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diffusion vision-language models

model1 events
papersSEP 12 04:00 UTC

Trajectory-Aware Decoding Control for Diffusion Vision-Language Models

A new arXiv paper proposes a decoding-control method for diffusion vision-language models that uses intermediate answer trajectories to decide how much reasoning a query actually needs. The approach targets a mismatch in which models apply reasoning effort that does not match the difficulty of the task, aiming to make inference more efficient and better calibrated. The work is presented as a preprint and has not yet been peer reviewed.