activity
20242026
collaborators

7 papers

cs.CV2026

Common Objects Out of Context (COOCo): Investigating Multimodal Context and Semantic Scene Violations in Referential Communication

Filippo Merlo, Ece Takmaz, Wenkai Chen +1

To what degree and under what conditions do VLMs rely on scene context when generating references to objects? To address this question, we introduce the $\textit{Common Objects Out…

cs.CL2025

References Matter: Investigating the Impact of Reference Set Variation on Summarization Evaluation

Silvia Casola, Yang Janet Liu, Siyao Peng +3

Human language production exhibits remarkable richness and variation, reflecting diverse communication styles and intents. However, this variation is often overlooked in summarizat…

cs.CL2025

VAQUUM: Are Vague Quantifiers Grounded in Visual Data?

Hugh Mee Wong, Rick Nouwen, Albert Gatt

Vague quantifiers such as "a few" and "many" are influenced by various contextual factors, including the number of objects present in a given context. In this work, we evaluate the…

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

FTFT: Efficient and Robust Fine-Tuning by Transferring Training Dynamics

Yupei Du, Albert Gatt, Dong Nguyen

Despite the massive success of fine-tuning Pre-trained Language Models (PLMs), they remain susceptible to out-of-distribution input. Dataset cartography is a simple yet effective d…

cs.CL2024

A Systematic Analysis of Large Language Models as Soft Reasoners: The Case of Syllogistic Inferences

Leonardo Bertolazzi, Albert Gatt, Raffaella Bernardi

The reasoning abilities of Large Language Models (LLMs) are becoming a central focus of study in NLP. In this paper, we consider the case of syllogistic reasoning, an area of deduc…