zorazrw/filco
[Preprint] Learning to Filter Context for Retrieval-Augmented Generaton
This tool helps improve the accuracy and relevance of answers generated by AI systems, especially for question-answering tasks. It takes a question and a collection of retrieved text passages, then intelligently filters out less relevant information. The output is a refined set of passages that helps the AI generate more precise answers. It's for researchers and practitioners working on fine-tuning large language models for specific generative AI applications.
196 stars. No commits in the last 6 months.
Use this if you are building or fine-tuning a retrieval-augmented generation (RAG) system and want to reduce 'hallucinations' or irrelevant information in the generated output.
Not ideal if you are looking for a ready-to-use, off-the-shelf generative AI application or if you don't have experience with training and evaluating large language models.
Stars
196
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20
Language
Python
License
CC-BY-SA-4.0
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Last pushed
Apr 06, 2024
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