공대생 도전 일지

Is Semantic Chunking Worth the Computational Cost? - 논문 리뷰

https://arxiv.org/abs/2410.13070 Is Semantic Chunking Worth the Computational Cost?Recent advances in Retrieval-Augmented Generation (RAG) systems have popularized semantic chunking, which aims to improve retrieval performance by dividing documents into semantically coherent segments. Despite its growing adoption, the actual benefits ovearxiv.org 제가 생각했던 내용을 논문으로 정리해놨는데성능이 나빠진 다는 것이 오히려 의외였습니다....

BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models - 논문 리뷰

https://arxiv.org/abs/2404.12494 BIRD: A Trustworthy Bayesian Inference Framework for Large Language ModelsPredictive models often need to work with incomplete information in real-world tasks. Consequently, they must provide reliable probability or confidence estimation, especially in large-scale decision making and planning tasks. Current large language modelsarxiv.org    연구 목적대규모 언어 모델(LLM)의 확..