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Vittorio Mazzia

4 accepted papers

2025

Detecting and Mitigating Challenges in Zero-Shot Video Summarization with Video LLMs

ACL 2025finding

Video summarization aims to generate a condensed textual version of an original video. Summaries may consist of either plain text or a shortlist of salient events, possibly including temporal or spatial references. Video Large Language Models (VLLMs) exhibit impressive zero-shot capabilities in vide…

2025

MASSIVE-Agents: A Benchmark for Multilingual Function-Calling in 52 Languages

EMNLP 2025

We present MASSIVE-Agents, a new benchmark for assessing multilingual function calling across 52 languages. We created MASSIVE-Agents by cleaning the original MASSIVE dataset and then reformatting it for evaluation within the Berkeley Function-Calling Leaderboard (BFCL) framework. The full benchmark

2023

Exploring Subgroup Performance in End-to-End Speech Models

ICASSP 2023accepted

End-to-End Spoken Language Understanding models are generally evaluated according to their overall accuracy, or separately on (a priori defined) data subgroups of interest. We propose a technique for analyzing model performance at the subgroup level, which considers all subgroups that can be defined…

Cited by 0Source ↗Scholar ↗
2021

Deep Semantic Segmentation at the Edge for Autonomous Navigation in Vineyard Rows

IROS 2021poster

Precision agriculture is a fast-growing field that aims at introducing affordable and effective automation into agricultural processes. Nowadays, algorithmic solutions for navigation in vineyards require expensive sensors and high computational workloads that preclude large-scale applicability of au…

Cited by 38Source ↗code ↗Scholar ↗