Papers with decoding-time strategies

2 papers
Adaptive Weighted Proxy Tuning: Efficient Gray-Box Steering for Image Captioning. (2026.acl-industry)

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Challenge: Proxy tuning is a decoding-time approach that fails to account for instance-specific variations in model certainty and domain shift.
Approach: They propose a gray-box steering framework that dynamically modulates the logit contributions of a large base model, a fine-tuned expert, and an untune .
Outcome: Adaptive Weighted Proxy Tuning achieves performance parity with fine-tuned models while remaining parameter-free.
Comparison of Diverse Decoding Methods from Conditional Language Models (P19-1)

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Challenge: Conditional language models can generate a diverse set of outputs, but for open-ended tasks, beam search is ill-suited to generating a set of diverse sequences.
Approach: They propose a method where we over-sample candidates and use clustering to remove similar sequences to achieve high diversity without sacrificing quality.
Outcome: The proposed method over-samples candidates and removes similar sequences to achieve high diversity without sacrificing quality.

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