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PACE-dLLM is proposed, which fits this parametric cliff in closed form at each step, sets the next horizon by its saturation point, and uses an independent confidence threshold for token commitment, and achieves the best average accuracy on both open-source dLLM backbones.
Prefix-Conditioned Diffusion (PCD), which samples a boundary, preserves the prefix, preserves the prefix, and denoises the suffix, is proposed, and improvements in reasoning and coding over native diffusion training are shown.
WorldCycle is introduced, a self-verifiable RL framework that constructs closed action cycles and their repeated executions from ordinary action sequences, and optimizes two complementary rewards: a spatial closure reward enforcing symmetry between mirrored forward and reverse segments, and a temporal consistency rewar...
This work proposes OPTD, On-Policy Transition Distillation with consistency-guided adaptive compression, which consistently improves the quality--efficiency trade-off and attains the strongest overall quality-constrained AUP among the evaluated few-step baselines.
This work proposes Progressively Disentangled and Recurrent Prompt Tuning (PDRPT), an edge-efficient framework that decouples object and state updates before joint refinement, suppresses traction force from highly-entangled prompts, and preserves alignment with the natural language space of CLIP.
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