activity
20232026
collaborators

8 papers

cs.CL2026

LLM-as-a-Demographic: Whom Sociodemographic Prompting Helps, and Whom It Hurts

Daniela Occhipinti, Andrea Piergentili, Marco Guerini

Large language models (LLMs) are increasingly used as judges for subjective tasks, where annotators disagree and the relevant question is not only how accurate a judge is, but whos…

cs.CL2026

Stranger, Fan, or Peer? A Systematic Study on the Role of Interlocutor in Persona-Based Dialogue Generation

Daniela Occhipinti, Malvina Nissim, Marco Guerini

Persona-based dialogue systems are usually conditioned on speaker biography, but dialogues involve at least two participants, and who has access to whose biography can vary across…

cs.CL2026

CATCH-ME if you RAG: a dataset of Contextually Annotated multi-Turn Counterspeech against Hate and Misinformation Exchanges

Helena Bonaldi, Genoveffa Martone, Marco Guerini

Online hate speech and misinformation frequently overlap, yet NLP research has mainly treated them in isolation. While LLMs represent a scalable solution for assisting humans in th…

cs.CL2026

Guide Me Out: A Framework to Benchmark VLM Operators Communication in Crisis Scenarios

Giacomo Gonella, Stefano Menini, Marco Guerini

Effective crisis response requires spatially grounded communication that bridges linguistic guidance of civilians with the physical environment, accounting for structural bottlenec…

cs.CL2026

Assisted Counterspeech Writing at the Crossroads of Hate Speech and Misinformation

Genoveffa Martone, Helena Bonaldi, Marco Guerini

Hate speech and misinformation frequently co-occur online, amplifying prejudice and polarization. Given their scale, using Large Language Models (LLMs) to assist expert counterspee…

cs.CL2025

When Harry Meets Superman: The Role of The Interlocutor in Persona-Based Dialogue Generation

Daniela Occhipinti, Marco Guerini, Malvina Nissim

Endowing dialogue agents with persona information has proven to significantly improve the consistency and diversity of their generations. While much focus has been placed on aligni…

cs.CL2024

Fine-tuning with HED-IT: The impact of human post-editing for dialogical language models

Daniela Occhipinti, Michele Marchi, Irene Mondella +4

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 th…

cs.CL2023

PRODIGy: a PROfile-based DIalogue Generation dataset

Daniela Occhipinti, Serra Sinem Tekiroglu, Marco Guerini

Providing dialogue agents with a profile representation can improve their consistency and coherence, leading to better conversations. However, current profile-based dialogue datase…