Papers with hallucination detection method
Light-Weight Hallucination Detection using Contrastive Learning for Conditional Text Generation (2025.acl-srw)
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| Challenge: | Existing methods for hallucination detection are limited to the scenario where we can access the LLMs that have generated the outputs. |
| Approach: | They propose a hallucination detection method that uses contrastive learning to pull faithful outputs and input contexts together while pushing hallucinous outputs apart. |
| Outcome: | The proposed method outperforms GPT-4o prompting in binary hallucination detection. |
ICR Probe: Tracking Hidden State Dynamics for Reliable Hallucination Detection in LLMs (2025.acl-long)
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| Challenge: | Existing methods for hallucination detection rely on static and isolated representations, overlooking their dynamic evolution across layers. |
| Approach: | They propose a method which captures the cross-layer evolution of hidden states and propose 'ICR Probe' which capture the evolution of the hidden states. |
| Outcome: | The proposed method achieves superior performance with significantly fewer parameters and ablation studies offer deeper insights into the underlying mechanism of the method, improving its interpretability. |