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cs.CV2025
A Comprehensive Study on Visual Token Redundancy for Discrete Diffusion-based Multimodal Large Language Models
Duo Li, Zuhao Yang, Xiaoqin Zhang +2
Discrete diffusion-based multimodal large language models (dMLLMs) have emerged as a promising alternative to autoregressive MLLMs thanks to their advantages in parallel decoding a…
cs.CV2025
ToDRE: Effective Visual Token Pruning via Token Diversity and Task Relevance
Duo Li, Zuhao Yang, Xiaoqin Zhang +2
Visual token pruning, which aims to compress and prune redundant visual tokens, plays a critical role in efficient inference with large vision-language models (LVLMs). However, exi…
cs.DC2025★ 1 cited
DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training
Masahiro Tanaka, Du Li, Umesh Chand +3
The rapid growth of deep learning models has increased the demand for efficient distributed training strategies. Fully sharded approaches like ZeRO-3 and FSDP partition model param…