Papers by Yuling Xi

1 papers
Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration (2026.acl-long)

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Challenge: Non-sequential and bidirectional nature of diffusion large language models makes direct likelihood-based self-evaluation challenging.
Approach: They propose a self-evaluation confidence quantification method for diffusion large language models that quantifies confidence by computing the probability of regenerating tokens in the entire generated sequence, given the full context.
Outcome: The proposed method is correlated with semantic coherence and answer accuracy.

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