Jiale Liu

Portrait of Jiale Liu

I am a Ph.D. student in Informatics at Penn State University, advised by Qingyun Wu. I am currently a student researcher at Google DeepMind in New York, working on continual learning and memory for LLM agents. In summer 2025, I was a research scientist intern at Adobe Research. Before Penn State, I obtained my B.Eng. in Computer Science from Xidian University, where I ranked first in my class of 134.

My research develops scalable frameworks and algorithms that enable LLM agents to reason, collaborate, and self-improve in complex, open-ended environments. In particular, I study how to debug and optimize agentic behavior and how to form effective multi-agent teams. I am a co-creator and maintainer of AutoGen.

2027 Job Market

I am on the job market and looking for full-time roles starting in 2027. If you are hiring, I would love to hear from you. jiale.liu@psu.edu

Experience

  • May 2026 – Present

    Google DeepMind Student Researcher, New York, NY

    Continual learning and memory for LLM agents that learn from experience.

    Mentors: Zun Li, John Schultz, Marc Lanctot

  • May – Aug 2025

    Adobe Research Research Scientist Intern, San Jose, CA

    Multi-agent intelligence for creative support.

    Mentors: Victor S. Bursztyn, Saayan Mitra

Publications

* equal contribution

2026

  1. Who&When Pro: Can LLMs Really Attribute Failures in AI Agents?

    Jiale Liu, Huajun Xi, Shaokun Zhang, Yifan Zeng, Tianwei Yue, Chi Wang, Jian Kang, Qingyun Wu, Huazheng Wang

    NeurIPS E&D 2026 Paper Code Project

  2. TeamFusion: Supporting Open-ended Teamwork with Multi-Agent Systems

    Jiale Liu, Victor Bursztyn, Lin Ai, Haoliang Wang, Sunav Choudhary, Saayan Mitra, Qingyun Wu

    ACL 2026 Paper

  3. Digital Agents Require Unified Agent-Native Environments

    Yiran Wu*, Jiale Liu*, Jieyu Zhang, Yaolun Zhang, Shilong Liu, Chi Wang, Mengdi Wang, Huazheng Wang, Qingyun Wu

    ICML 2026 Paper Code Project

2025

  1. Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at Scale

    Jiale Liu, Yifan Zeng, Shaokun Zhang, Chi Zhang, Malte Højmark-Bertelsen, Marie Normann Gadeberg, Huazheng Wang, Qingyun Wu

    EMNLP Findings 2025 Paper Code

  2. SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement

    Chelsi Jain, Yiran Wu, Yifan Zeng, Jiale Liu, Zhenwen Shao, Qingyun Wu, Huazheng Wang

    EMNLP 2025 Paper Code

  3. Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems

    Shaokun Zhang, Ming Yin, Jieyu Zhang, Jiale Liu, et al.

    ICML 2025 Spotlight Paper Code Project

2024

  1. Adaptive In-conversation Team Building for Language Model Agents

    Linxin Song*, Jiale Liu*, Jieyu Zhang, Shaokun Zhang, Ao Luo, Shijian Wang, Qingyun Wu, Chi Wang

    COLM Workshop 2024 Paper

  2. Autogen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

    Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Jiale Liu, Ahmed Hassan Awadallah, Ryen W White, Doug Burger, Chi Wang

    COLM 2024 ICLR Workshop Best Paper Award Paper Code

  3. Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints

    Xiaobo Xia, Jiale Liu, Shaokun Zhang, Qingyun Wu, Tongliang Liu

    ICML 2024 Spotlight Paper

  4. Offline Training of Language Model Agents with Functions as Learnable Weights

    Shaokun Zhang, Jieyu Zhang, Jiale Liu, Linxin Song, Chi Wang, Ranjay Krishna, Qingyun Wu

    ICML 2024 Paper

  5. IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models

    Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang, Ling-Hao Chen, Jiale Liu, Qingyun Wu, Tongliang Liu

    ICLR 2024 Paper Code

  6. Embodied LLM Agents Learn to Cooperate in Organized Teams

    Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L Griffiths, Mengdi Wang

    NeurIPS Workshop 2024 Paper Code

  7. Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction

    Xiaobo Xia, Xiaofeng Liu, Jiale Liu, et al.

    Nexus 2024 Paper Code

  8. RLAD: A Reliable Hippo-guided Multi-task Model for Alzheimer's Disease Diagnosis

    Zhenxin Lei*, Wenjing Zhu*, Jiale Liu*, Cong Hua, Johann Li, Syed Afaq Ali Shah, Liang Zhang, Mohammed Bennamoun, Cuiping Mao

    J-BHI 2024 Paper

2023

  1. Moderate Coreset: A Universal Method of Data Selection for Real-world Data Analysis

    Xiaobo Xia, Jiale Liu, Jun Yu, Xu Shen, Bo Han, Tongliang Liu

    ICLR 2023 Paper Code

Open Source

  • Co-creator, Maintainer
    AutoGen microsoft/autogen

    An open-source framework enabling next-gen LLM applications via multi-agent conversation.

  • Co-creator, Maintainer
    AG2 ag2ai/ag2

    The evolution of AutoGen with integrated adaptive team building for LLM agents.

  • Maintainer
    FLAML microsoft/FLAML

    A fast library for automated machine learning and tuning.