6 papers
What's the Catch? Evaluating Temporal Consistency in Vision-Language Models
Marek Hradil, Danae Sánchez Villegas
Vision-language models (VLMs) achieve strong performance on video and image-sequence benchmarks, yet it remains unclear whether they capture temporal structure. To study this quest…
Reasoning Dynamics and the Limits of Monitoring Modality Reliance in Vision-Language Models
Danae Sánchez Villegas, Samuel Lewis-Lim, Nikolaos Aletras +1
Recent advances in vision language models (VLMs) offer reasoning capabilities, yet how these unfold and integrate visual and textual information remains unclear. We analyze reasoni…
Beyond Binary Classification: Detecting Fine-Grained Sexism in Social Media Videos
Laura De Grazia, Danae Sánchez Villegas, Desmond Elliott +2
Online sexism appears in various forms, which makes its detection challenging. Although automated tools can enhance the identification of sexist content, they are often restricted…
How Well Do Vision-Language Models Understand Movies?
Emmanouil Zaranis, António Farinhas, Saul Santos +28
Vision-language models (VLMs) can increasingly handle extended contexts and answer questions about long videos--but can they understand the narrative structure of movies as humans…
MuSeD: A Multimodal Spanish Dataset for Sexism Detection in Social Media Videos
Laura De Grazia, Pol Pastells, Mauro Vázquez Chas +4
Sexism is generally defined as prejudice and discrimination based on sex or gender, affecting every sector of society, from social institutions to relationships and individual beha…
ImageChain: Advancing Sequential Image-to-Text Reasoning in Multimodal Large Language Models
Danae Sánchez Villegas, Ingo Ziegler, Desmond Elliott
Reasoning over sequences of images remains a challenge for multimodal large language models (MLLMs). While recent models incorporate multi-image data during pre-training, they stil…