Papers with hallucination detection classifier
Light-Weight Hallucination Detection using Contrastive Learning for Conditional Text Generation (2025.acl-srw)
Copied to clipboard
| 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. |