GeoDe constructs a truth hyperplane with linear probes and uses geometric distance as a confidence signal to filter gray zone samples during fine-tuning, leading to better truthfulness and OOD generalization in LLMs.
InProceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 18199–18224, Miami, Florida, USA
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Purging the Gray Zone: Latent-Geometric Denoising for Precise Knowledge Boundary Awareness
GeoDe constructs a truth hyperplane with linear probes and uses geometric distance as a confidence signal to filter gray zone samples during fine-tuning, leading to better truthfulness and OOD generalization in LLMs.