( en | de | ru )

 

Disambiguation of "Testoni, Alberto"

Author of the publication

copydeleteadd this publication to your clipboard
Learning to Ask Informative Questions: Enhancing LLMs with Preference Optimization and Expected Information Gain.

, , and . CoRR, (2024)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Alberto Fierro

Alberto Moreira

Alberto Coda

Alberto Ricco

Alberto Moreira

 

Other publications of authors with the same name

Naming, Describing, and Quantifying Visual Objects in Humans and LLMs., , and . CoRR, (2024)Grounding Dialogue History: Strengths and Weaknesses of Pre-trained Transformers., , and . AI*IA, volume 12414 of Lecture Notes in Computer Science, page 263-279. Springer, (2020)ACT-Thor: A Controlled Benchmark for Embodied Action Understanding in Simulated Environments., , , , and . COLING, page 5597-5612. International Committee on Computational Linguistics, (2022)A software architecture for generic human activity recognition from smartphone sensor data., and . M&N, page 1-6. IEEE, (2017)The Interplay of Task Success and Dialogue Quality: An in-depth Evaluation in Task-Oriented Visual Dialogues., and . EACL, page 2071-2082. Association for Computational Linguistics, (2021)Jointly Learning to See, Ask, Decide when to Stop, and then GuessWhat., , , and . CLiC-it, volume 2481 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)The Efficiency of Question-Asking Strategies in a Real-World Visual Search Task., , and . Cogn. Sci., (December 2023)Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questions., and . EACL (1), page 258-275. Association for Computational Linguistics, (2024)Looking for Confirmations: An Effective and Human-Like Visual Dialogue Strategy., and . EMNLP (1), page 9330-9338. Association for Computational Linguistics, (2021)Overprotective Training Environments Fall Short at Testing Time: Let Models Contribute to Their Own Training., and . CLiC-it, volume 2769 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)