Papers with token-level correctness

1 papers
SelFusion: Self-distillation for Diffusion Language Models (2026.acl-long)

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Challenge: Existing knowledge distillation methods for autoregressive large language models (LLMs) are not effective for reducing generation quality, but they can be useful for real-time applications.
Approach: They propose a self-distillation framework that allows for effective KD without external teacher . they propose to use two modes of knowledge distillation to determine distillation direction .
Outcome: The proposed framework outperforms existing methods with external teachers on instruction-following tasks.

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