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cs.CV2026

A Skill-augmented Agentic Framework and Benchmark for Multi-Video Understanding

Yue Zhang, Liqiang Jing, Jia Li +4

Multimodal Large Language Models have achieved strong performance in single-video understanding, yet their ability to reason across multiple videos remains limited. Existing approa…

cs.CV2026

Towards Spatio-Temporal World Scene Graph Generation from Monocular Videos

Rohith Peddi, Saurabh, Shravan Shanmugam +4

Spatio-temporal scene graphs provide a principled representation for modeling evolving object interactions, yet existing methods remain fundamentally frame-centric: they reason onl…

cs.CV2025

Can Video Large Multimodal Models Think Like Doubters-or Double-Down: A Study on Defeasible Video Entailment

Yue Zhang, Jilei Sun, Yunhui Guo +1

Video Large Multimodal Models (VLMMs) have made impressive strides in understanding video content, but they often struggle with abstract and adaptive reasoning-the ability to revis…

cs.CV2025

Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation

Rohith Peddi, Saurabh, Ayush Abhay Shrivastava +2

Spatio-Temporal Scene Graphs (STSGs) provide a concise and expressive representation of dynamic scenes by modeling objects and their evolving relationships over time. However, real…

cs.CV2025

Defeasible Visual Entailment: Benchmark, Evaluator, and Reward-Driven Optimization

Yue Zhang, Liqiang Jing, Vibhav Gogate

We introduce a new task called Defeasible Visual Entailment (DVE), where the goal is to allow the modification of the entailment relationship between an image premise and a text hy…

cs.CV2024

CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities

Rohith Peddi, Shivvrat Arya, Bharath Challa +10

Following step-by-step procedures is an essential component of various activities carried out by individuals in their daily lives. These procedures serve as a guiding framework tha…