activity
20182025
most citedAbusive Language Detection with Graph Convolutional Networks

46 citations · 70 across the 7 of their papers we have counts for

collaborators

12 papers

cs.CL2025

From Tools to Teammates: Evaluating LLMs in Multi-Session Coding Interactions

Nathanaël Carraz Rakotonirina, Mohammed Hamdy, Jon Ander Campos +5

Large Language Models (LLMs) are increasingly used in working environments for a wide range of tasks, excelling at solving individual problems in isolation. However, are they also…

cs.CL2022★ 6 cited

Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey

Xiaoyu Shen, Svitlana Vakulenko, Marco del Tredici +3

Dense retrieval (DR) approaches based on powerful pre-trained language models (PLMs) achieved significant advances and have become a key component for modern open-domain question-a…

cs.CL2022★ 1 cited

From Rewriting to Remembering: Common Ground for Conversational QA Models

Marco Del Tredici, Xiaoyu Shen, Gianni Barlacchi +2

In conversational QA, models have to leverage information in previous turns to answer upcoming questions. Current approaches, such as Question Rewriting, struggle to extract releva…

cs.CL2020

Words are the Window to the Soul: Language-based User Representations for Fake News Detection

Marco Del Tredici, Raquel Fernández

Cognitive and social traits of individuals are reflected in language use. Moreover, individuals who are prone to spread fake news online often share common traits. Building on thes…

cs.CL2020

Analysing Lexical Semantic Change with Contextualised Word Representations

Mario Giulianelli, Marco Del Tredici, Raquel Fernández

This paper presents the first unsupervised approach to lexical semantic change that makes use of contextualised word representations. We propose a novel method that exploits the BE…

cs.CL2019

You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP

Marco Del Tredici, Diego Marcheggiani, Sabine Schulte im Walde +1

Information about individuals can help to better understand what they say, particularly in social media where texts are short. Current approaches to modelling social media users pa…