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AquiLLM: Evaluating Faithfulness in Open-Weight RAG-LLM Systems for Scientific Research

This story is from 2026-09-16. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.16519v1 Announce Type: new Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that provide natural language access to scientific knowledge and research workflows. Researchers are expl…

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  1. 2026-09-16 04:00 · arXiv cs.AI
    AquiLLM: Evaluating Faithfulness in Open-Weight RAG-LLM Systems for Scientific Research

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