Fulin Lin

To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining prior knowledge. Current unified stream-based memory systems facilitate context updates but remain vulnerable to interference from transient nois...

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) yet suffers from a mismatch between coarse retrieval granularity and fine-grained generation needs. Specifically, coarse-grained passages inherently conflate valid context with intra-passage noise that semantic retrieval o...