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20242026
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cs.CV2025

Reinforcement Learning for Large Model: A Survey

Weijia Wu, Chen Gao, Joya Chen +6

Recent advances at the intersection of reinforcement learning (RL) and visual intelligence have enabled agents that not only perceive complex visual scenes but also reason, generat…

cs.CV2025

Seed1.5-VL Technical Report

Dong Guo, Faming Wu, Feida Zhu +194

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…

cs.CV2025

LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale

Joya Chen, Ziyun Zeng, Yiqi Lin +3

Recent video large language models (Video LLMs) often depend on costly human annotations or proprietary model APIs (e.g., GPT-4o) to produce training data, which limits their train…

cs.CV2024

One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

Zechen Bai, Tong He, Haiyang Mei +6

We introduce VideoLISA, a video-based multimodal large language model designed to tackle the problem of language-instructed reasoning segmentation in videos. Leveraging the reasoni…

cs.CV2024

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98

We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…

cs.CV2024

Learning Video Context as Interleaved Multimodal Sequences

Kevin Qinghong Lin, Pengchuan Zhang, Difei Gao +6

Narrative videos, such as movies, pose significant challenges in video understanding due to their rich contexts (characters, dialogues, storylines) and diverse demands (identify wh…