4 papers
Diffusion LLM with Native Variable Generation Lengths: Let [EOS] Lead the Way
Yicun Yang, Cong Wang, Shaobo Wang +4
Diffusion-based large language models (dLLMs) have exhibited substantial potential for parallel text generation, which may enable more efficient generation compared to autoregressi…
Mask Tokens as Prophet: Fine-Grained Cache Eviction for Efficient dLLM Inference
Jianuo Huang, Yaojie Zhang, Yicun Yang +4
Diffusion large language models (dLLMs) present a promising alternative to dominant autoregressive models (ARMs) by the ability of parallel decoding at the expense of substantial c…
dVLA: Diffusion Vision-Language-Action Model with Multimodal Chain-of-Thought
Junjie Wen, Minjie Zhu, Jiaming Liu +6
Vision-Language-Action (VLA) models are emerging as a next-generation paradigm for robotics. We introduce dVLA, a diffusion-based VLA that leverages a multimodal chain-of-thought t…
Dataset Distillation with Neural Characteristic Function: A Minmax Perspective
Shaobo Wang, Yicun Yang, Zhiyuan Liu +4
Dataset distillation has emerged as a powerful approach for reducing data requirements in deep learning. Among various methods, distribution matching-based approaches stand out for…