Why Uncertainty Estimation Methods Fall Short in RAG: An Axiomatic Analysis (2025.findings-acl)
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| Challenge: | Existing UE methods cannot reliably estimate the correctness of LLM responses in Retrieval-Augmented Generation (RAG) . Existing methods generate low uncertainty values without considering relevance of context to query . |
| Approach: | They propose an axiomatic framework to identify deficiencies in existing UE methods and introduce five constraints that an effective UE method should meet after incorporating retrieved documents into the LLM’s prompt. |
| Outcome: | The proposed framework satisfies all the axioms and improves correlation between uncertainty estimates and correctness. |
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