10 papers
SVI-Bench: A Dynamic Microworld for Strategic Video Intelligence
Yulu Pan, Han Yi, Seongsu Ha +4
True video intelligence demands more than recognizing what is visible: it requires reasoning about why events unfold, predicting what would change under different conditions, and d…
Video-RTS: Rethinking Reinforcement Learning and Test-Time Scaling for Efficient and Enhanced Video Reasoning
Ziyang Wang, Jaehong Yoon, Shoubin Yu +3
Despite advances in reinforcement learning (RL)-based video reasoning with large language models (LLMs), data collection and fine-tuning remain significant challenges. These method…
BIMBA: Selective-Scan Compression for Long-Range Video Question Answering
Md Mohaiminul Islam, Tushar Nagarajan, Huiyu Wang +2
Video Question Answering (VQA) in long videos poses the key challenge of extracting relevant information and modeling long-range dependencies from many redundant frames. The self-a…
TimeRefine: Temporal Grounding with Time Refining Video LLM
Xizi Wang, Feng Cheng, Ziyang Wang +6
Video temporal grounding aims to localize relevant temporal boundaries in a video given a textual prompt. Recent work has focused on enabling Video LLMs to perform video temporal g…
ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos
Tanveer Hannan, Md Mohaiminul Islam, Jindong Gu +2
Large language models (LLMs) excel at retrieving information from lengthy text, but their vision-language counterparts (VLMs) face difficulties with hour-long videos, especially fo…
A Simple LLM Framework for Long-Range Video Question-Answering
Ce Zhang, Taixi Lu, Md Mohaiminul Islam +4
We present LLoVi, a language-based framework for long-range video question-answering (LVQA). Unlike prior long-range video understanding methods, which are often costly and require…