RAG systems optimize for factual certainty and ignore opinion diversity; O-RAG reduces Wasserstein distance to corpus sentiment and is preferred by humans 79% of the time.
Nomiracl: Knowing when you don’t know for robust multilingual retrieval-augmented generation
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A survey of RAG paradigms, components, benchmarks, and challenges for improving LLMs on knowledge-intensive tasks.
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Retrieval-Augmented Generation Must Move Beyond Factual Grounding to Represent Diverse Opinions
RAG systems optimize for factual certainty and ignore opinion diversity; O-RAG reduces Wasserstein distance to corpus sentiment and is preferred by humans 79% of the time.
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Retrieval-Augmented Generation for Large Language Models: A Survey
A survey of RAG paradigms, components, benchmarks, and challenges for improving LLMs on knowledge-intensive tasks.