Papers with MiniTruePrefixes
PrefixNLI: Detecting Factual Inconsistencies as Soon as They Arise (2026.acl-long)
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| Challenge: | Large Language Models (LLMs) are prone to factually inconsistent statements, known as hallucinations. |
| Approach: | They propose to train a specialized model that detects inconsistencies over text prefixes to improve generation faithfulness by 5-14 F1 points. |
| Outcome: | The proposed model outperforms baseline models by 5-14 F1 points in prefix-level entailment. |