no code implementations • 20 Dec 2017 • Ioannis Papaioannou, Amanda Cercas Curry, Jose L. Part, Igor Shalyminov, Xinnuo Xu, Yanchao Yu, Ondřej Dušek, Verena Rieser, Oliver Lemon
Open-domain social dialogue is one of the long-standing goals of Artificial Intelligence.
no code implementations • WS 2017 • Jekaterina Novikova, Christian Dondrup, Ioannis Papaioannou, Oliver Lemon
We find that happiness in the user's recognised facial expression strongly correlates with likeability of a robot, while dialogue-related features (such as number of human turns or number of sentences per robot utterance) correlate with perceiving a robot as intelligent.
no code implementations • 13 Sep 2019 • Christian Dondrup, Ioannis Papaioannou, Oliver Lemon
Smart speakers and robots become ever more prevalent in our daily lives.
no code implementations • 15 Sep 2019 • Mary Ellen Foster, Bart Craenen, Amol Deshmukh, Oliver Lemon, Emanuele Bastianelli, Christian Dondrup, Ioannis Papaioannou, Andrea Vanzo, Jean-Marc Odobez, Olivier Canévet, Yuanzhouhan Cao, Weipeng He, Angel Martínez-González, Petr Motlicek, Rémy Siegfried, Rachid Alami, Kathleen Belhassein, Guilhem Buisan, Aurélie Clodic, Amandine Mayima, Yoan Sallami, Guillaume Sarthou, Phani-Teja Singamaneni, Jules Waldhart, Alexandre Mazel, Maxime Caniot, Marketta Niemelä, Päivi Heikkilä, Hanna Lammi, Antti Tammela
In the EU-funded MuMMER project, we have developed a social robot designed to interact naturally and flexibly with users in public spaces such as a shopping mall.
no code implementations • 25 May 2023 • Sabrina Chiesurin, Dimitris Dimakopoulos, Marco Antonio Sobrevilla Cabezudo, Arash Eshghi, Ioannis Papaioannou, Verena Rieser, Ioannis Konstas
Large language models are known to produce output which sounds fluent and convincing, but is also often wrong, e. g. "unfaithful" with respect to a rationale as retrieved from a knowledge base.
Conversational Question Answering Open-Domain Question Answering
1 code implementation • 31 Jul 2023 • Vevake Balaraman, Arash Eshghi, Ioannis Konstas, Ioannis Papaioannou
We demonstrate the usefulness of the data by training and evaluating strong baseline models for executing TPRs.