistant of NLP Mooc, learnX
- (11/2023) Give a talk at AITime about Tool learning techniques
- (10/2023) reach 100 citations on Google-Scholar
Academic Background
| Name | Time | Degree | Icon |
|---|---|---|---|
| Beijing National Day School | 2016-2019 | High school |  |
| Tsinghua University, Computer Science and Technology | 2019-2023 | Bachelor’s Degree |  |
| Tsinghua University, Computer Science and Technology, THUNLP Lab | 2023-2026 | Master’s Degree |  |
Selected Publications
- 2025/01: UI-TARS: Pioneering Automated GUI Interaction with Native Agents (6k star)
We trained a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., keyboard and mouse operations). TARS achieves SOTA performance in 10+ GUI agent benchmarks evaluating perception, grounding, and GUI task execution. Notably, in the OSWorld benchmark, UI-TARS achieves scores of 24.6 with 50 steps and 22.7 with 15 steps, outperforming Claude (22.0 and 14.9 respectively)
It’s basically the reverse of XAgent
- 2024/02: RepoAgent: An LLM-Powered Open-Source Framework for Repository-level Code Documentation Generation(EMNLP 2024)
Our goal is to create an intelligent document assistant that helps people read and understand repositories and generate documents, ultimately helping people improve efficiency and save time.
- 2024/01: DebugBench: Evaluating Debugging Capability of Large Language Models (ACL 2024)
We have evaluated the debugging abilities of common LLMs, and we found that open-source LLM did poor on that task
We explored using LLM to automatically generate RPA workflows, and how to use LLM as AI-data and AI-logic node in the workflow, which is called APA(Agentic Process Automation)
- 2023/10: XAgent (8k star)
XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.
- 2023/8: Large Language Model as Autonomous Decision Maker (ICLR 2025)
We Provided a novel Elo-based tree search method, connecting prior and posterior knowledge, and reaching the SOTA on the ToolBench Dataset
- 2023/7: Toolllm: Facilitating large language models to master 16000+ real-world apis (ICLR 2024 spotlight)
We aligned 16000+ real-world RapidAPI query, tested ChatGPT and GPT-4 to automaticaly handle real-world without human knowledge. Together, we trained Llama on the annotated data, making Llama the same function calling ability with ChatGPT
- 2023/4: Tool Learning with Foundation Models (CORR)
We make the first step towards general tool learning settings, testing on about 30 tasks.
Honors & Awards
- Outstanding-Graduate in Computer Science and Technology, Tsinghua University
- Outstanding-Graduate in Tsinghua University
Collaborators
| Name | Description | Photo |
|---|---|---|
| Zhiyuan Liu |  |
|
| Maosong Sun |  |
|
| Yujia Qin |  |
|
| Xin Cong |  |
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| Fanchao Qi |  |