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pro vyhledávání: '"A, Guerini"'
Natural Language Processing and Generation systems have recently shown the potential to complement and streamline the costly and time-consuming job of professional fact-checkers. In this work, we lift several constraints of current state-of-the-art p
Externí odkaz:
http://arxiv.org/abs/2412.15189
Autor:
Campedelli, Gian Maria, Penzo, Nicolò, Stefan, Massimo, Dessì, Roberto, Guerini, Marco, Lepri, Bruno, Staiano, Jacopo
As Large Language Model (LLM)-based agents become increasingly autonomous and will more freely interact with each other, studying interactions between them becomes crucial to anticipate emergent phenomena and potential risks. Drawing inspiration from
Externí odkaz:
http://arxiv.org/abs/2410.07109
Autor:
Bonaldi, Helena, Damo, Greta, Ocampo, Nicolás Benjamín, Cabrio, Elena, Villata, Serena, Guerini, Marco
The potential effectiveness of counterspeech as a hate speech mitigation strategy is attracting increasing interest in the NLG research community, particularly towards the task of automatically producing it. However, automatically generated responses
Externí odkaz:
http://arxiv.org/abs/2410.03466
Assessing the performance of systems to classify Multi-Party Conversations (MPC) is challenging due to the interconnection between linguistic and structural characteristics of conversations. Conventional evaluation methods often overlook variances in
Externí odkaz:
http://arxiv.org/abs/2409.18602
Autor:
Occhipinti, Daniela, Marchi, Michele, Mondella, Irene, Lai, Huiyuan, Dell'Orletta, Felice, Nissim, Malvina, Guerini, Marco
Automatic methods for generating and gathering linguistic data have proven effective for fine-tuning Language Models (LMs) in languages less resourced than English. Still, while there has been emphasis on data quantity, less attention has been given
Externí odkaz:
http://arxiv.org/abs/2406.07288
In recent years, counterspeech has emerged as one of the most promising strategies to fight online hate. These non-escalatory responses tackle online abuse while preserving the freedom of speech of the users, and can have a tangible impact in reducin
Externí odkaz:
http://arxiv.org/abs/2403.20103
Counter Narratives (CNs) are non-negative textual responses to Hate Speech (HS) aiming at defusing online hatred and mitigating its spreading across media. Despite the recent increase in HS content posted online, research on automatic CN generation h
Externí odkaz:
http://arxiv.org/abs/2403.09159
In the present work, we obtain the hydrostatic equilibrium configurations of neutron stars in the recently proposed $f(R,\mathcal{L},T)$ theory of gravity, for which $R$ is the Ricci scalar, $\mathcal{L}$ is the matter lagrangian density, $T$ is the
Externí odkaz:
http://arxiv.org/abs/2402.15395
Current text classification approaches usually focus on the content to be classified. Contextual aspects (both linguistic and extra-linguistic) are usually neglected, even in tasks based on online discussions. Still in many cases the multi-party and
Externí odkaz:
http://arxiv.org/abs/2402.02975
The proliferation of misinformation on social media platforms (SMPs) poses a significant danger to public health, social cohesion and ultimately democracy. Previous research has shown how social correction can be an effective way to curb misinformati
Externí odkaz:
http://arxiv.org/abs/2311.10587