works on

From the 1 of 16 linked papers with an AI index.

collaborators

16 papers

cs.IR2026

MemoryCPT: An End-to-End Agent Memory Framework for Cost-Performance Trade-off

Songxin Lei, Kun Ouyang, Weilin Ruan +4

Long-horizon LLM agents require memory systems that recover useful evidence from large interaction histories without passing excessive context to downstream models. Existing memory…

cs.CV2026

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding

Xinhao Li, Yuhan Zhu, Xiangyu Zeng +24

VideoChat3 is a fully open, 4B-parameter video-centric multimodal large language model that combines an efficient Inflated 3D Vision Transformer and adaptive frame resolution with…

cs.CV2026

TimeChat-Captioner: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions

Linli Yao, Yuancheng Wei, Yaojie Zhang +12

This paper proposes Omni Dense Captioning, a novel task designed to generate continuous, fine-grained, and structured audio-visual narratives with explicit timestamps. To ensure de…

cs.CV2026

Thinking Without Images: Internalizing Visual Manipulation with On-Policy Self-Distillation

Yishuo Cai, Jiahui Liu, Yuanxin Liu +9

''Thinking with Images'' has emerged as an effective paradigm for fine-grained visual reasoning: by explicitly zooming into relevant regions and reasoning over crops, models can ac…

cs.CV2026

Video-o3: Native Interleaved Clue Seeking for Long Video Multi-Hop Reasoning

Xiangyu Zeng, Zhiqiu Zhang, Yuhan Zhu +12

Existing multimodal large language models for long-video understanding predominantly rely on uniform sampling and single-turn inference, limiting their ability to identify sparse y…

cs.CV2026

VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?

Yuanxin Liu, Kun Ouyang, Haoning Wu +7

Recent studies have shown that long chain-of-thought (CoT) reasoning can significantly enhance the performance of large language models (LLMs) on complex tasks. However, this benef…