Benchmarking Uncertainty Metrics for LLM Target-Aware Search (2025.findings-emnlp)
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| Challenge: | Existing uncertainty metrics for LLM search methods do not capture the diverse types of uncertainty needed to guide different optimization goals. |
| Approach: | They propose a framework for uncertainty benchmarking that captures four different uncertainty types . the uncertainty types Answer, Correctness, Aleatoric, and Epistemic serve different optimization goals . |
| Outcome: | The proposed framework identifies four different uncertainty types . the uncertainty types serve different optimization goals in LLM search . |
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