Papers by Neeraja Kirtane
FACTCHECKMATE: Preemptively Detecting and Mitigating Hallucinations in LMs (2025.findings-emnlp)
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| Challenge: | Language models (LMs) hallucinate. |
| Approach: | They introduce a classifier that predicts whether LMs hallucinate based on model’s hidden states before decoding begins. |
| Outcome: | The proposed model preemptively detects hallucinations by learning a classifier that predicts whether the LM will hallucinate . if a hallucinomy is detected, FactCheckmate intervenes by adjusting the model’s hidden states to produce more factual outputs. |