UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers — HN submission

Thu, 04 Jan 2024 16:48:34 GMT

Show HN: RAGatouille, a simple lib to use&train top retrieval models in RAG apps

Hey HN! If you’re at all interested in LLMs/LLM-apps, you’ve probably heard of RAG: Retrieval-Assisted Generation, i.e. retrieving relevant documents to give to your LLM as context to answer user queries. Today, I’m releasing RAGatouille v0.0.1, whose aim is to make it as easy as can be to improve your RAG pipelines by leveraging state-of-the-art Information Retrieval research. As of right now, there’s quite a big gap between common everyday practice and the IR literature, and a lot of the gap is because there just aren’t good ways to quickly try out and leverage SotA IR techniques.…

15 points; 5 discussion replies on HN. Paper and source history. A submission is not an endorsement.

UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers · HackerPapers discussions

UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers — HN submission