I am a Ph.D. student in Informatics at Penn State University, advised by Qingyun Wu. Previously I obtained my B.Eng in Computer Science from Xidian University (Rank 1/134). I have spent time at Adobe Research as a research scientist intern.
My research develops scalable frameworks and algorithms that help LLM agents reason, collaborate, and self-improve in complex open-ended environments. I study how to debug and optimize agentic behavior and how to form effective multi-agent teams.
Experience
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Adobe Research · Research Scientist Intern05/2025 - 08/2025
Multi-agent intelligence for creative support.
Publications
(* equal contribution)
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Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at ScaleEMNLP Findings
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SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative RefinementEMNLP
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Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent SystemsICML Spotlight
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Adaptive In-conversation Team Building for Language Model AgentsCOLM Workshop
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Autogen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation FrameworkCOLM ICLR Workshop Best Paper Award
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Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance ConstraintsICML Spotlight
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Offline Training of Language Model Agents with Functions as Learnable WeightsICML
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IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language ModelsICLR
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Embodied LLM Agents Learn to Cooperate in Organized TeamsNeurIPS Workshop
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Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality PredictionNexus
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RLAD: A Reliable Hippo-guided Multi-task Model for Alzheimer's Disease DiagnosisJ-BHI
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Moderate Coreset: A Universal Method of Data Selection for Real-world Data AnalysisICLR
Open Source
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Co-creator and maintainer. An open-source framework enabling next-gen LLM applications via multi-agent conversation.
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Co-creator and maintainer. The evolution of AutoGen with integrated adaptive team building for LLM agents.
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Maintainer. A fast library for automated machine learning and tuning.