공대생 도전 일지

https://arxiv.org/abs/2006.16668 GShard: Scaling Giant Models with Conditional Computation and Automatic ShardingNeural network scaling has been critical for improving the model quality in many real-world machine learning applications with vast amounts of training data and compute. Although this trend of scaling is affirmed to be a sure-fire approach for better modelarxiv.org      이 논문은 대규모 신경망을..

https://arxiv.org/abs/2309.01431 Benchmarking Large Language Models in Retrieval-Augmented GenerationRetrieval-Augmented Generation (RAG) is a promising approach for mitigating the hallucination of large language models (LLMs). However, existing research lacks rigorous evaluation of the impact of retrieval-augmented generation on different large languagearxiv.org 이 논문에선 LLM의 할루시네이션, 지식 갱신을 해결하기 ..