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Trusting Your Evidence: Hallucinate Less with Context-aware Decoding
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“Even when provided with accurate context, models may misinterpret the data or include details that are not supported by the context (Shi et al., 2024;Chuang et al., 2024).”
From SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models (2025) · cites this paper as Shi et al., 2024
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Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
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SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
Chuang, Y.-S., Cohen-Wang, B., Shen, S. Z., Wu, Z., Xu, H., Lin, X. V., Glass, J., Li, S.-W., & Yih, W.-T. (2025) · arXiv · doi:10.48550/arxiv.2502.09604
Self-citation
Metadata
- Authors
- Shi, W., Han, X., Lewis, M., Tsvetkov, Y., Zettlemoyer, L., & Yih, W.-T.
- Venue
- Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
- Published
- 2024
- Pages
- 783-791
- Cited by
- 83
- References
- 0
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