Uncertainty Quantification of Large Language Models through Multiple Uncertainty Sources (2026.findings-acl)
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| Challenge: | Existing methods for uncertainty quantification fail to capture multifaceted nature of natural language generation. |
| Approach: | They propose a multi-resource Uncertainty Quantification framework that integrates heterogeneous uncertainty signals into a unified measure. |
| Outcome: | The proposed framework outperforms existing methods on CoQA, NQ_Open, and HotpotQA. |
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