activity
20242026
collaborators

5 papers

cs.CV2026

Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Contextually Important Moments

Aditya K Surikuchi, Raquel Fernández, Sandro Pezzelle

Foundation models are used for many real-world applications involving language generation from temporally-ordered multimodal events. In this work, we study the ability of models to…

cs.CL2026

Vision-Language Models Align with Human Neural Representations in Concept Processing

Anna Bavaresco, Marianne de Heer Kloots, Sandro Pezzelle +1

Recent studies suggest that transformer-based vision-language models (VLMs) capture the multimodality of concept processing in the human brain. However, a systematic evaluation exp…

cs.CL2025

Natural Language Generation from Visual Events: State-of-the-Art and Key Open Questions

Aditya K Surikuchi, Raquel Fernández, Sandro Pezzelle

In recent years, a substantial body of work in visually grounded natural language processing has focused on real-life multimodal scenarios such as describing content depicted in im…

cs.CL2025

LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks

Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi +17

There is an increasing trend towards evaluating NLP models with LLMs instead of human judgments, raising questions about the validity of these evaluations, as well as their reprodu…

cs.CL2024

Not (yet) the whole story: Evaluating Visual Storytelling Requires More than Measuring Coherence, Grounding, and Repetition

Aditya K Surikuchi, Raquel Fernández, Sandro Pezzelle

Visual storytelling consists in generating a natural language story given a temporally ordered sequence of images. This task is not only challenging for models, but also very diffi…