Dataset Construction via Attention for Aspect Term Extraction with Distant Supervision. - Athanasios Giannakopoulos; Diego Antognini; Claudiu Musat; Andreea Hossmann; Michael Baeriswyl (ICDM Workshops, 2017)

Multi-Dimensional Explanation of Reviews. - Diego Antognini; Claudiu Musat; Boi Faltings (CoRR, 2019)

Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization. - Diego Antognini; Boi Faltings (CoRR, 2019)

HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset. - Diego Antognini; Boi Faltings (LREC, 2020)

GameWikiSum: a Novel Large Multi-Document Summarization Dataset. - Diego Antognini; Boi Faltings (LREC, 2020)

Multi-Gradient Descent for Multi-Objective Recommender Systems. - Nikola Milojkovic; Diego Antognini; Giancarlo Bergamin; Boi Faltings; Claudiu Musat (CoRR, 2020)

T-RECS: a Transformer-based Recommender Generating Textual Explanations and Integrating Unsupervised Language-based Critiquing. - Diego Antognini; Claudiu Musat; Boi Faltings (CoRR, 2020)

Momentum-based Gradient Methods in Multi-objective Recommender Systems. - Blagoj Mitrevski; Milena Filipovic; Diego Antognini; Emma Lejal Glaude; Boi Faltings; Claudiu Musat (CoRR, 2020)

Multi-Dimensional Explanation of Target Variables from Documents. - Diego Antognini; Claudiu Musat; Boi Faltings (AAAI, 2021)

Rationalization through Concepts. - Diego Antognini; Boi Faltings (ACL/IJCNLP (Findings), 2021)

Interacting with Explanations through Critiquing. - Diego Antognini; Claudiu Musat; Boi Faltings (IJCAI, 2021)

Fast Multi-Step Critiquing for VAE-based Recommender Systems. - Diego Antognini; Boi Faltings (RecSys, 2021)

Modeling Online Behavior in Recommender Systems: The Importance of Temporal Context. - Milena Filipovic; Blagoj Mitrevski; Diego Antognini; Emma Lejal Glaude; Boi Faltings; Claudiu Musat (Perspectives@RecSys, 2021)

Multi-Step Critiquing User Interface for Recommender Systems. - Diana Andreea Petrescu; Diego Antognini; Boi Faltings (RecSys, 2021)

Addressing fairness in classification with a model-agnostic multi-objective algorithm. - Kirtan Padh; Diego Antognini; Emma Lejal Glaude; Boi Faltings; Claudiu Musat (UAI, 2021)

Recommending Burgers based on Pizza Preferences: Addressing Data Sparsity with a Product of Experts. - Martin Milenkoski; Diego Antognini; Claudiu Musat (CoRR, 2021)

Active Learning for Imbalanced Civil Infrastructure Data. - Thomas Frick; Diego Antognini; Mattia Rigotti; Ioana Giurgiu; Benjamin F. Grewe; Cristiano Malossi (ECCV Workshops (7), 2022)

Unsupervised Term Extraction for Highly Technical Domains. - Francesco Fusco; Peter W. J. Staar; Diego Antognini (EMNLP (Industry Track), 2022)

Positive and Negative Critiquing for VAE-based Recommenders. - Diego Antognini; Boi Faltings (CoRR, 2022)

Interlock-Free Multi-Aspect Rationalization for Text Classification. - Shuangqi Li; Diego Antognini; Boi Faltings (CoRR, 2022)

Textual Explanations and Critiques in Recommendation Systems. - Diego Antognini (CoRR, 2022)

Textual Explanations and Critiques in Recommendation Systems. - Diego Antognini (2022)

Extracting Text Representations for Terms and Phrases in Technical Domains. - Francesco Fusco; Diego Antognini (ACL (industry), 2023)

pNLP-Mixer: an Efficient all-MLP Architecture for Language. - Francesco Fusco; Damian Pascual; Peter W. J. Staar; Diego Antognini (ACL (industry), 2023)

Assistive Recipe Editing through Critiquing. - Diego Antognini; Shuyang Li; Boi Faltings; Julian J. McAuley (EACL, 2023)

ESG Accountability Made Easy: DocQA at Your Service. - Lokesh Mishra; Cesar Berrospi; Kasper Dinkla; Diego Antognini; Francesco Fusco; Benedikt Bothur; Maksym Lysak; Nikolaos Livathinos; Ahmed S. Nassar; Panagiotis Vagenas; Lucas Morin; Christoph Auer; et al. (AAAI, 2024)

Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models. - Yue Zhou; Yada Zhu; Diego Antognini; Yoon Kim; Yang Zhang 001 (NAACL-HLT, 2024)

Trans-LoRA: towards data-free Transferable Parameter Efficient Finetuning. - Runqian Wang; Soumya Ghosh; David D. Cox; Diego Antognini; Aude Oliva; Rogério Feris; Leonid Karlinsky (NeurIPS, 2024)

MC Layer Normalization for calibrated uncertainty in Deep Learning. - Thomas Frick; Diego Antognini; Ioana Giurgiu; Benjamin F. Grewe; Cristiano Malossi; Rong J. B. Zhu; Mattia Rigotti (Trans. Mach. Learn. Res., 2024)

InkFM: A Foundational Model for Full-Page Online Handwritten Note Understanding. - Anastasiia Fadeeva; Vincent Coriou; Diego Antognini; Claudiu Musat; Andrii Maksai (CoRR, 2025)