@patent{mambelli2026produce,author={Mambelli, Filippo and Guerra, Marco and Virgillito, Andrea and Le Creurer, Kilian and Pittiglio, Alessio and Giordano, Roberto},title={Systems and Methods for Produce Recognition in a Retail Environment},year={2026},month=jul,number={US 2026/0204084 A1},holder={Datalogic IP Tech S.R.L.},}
2025
ArgMining
Leveraging Context for Multimodal Fallacy Classification in Political Debates
Alessio Pittiglio
In Proceedings of the 12th Argument Mining Workshop, Jul 2025
In this paper, we present our submission to the MM-ArgFallacy2025 shared task, which aims to advance research in multimodal argument mining, focusing on logical fallacies in political debates. Our approach uses pretrained Transformer-based models and proposes several ways to leverage context. In the fallacy classification subtask, our models achieved macro F1-scores of 0.4444 (text), 0.3559 (audio), and 0.4403 (multimodal). Our multimodal model showed performance comparable to the text-only model, suggesting potential for improvements.
@inproceedings{pittiglio2025leveraging,author={Pittiglio, Alessio},title={Leveraging Context for Multimodal Fallacy Classification in Political Debates},booktitle={Proceedings of the 12th Argument Mining Workshop},year={2025},month=jul,pages={388--397},address={Vienna, Austria},publisher={Association for Computational Linguistics},}