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cs.CV2025
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
Yang Shi, Jiaheng Liu, Yushuo Guan +12
Long-context video understanding in multimodal large language models (MLLMs) faces a critical challenge: balancing computational efficiency with the retention of fine-grained spati…
cs.CV2025
HAIC: Improving Human Action Understanding and Generation with Better Captions for Multi-modal Large Language Models
Xiao Wang, Jingyun Hua, Weihong Lin +5
Recent Multi-modal Large Language Models (MLLMs) have made great progress in video understanding. However, their performance on videos involving human actions is still limited by t…
cs.AI2025
VidCapBench: A Comprehensive Benchmark of Video Captioning for Controllable Text-to-Video Generation
Xinlong Chen, Yuanxing Zhang, Chongling Rao +7
The training of controllable text-to-video (T2V) models relies heavily on the alignment between videos and captions, yet little existing research connects video caption evaluation…