25 citations · 53 across the 23 of their papers we have counts for
7 papers · 1 filter
Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel
Zun Wang, Jialu Li, Yicong Hong +8
Creating high-quality data for training robust language-instructed agents is a long-lasting challenge in embodied AI. In this paper, we introduce a Self-Refining Data Flywheel (SRD…
Motion-Grounded Video Reasoning: Understanding and Perceiving Motion at Pixel Level
Andong Deng, Tongjia Chen, Shoubin Yu +6
In this paper, we introduce Motion-Grounded Video Reasoning, a new motion understanding task that requires generating visual answers (video segmentation masks) according to the inp…
SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation
Jaehong Yoon, Shoubin Yu, Vaidehi Patil +2
Recent advances in diffusion models have significantly enhanced their ability to generate high-quality images and videos, but they have also increased the risk of producing unsafe…
STAR: A Benchmark for Situated Reasoning in Real-World Videos
Bo Wu, Shoubin Yu, Zhenfang Chen +2
Reasoning in the real world is not divorced from situations. How to capture the present knowledge from surrounding situations and perform reasoning accordingly is crucial and chall…
VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos
Ziyang Wang, Shoubin Yu, Elias Stengel-Eskin +4
Long-form video understanding is complicated by the high redundancy of video data and the abundance of query-irrelevant information. To tackle these challenges, we propose VideoTre…
RACCooN: A Versatile Instructional Video Editing Framework with Auto-Generated Narratives
Jaehong Yoon, Shoubin Yu, Mohit Bansal
Recent video generative models primarily rely on carefully written text prompts for specific tasks, like inpainting or style editing. They require labor-intensive textual descripti…
CREMA: Generalizable and Efficient Video-Language Reasoning via Multimodal Modular Fusion
Shoubin Yu, Jaehong Yoon, Mohit Bansal
Despite impressive advancements in recent multimodal reasoning approaches, they are still limited in flexibility and efficiency, as these models typically process only a few fixed…