Papers by Pinlong Cai

    2 papers
    Towards Self-Evolving Agents: Enabling Autonomy through Interactive Experience Refinement (2026.findings-acl)

    Copied to clipboard

    Challenge: Large Language Models struggle with complex, multi-step operational tasks because they remain static during inference and cannot learn from past experience.
    Approach: They propose a framework that organizes cross-domain insights to facilitate orchestration of long-horizon workflows.
    Outcome: The proposed framework outperforms existing methods on the TAC productivity benchmark and shows strong cross-task transferability.
    The Agent’s First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios (2026.findings-acl)

    Copied to clipboard

    Challenge: Existing research mainly focuses on performance upper bounds in static environments, overlooking stochastic real-world deployment.
    Approach: They propose a dynamic evaluation environment that simulates a "trainee" agent continuously exploring a novel setting.
    Outcome: The proposed model evaluates agents in a dynamic evaluation environment that simulates a "trainee" agent continuously exploring a novel setting.

    What is GenGO?

    GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

    Information

    About
    Limitations