Eyes Show the Way: Modelling Gaze Behaviour for Hallucination Detection (2023.findings-emnlp)
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| Challenge: | Existing methods for hallucination detection depend on knowledge sources that are explicit such as Wikipedia or knowledge graphs. |
| Approach: | They propose a cognitive approach that leverages gaze signals from humans to detect hallucinations in natural language processing (NLP) they collect and introduce an eye tracking corpus consisting of 500 instances, annotated by five annotators for hallucinism detection. |
| Outcome: | The proposed approach achieves a balanced accuracy of 87.1% on a FactCC dataset. |
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| Challenge: | Recent studies on hallucination in large language models (LLMs) have been actively progressing in natural language processing. |
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