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 generates synthetic RAG training and evaluation data from 40 defense documents, halving hallucination rates in a LoRA-adapted Llama3.1-8B compared to 8 baselines.
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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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A Benchmark Construction and Evaluation Framework for Specialist Domains: Case Study on Defense-related Documents
DoRA generates synthetic RAG training and evaluation data from 40 defense documents, halving hallucination rates in a LoRA-adapted Llama3.1-8B compared to 8 baselines.