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George Lee

2 accepted papers

2026

ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory

ICLR 2026poster

With the growing adoption of large language model (LLM) agents in persistent, real-world roles, they naturally encounter continuous streams of tasks and interactions. A key limitation, however, is their failure to learn from this accumulated experience, forcing them to discard valuable insights and…

Cited by 0SourcecodeScholar
2025

In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents

ACL 2025long

Large Language Models (LLMs) have made significant progress in open-ended dialogue, yet their inability to retain and retrieve relevant information from long-term interactions limits their effectiveness in applications requiring sustained personalization. External memory mechanisms have been propose…