From the 1 of 9 linked papers with an AI index.
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DIVE: Dynamic Iterative Visual Evidence Construction for Efficient Vision-Language Models
Chen Zhong, Xiao An, Zijie Wang +3
Visual inputs in vision-language models (VLMs) are often encoded into substantially longer token sequences than text, making visual tokens a major bottleneck for efficient inferenc…
Self-Consistent Latent Reasoning: Long Latent Sequence Reasoning for Vision-Language Model
Chenfeng Wang, Wei He, Xuhan Zhu +10
In language reasoning, longer chains of thought consistently yield better performance, which naturally suggests that visual latent reasoning may likewise benefit from longer latent…
SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models
Chen Zhong, Xiao An, Jiaxing Sun +3
Low-level visual perception underpins reliable remote sensing (RS) image analysis, yet current image quality assessment (IQA) methods output uninterpretable scalar scores rather th…
OmniEval: A Benchmark for Evaluating Omni-modal Models with Visual, Auditory, and Textual Inputs
Yiman Zhang, Ziheng Luo, Qiangyu Yan +4
In this paper, we introduce OmniEval, a benchmark for evaluating omni-modality models like MiniCPM-O 2.6, which encompasses visual, auditory, and textual inputs. Compared with exis…
Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMs
Kai Han, Jianyuan Guo, Yehui Tang +3
Vision-language large models have achieved remarkable success in various multi-modal tasks, yet applying them to video understanding remains challenging due to the inherent complex…