4 papers
MemR: Memory Retrieval via Reflective Reasoning for LLM Agents
Xingbo Du, Loka Li, Duzhen Zhang +1
Memory systems have been designed to leverage past experiences in Large Language Model (LLM) agents. However, many deployed memory systems primarily optimize compression and storag…
LifelongAgentBench: Evaluating LLM Agents as Lifelong Learners
Junhao Zheng, Xidi Cai, Qiuke Li +5
Lifelong learning is essential for intelligent agents operating in dynamic environments. Current large language model (LLM)-based agents, however, remain stateless and unable to ac…
From System 1 to System 2: A Survey of Reasoning Large Language Models
Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang +18
Achieving human-level intelligence requires refining the transition from the fast, intuitive System 1 to the slower, more deliberate System 2 reasoning. While System 1 excels in qu…
Beyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMs
Zixiao Wang, Duzhen Zhang, Ishita Agrawal +3
Previous approaches to persona simulation large language models (LLMs) have typically relied on learning basic biographical information, or using limited role-play dialogue dataset…