8 citations · 18 across the 16 of their papers we have counts for
5 papers · 1 filter
Seeing or Knowing? Visual Context Sensitivity in Multimodal Large Language Models
Jiaang Li, Chengzu Li, Zhaochong An +4
Multimodal Large Language Models (MLLMs) achieve strong performance by integrating visual inputs with the rich priors of pretrained language models. However, they often fail on vis…
Video Understanding: From Geometry and Semantics to Unified Models
Zhaochong An, Zirui Li, Mingqiao Ye +9
Video understanding aims to enable models to perceive, reason about, and interact with the dynamic visual world. In contrast to image understanding, video understanding inherently…
Evaluation of Cultural Competence of Vision-Language Models
Srishti Yadav, Lauren Tilton, Maria Antoniak +10
Modern vision-language models (VLMs) often fail at cultural competency evaluations and benchmarks. Given the diversity of applications built upon VLMs, there is renewed interest in…
RAVENEA: A Benchmark for Multimodal Retrieval-Augmented Visual Culture Understanding
Jiaang Li, Yifei Yuan, Wenyan Li +8
As vision-language models (VLMs) become increasingly integrated into daily life, the need for accurate visual culture understanding is becoming critical. Yet, these models frequent…
Understanding Retrieval Robustness for Retrieval-Augmented Image Captioning
Wenyan Li, Jiaang Li, Rita Ramos +2
Recent advances in retrieval-augmented models for image captioning highlight the benefit of retrieving related captions for efficient, lightweight models with strong domain-transfe…