collaborators

19 papers

cs.CV2026

When to Think and When to Look: Uncertainty-Guided Lookback

Jing Bi, Filippos Bellos, Junjia Guo +8

Test-time thinking (that is, generating explicit intermediate reasoning chains) is known to boost performance in large language models and has recently shown strong gains for large…

cs.CV2025

MMPerspective: Do MLLMs Understand Perspective? A Comprehensive Benchmark for Perspective Perception, Reasoning, and Robustness

Yolo Y. Tang, Pinxin Liu, Zhangyun Tan +11

Understanding perspective is fundamental to human visual perception, yet the extent to which multimodal large language models (MLLMs) internalize perspective geometry remains uncle…

cs.CL2025

Why Reasoning Matters? A Survey of Advancements in Multimodal Reasoning (v1)

Jing Bi, Susan Liang, Xiaofei Zhou +16

Reasoning is central to human intelligence, enabling structured problem-solving across diverse tasks. Recent advances in large language models (LLMs) have greatly enhanced their re…

cs.CV2025

Generative AI for Cel-Animation: A Survey

Yolo Y. Tang, Junjia Guo, Pinxin Liu +14

Traditional Celluloid (Cel) Animation production pipeline encompasses multiple essential steps, including storyboarding, layout design, keyframe animation, inbetweening, and colori…

cs.CV2025

VidComposition: Can MLLMs Analyze Compositions in Compiled Videos?

Yolo Y. Tang, Junjia Guo, Hang Hua +9

The advancement of Multimodal Large Language Models (MLLMs) has enabled significant progress in multimodal understanding, expanding their capacity to analyze video content. However…

cs.CV2025

Video Understanding with Large Language Models: A Survey

Yolo Y. Tang, Jing Bi, Siting Xu +17

With the burgeoning growth of online video platforms and the escalating volume of video content, the demand for proficient video understanding tools has intensified markedly. Given…