Luca Di Liello

According to our database, Luca Di Liello authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Semantic Loss Functions for Neuro-Symbolic Structured Prediction.

Kareem Ahmed, Stefano Teso, Paolo Morettin, Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Yitao Liang, Eric Wang, Kai-Wei Chang, Andrea Passerini, Guy Van den Broeck

CoRR, 2024

2023

Semantic Loss Functions for Neuro-Symbolic Structured Prediction.

Kareem Ahmed, Stefano Teso, Paolo Morettin, Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Yitao Liang, Eric Wang, Kai-Wei Chang, Andrea Passerini, Guy Van den Broeck

Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

Structural Self-Supervised Objectives for Transformers.

Luca Di Liello

CoRR, 2023

Context-Aware Transformer Pre-Training for Answer Sentence Selection.

Luca Di Liello, Siddhant Garg, Alessandro Moschitti

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

TorchMetrics - Measuring Reproducibility in PyTorch.

Nicki Skafte Detlefsen, Jirí Borovec, Justus Schock, Ananya Harsh Jha, Teddy Koker, Luca Di Liello, Daniel Stancl, Changsheng Quan, Maxim Grechkin, William Falcon

J. Open Source Softw., 2022

Effective Pre-Training Objectives for Transformer-based Autoencoders.

Luca Di Liello, Matteo Gabburo, Alessandro Moschitti

CoRR, 2022

Paragraph-based Transformer Pre-training for Multi-Sentence Inference.

Luca Di Liello, Siddhant Garg, Luca Soldaini, Alessandro Moschitti

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection.

Luca Di Liello, Siddhant Garg, Luca Soldaini, Alessandro Moschitti

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Effective Pretraining Objectives for Transformer-based Autoencoders.

Luca Di Liello, Matteo Gabburo, Alessandro Moschitti

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Efficient pre-training objectives for Transformers.

Luca Di Liello, Matteo Gabburo, Alessandro Moschitti

CoRR, 2021

Language Transfer for Identifying Diagnostic Paragraphs in Clinical Notes.

Luca Di Liello, Olga Uryupina, Alessandro Moschitti

Proceedings of the Eighth Italian Conference on Computational Linguistics, 2021

2020

Efficient Generation of Structured Objects with Constrained Adversarial Networks.

Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Paolo Morettin, Stefano Teso, Andrea Passerini

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cross-Language Transformer Adaptation for Frequently Asked Questions.

Luca Di Liello, Daniele Bonadiman, Alessandro Moschitti, Cristina Giannone, Andrea Favalli, Raniero Romagnoli

Proceedings of the Seventh Italian Conference on Computational Linguistics, 2020