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Giuseppe Riccardi

7 accepted papers

2025

CIVET: Systematic Evaluation of Understanding in VLMs

EMNLP 2025

While Vision-Language Models (VLMs) have achieved competitive performance in various tasks, their comprehension of the underlying structure and semantics of a scene remains understudied. To investigate the understanding of VLMs, we study their capability regarding object properties and relations in

Cited by 0SourcePDFScholar
2024

DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs

EMNLP 2024finding

LLMs acquire knowledge from massive data snapshots collected at different timestamps. Their knowledge is then commonly evaluated using static benchmarks. However, factual knowledge is generally subject to time-sensitive changes, and static benchmarks cannot address those cases. We present an approac…

2024

Will LLMs Replace the Encoder-Only Models in Temporal Relation Classification?

EMNLP 2024main

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 promising performance in temporal reasoning tasks such as temporal question answering. Nevertheless, recent studies have t…

2017

A Deep Learning approach to modeling competitiveness in spoken conversations

ICASSP 2017accepted

The motivation behind the research on overlapping speech has always been dominated by the need to model human-machine interaction for dialog systems and conversation analysis. To have more complex insights of the interlocutors' intentions behind the interaction, we need to understand the type of ove…

Cited by 0SourceScholar
2017

A cross-modal adaptation approach for brain decoding

ICASSP 2017accepted

Brain decoding has become a hot topic in many recent brain studies. In a typical neuroimaging experiment, participants are presented with different categories of stimuli while their concurrent brain activity is recorded. Then a classifier is trained on the features extracted from the recorded brain…

Cited by 0SourceScholar
2016

Discourse connective detection in spoken conversations

ICASSP 2016accepted

Discourse parsing is an important task in Language Understanding with applications to human-human and human-machine communication modeling. However, most of the research has focused on written text, and parsers heavily rely on syntactic parsers that themselves have low performance on dialog data. In…

Cited by 0SourceScholar
2015

Annotating and categorizing competition in overlap speech

ICASSP 2015accepted

Overlapping speech is a common and relevant phenomenon in human conversations, reflecting many aspects of discourse dynamics. In this paper, we focus on the pragmatic role of overlaps in turn-in-progress, where it can be categorized as competitive or non-competitive. Previous studies on these two ca…

Cited by 0SourceScholar