FG-PRM: Fine-grained Hallucination Detection and Mitigation in Language Model Mathematical Reasoning (2025.findings-emnlp)
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| Challenge: | Existing methods to detect hallucinations in large language models lack nuanced understanding of their types and manifestations. |
| Approach: | They propose a taxonomy that categorizes hallucinations into six types . they propose an augmented model to detect and mitigate hallucinosity in a fine-grained manner . |
| Outcome: | The proposed model detects and mitigates hallucinations in a fine-grained manner . it significantly boosts the performance of LLMs on GSM8K and MATH benchmarks. |
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