4 citations · 6 across the 10 of their papers we have counts for
10 papers
Positional task conditioning for scalable defect detection across product families in large product catalogs
Soham Satyadharma, Gabriel Roccabruna, Suleiman A. Khan
Product families in large product catalogs suffer from inconsistencies such as duplicates and unit mismatches that degrade customer experience. Detecting these requires reasoning o…
MATEO: A Multimodal Benchmark for Temporal Reasoning and Planning in LVLMs
Gabriel Roccabruna, Olha Khomyn, Giuseppe Riccardi
AI agents need to plan to achieve complex goals that involve orchestrating perception, sub-goal decomposition, and execution. These plans consist of ordered steps structured accord…
[De|Re]constructing VLMs' Reasoning in Counting
Simone Alghisi, Gabriel Roccabruna, Massimo Rizzoli +2
Vision-Language Models (VLMs) have recently gained attention due to their competitive performance on multiple downstream tasks, achieved by following user-input instructions. Howev…
CIVET: Systematic Evaluation of Understanding in VLMs
Massimo Rizzoli, Simone Alghisi, Olha Khomyn +3
While Vision-Language Models (VLMs) have achieved competitive performance in various tasks, their comprehension of the underlying structure and semantics of a scene remains underst…
Will LLMs Replace the Encoder-Only Models in Temporal Relation Classification?
Gabriel Roccabruna, Massimo Rizzoli, Giuseppe Riccardi
The automatic detection of temporal relations among events has been mainly investigated with encoder-only models such as RoBERTa. Large Language Models (LLM) have recently shown pr…
Should We Fine-Tune or RAG? Evaluating Different Techniques to Adapt LLMs for Dialogue
Simone Alghisi, Massimo Rizzoli, Gabriel Roccabruna +2
We study the limitations of Large Language Models (LLMs) for the task of response generation in human-machine dialogue. Several techniques have been proposed in the literature for…
Are LLMs Robust for Spoken Dialogues?
Seyed Mahed Mousavi, Gabriel Roccabruna, Simone Alghisi +3
Large Pre-Trained Language Models have demonstrated state-of-the-art performance in different downstream tasks, including dialogue state tracking and end-to-end response generation…
Let's Give a Voice to Conversational Agents in Virtual Reality
Michele Yin, Gabriel Roccabruna, Abhinav Azad +1
The dialogue experience with conversational agents can be greatly enhanced with multimodal and immersive interactions in virtual reality. In this work, we present an open-source ar…
Understanding Emotion Valence is a Joint Deep Learning Task
Gabriel Roccabruna, Seyed Mahed Mousavi, Giuseppe Riccardi
The valence analysis of speakers' utterances or written posts helps to understand the activation and variations of the emotional state throughout the conversation. More recently, t…
Whats New? Identifying the Unfolding of New Events in Narratives
Seyed Mahed Mousavi, Shohei Tanaka, Gabriel Roccabruna +3
Narratives include a rich source of events unfolding over time and context. Automatic understanding of these events provides a summarised comprehension of the narrative for further…