arXiv AI July 17, 2026 By Qicheng Zhao, Qi Sun, Zheyu Yan

Seeing the End at Step Zero: Accelerating Diffusion MLLMs via MLP Sparsity-Aware Truncation

arXiv:2607. 14557v1 Announce Type: new Abstract: Diffusion Multimodal Large Language Models (DMLLMs) are highly effective for multimodal reasoning, yet their inference efficiency is significantly hindered by fixed-length generation constraints.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jun 15

Residual Context Diffusion Language Models

arXiv:2601. 22954v2 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to purely autoregressive language models because they can decode multiple tokens in parallel.

By Yuezhou Hu, Harman Singh, Monishwaran Maheswaran, Haocheng Xi, Coleman Hooper, Jintao Zhang, Aditya Tomar, Michael W. Mahoney, Sewon Min, Mehrdad Farajtabar, Kurt Keutzer, Amir Gholami, Chenfeng Xu

llms diffusion benchmarks

arXiv Machine Learning

Jun 5

A Survey on Diffusion Language Models

arXiv:2508. 10875v3 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) are rapidly emerging as a powerful and promising alternative to the dominant autoregressive (AR) paradigm.

By Tianyi Li, Mingda Chen, Bowei Guo, Zhiqiang Shen

llms diffusion nlp efficiency multimodal benchmarks

arXiv AI

Sep 16

VideoMM: Adaptive Macro-Micro Inference for Efficient Video MLLMs

arXiv:2609.16722v1 Announce Type: new Abstract: Scaling Multimodal Large Language Models (MLLMs) to long-form video understanding is bottlenecked by the explosion of visual tokens, which saturates co...

By Haoyu Guo, Yuan Feng, Junlin Lv, Mingjun Xiao, S Kevin Zhou, Xike Xie

llms multimodal

arXiv Computer Vision

Sep 1

Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding

arXiv:2505.16990v3 Announce Type: replace Abstract: In this work, we propose Dimple, the first Discrete Diffusion Multimodal Large Language Model (DMLLM). We observe that training with a purely discr...

By Runpeng Yu, Xinyin Ma, Xinchao Wang

llms diffusion multimodal benchmarks safety

arXiv Machine Learning

Jun 11

Visual-Redundancy-Controlled Parallel Decoding for Diffusion-Based Multimodal Large Language Models

arXiv:2605. 25820v2 Announce Type: replace Abstract: Diffusion-based multimodal large language models (dMLLMs) decode by iteratively predicting tokens at multiple masked positions in parallel.

By Yulin Yuan, Hongshuo Zhao, Xiangming Meng

llms diffusion multimodal benchmarks

Hugging Face Trending Papers

Sep 15

VideoMM: Adaptive Macro-Micro Inference for Efficient Video MLLMs

Scaling Multimodal Large Language Models (MLLMs) to long-form video understanding is bottlenecked by the explosion of visual tokens, which saturates context windows and incurs prohibitive costs. Curre...

llms multimodal

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Residual Context Diffusion Language Models

A Survey on Diffusion Language Models

VideoMM: Adaptive Macro-Micro Inference for Efficient Video MLLMs

Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding

Visual-Redundancy-Controlled Parallel Decoding for Diffusion-Based Multimodal Large Language Models

VideoMM: Adaptive Macro-Micro Inference for Efficient Video MLLMs