5 papers
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…
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…
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…
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…
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…