CARE, a context-aware LLM judge, outperforms standard methods when evaluating multi-hop retrieval quality in RAG systems.
arXiv preprint arXiv:2409.03759v1 , year=
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DoRA is a new synthetic benchmark for RAG-based QA on defense documents where fine-tuning Llama3.1-8B-Instruct on it improves task success by up to 26% and cuts hallucination rates by 47%.
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Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies
CARE, a context-aware LLM judge, outperforms standard methods when evaluating multi-hop retrieval quality in RAG systems.
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Domain-oriented RAG Assessment (DoRA): Synthetic Benchmarking for RAG-based Question Answering on Defense Documents
DoRA is a new synthetic benchmark for RAG-based QA on defense documents where fine-tuning Llama3.1-8B-Instruct on it improves task success by up to 26% and cuts hallucination rates by 47%.