2 papers
cs.CL2026
CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning
Cheng-Yen Li, Xuanjun Chen, Claire Lin +4
Large Language Models (LLMs) struggle with knowledge-intensive tasks due to hallucinations and fragmented reasoning over dispersed information. While Retrieval-Augmented Generation…
cs.LG2025
Brewing Knowledge in Context: Distillation Perspectives on In-Context Learning
Chengye Li, Haiyun Liu, Yuanxi Li
In-context learning (ICL) allows large language models (LLMs) to solve novel tasks without weight updates. Despite its empirical success, the mechanism behind ICL remains poorly un…