Top-n𝜎: Eliminating Noise in Logit Space for Robust Token Sampling of LLM (2025.acl-long)
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| Challenge: | Existing sampling methods that are sensitive to temperature scaling fail to distinguish between diversity and noise. |
| Approach: | They propose a method that identifies informative tokens by eliminating noise directly in logit space and a new sampling method that is temperature-invariant. |
| Outcome: | The proposed method outperforms existing methods with significant improvements in reasoning and creative writing tasks. |
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Yuanhao Ding, Meimingwei Li, Esteban Garces Arias, Matthias Aßenmacher, Christian Heumann, Chongsheng Zhang
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