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cs.CV2026★ 1 cited
LADR: Locality-Aware Dynamic Rescue for Efficient Text-to-Image Generation with Diffusion Large Language Models
Chenglin Wang, Yucheng Zhou, Shawn Chen +2
Discrete Diffusion Language Models have emerged as a compelling paradigm for unified multimodal generation, yet their deployment is hindered by high inference latency arising from…
cs.CV2026
LFS: Learnable Frame Selector for Event-Aware and Temporally Diverse Video Captioning
Lianying Chao, Linfeng Yin, Peiyu Ren +8
Video captioning models convert frames into visual tokens and generate descriptions with large language models (LLMs). Since encoding all frames is prohibitively expensive, uniform…
cs.CV2026
Multi-Modal LLM based Image Captioning in ICT: Bridging the Gap Between General and Industry Domain
Lianying Chao, Kai Zhang, Haoran Cai +3
In the information and communications technology (ICT) industry, training a domain-specific large language model (LLM) or constructing a retrieval-augmented generation system requi…