Fine-tuning on Clean Data for End-to-End Speech Translation: FBK @ IWSLT 2018. - Mattia Antonino Di Gangi; Roberto Dessì; Roldano Cattoni; Matteo Negri; Marco Turchi (IWSLT, 2018)

CNNs found to jump around more skillfully than RNNs: Compositional Generalization in Seq2seq Convolutional Networks. - Roberto Dessì; Marco Baroni (ACL (1), 2019)

Enhancing Transformer for End-to-end Speech-to-Text Translation. - Mattia Antonino Di Gangi; Matteo Negri; Roldano Cattoni; Roberto Dessì; Marco Turchi (MTSummit (1), 2019)

Focus on What's Informative and Ignore What's not: Communication Strategies in a Referential Game. - Roberto Dessì; Diane Bouchacourt; Davide Crepaldi; Marco Baroni (CoRR, 2019)

Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN. - Rahma Chaabouni 001; Roberto Dessì; Eugene Kharitonov (BlackboxNLP@EMNLP, 2021)

Interpretable agent communication from scratch (with a generic visual processor emerging on the side). - Roberto Dessì; Eugene Kharitonov; Marco Baroni (NeurIPS, 2021)

Communication breakdown: On the low mutual intelligibility between human and neural captioning. - Roberto Dessì; Eleonora Gualdoni; Francesca Franzon; Gemma Boleda; Marco Baroni (EMNLP, 2022)

Cross-Domain Image Captioning with Discriminative Finetuning. - Roberto Dessì; Michele Bevilacqua; Eleonora Gualdoni; Nathanaël Carraz Rakotonirina; Francesca Franzon; Marco Baroni (CVPR, 2023)

Robustness of Named-Entity Replacements for In-Context Learning. - Saeed Goodarzi; Nikhil Kagita; Dennis Minn; Shufan Wang; Roberto Dessì; Shubham Toshniwal; Adina Williams; Jack Lanchantin; Koustuv Sinha (EMNLP (Findings), 2023)

Can discrete information extraction prompts generalize across language models? - Nathanaël Carraz Rakotonirina; Roberto Dessì; Fabio Petroni; Sebastian Riedel 001; Marco Baroni (ICLR, 2023)

Toolformer: Language Models Can Teach Themselves to Use Tools. - Timo Schick; Jane Dwivedi-Yu; Roberto Dessì; Roberta Raileanu; Maria Lomeli; Eric Hambro; Luke Zettlemoyer; Nicola Cancedda; Thomas Scialom (NeurIPS, 2023)

Toolformer: Language Models Can Teach Themselves to Use Tools. - Timo Schick; Jane Dwivedi-Yu; Roberto Dessì; Roberta Raileanu; Maria Lomeli; Luke Zettlemoyer; Nicola Cancedda; Thomas Scialom (CoRR, 2023)

Augmented Language Models: a Survey. - Grégoire Mialon; Roberto Dessì; Maria Lomeli; Christoforos Nalmpantis; Ramakanth Pasunuru; Roberta Raileanu; Baptiste Rozière; Timo Schick; Jane Dwivedi-Yu; Asli Celikyilmaz; Edouard Grave; Yann LeCun; et al. (Trans. Mach. Learn. Res., 2023)

I Want to Break Free! Persuasion and Anti-Social Behavior of LLMs in Multi-Agent Settings with Social Hierarchy. - Gian Maria Campedelli; Nicolò Penzo; Massimo Stefan; Roberto Dessì; Marco Guerini; Bruno Lepri; Jacopo Staiano (CoRR, 2024)

Referential communication in heterogeneous communities of pre-trained visual deep networks. - Matéo Mahaut; Roberto Dessì; Francesca Franzon; Marco Baroni (Trans. Mach. Learn. Res., 2025)