2 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CV2025★ 2 cited
Thinking With Videos: Multimodal Tool-Augmented Reinforcement Learning for Long Video Reasoning
Haoji Zhang, Xin Gu, Jiawen Li +7
The video reasoning ability of multimodal large language models (MLLMs) is crucial for downstream tasks like video question answering and temporal grounding. While recent approache…
cs.CV2025
Stepping Out of Similar Semantic Space for Open-Vocabulary Segmentation
Yong Liu, SongLi Wu, Sule Bai +3
Open-vocabulary segmentation aims to achieve segmentation of arbitrary categories given unlimited text inputs as guidance. To achieve this, recent works have focused on developing…
cs.CV2025★ 1 cited
UniVG-R1: Reasoning Guided Universal Visual Grounding with Reinforcement Learning
Sule Bai, Mingxing Li, Yong Liu +5
Traditional visual grounding methods primarily focus on single-image scenarios with simple textual references. However, extending these methods to real-world scenarios that involve…