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From the 3 of 21 linked papers with an AI index.

most citedOmniVideo-R1: Reinforcing Audio-visual Reasoning with Query Intention and Modality Attention

1 citations · 2 across the 19 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

Evidence-RL: Towards Evidence-intensive Visual Reasoning

Haojie Huang, Xinlei Yu, Chengming Xu +6

Vision-Language Models (VLMs) should answer from concrete image evidence rather than language priors, dataset shortcuts, or irrelevant visual context. Existing perception-aware pos…

cs.CV2026

Beacon: Knowing When and How to Perform Agentic Visual Reasoning

Qixun Wang, Yang Shi, Letian Cheng +11

The paper introduces Beacon, an agentic visual reasoning system that learns when to invoke external tools and how to use them effectively, improving multimodal large language model…

cs.CV2026

RefCaptioner: Multi-Reference Image-Grounded Video Captioning

Tengfei Liu, Yang Shi, Yuran Wang +16

Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple reference images. We introduce multi-…

cs.CV2026

KeyFrame-Compass: Towards Comprehensive Evaluation of Keyframe-Conditioned Video Generation

Yuqi Tang, Tengfei Liu, Yizheng Lai +18

The paper introduces KeyFrame-Compass, a benchmark and evaluation framework for assessing how well video generation models follow supplied keyframes while preserving overall video…

cs.CV2026

Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models

Xiaomin Yu, Yi Xin, Yuhui Zhang +12

Despite the success of multimodal contrastive learning in aligning visual and linguistic representations, a persistent geometric anomaly, the Modality Gap, remains: embeddings of d…

cs.CV2026

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding

Zhangquan Chen, Manyuan Zhang, Xinlei Yu +9

Dynamic spatial reasoning from monocular video is essential for bridging visual intelligence and the physical world, yet remains challenging for vision-language models (VLMs). Prio…