| The LAMBADA dataset: Word prediction requiring a broad discourse context D Paperno, G Kruszewski, A Lazaridou, QN Pham, R Bernardi, S Pezzelle, ... arXiv preprint arXiv:1606.06031, 2016 | 287 | 2016 |
| Foil it! find one mismatch between image and language caption R Shekhar, S Pezzelle, Y Klimovich, A Herbelot, M Nabi, E Sangineto, ... arXiv preprint arXiv:1705.01359, 2017 | 95 | 2017 |
| Probing the mental representation of quantifiers S Pezzelle, R Bernardi, M Piazza Cognition 181, 117-126, 2018 | 25 | 2018 |
| Refer, reuse, reduce: Generating subsequent references in visual and conversational contexts E Takmaz, M Giulianelli, S Pezzelle, A Sinclair, R Fernández arXiv preprint arXiv:2011.04554, 2020 | 22 | 2020 |
| “Look, some green circles!”: Learning to quantify from images I Sorodoc, A Lazaridou, G Boleda Torrent, AGG Herbelot, S Pezzelle, ... ACL 2016 5th Workshop on Vision and Language (VL’16): Proceedings of the …, 2016 | 21 | 2016 |
| Generating image descriptions via sequential cross-modal alignment guided by human gaze E Takmaz, S Pezzelle, L Beinborn, R Fernández arXiv preprint arXiv:2011.04592, 2020 | 19 | 2020 |
| Is the red square big? MALeViC: Modeling adjectives leveraging visual contexts S Pezzelle, R Fernández arXiv preprint arXiv:1908.10285, 2019 | 18 | 2019 |
| Be different to be better! A benchmark to leverage the complementarity of language and vision S Pezzelle, C Greco, G Gandolfi, E Gualdoni, R Bernardi Findings of the association for computational linguistics: EMNLP 2020, 2751-2767, 2020 | 13 | 2020 |
| Comparatives, quantifiers, proportions: a multi-task model for the learning of quantities from vision S Pezzelle, IT Sorodoc, R Bernardi arXiv preprint arXiv:1804.05018, 2018 | 12 | 2018 |
| Vision and language integration: Moving beyond objects R Shekhar, S Pezzelle, A Herbelot, M Nabi, E Sangineto, R Bernardi IWCS 2017—12th International Conference on Computational Semantics—Short …, 2017 | 12 | 2017 |
| Linguistic issues behind visual question answering R Bernardi, S Pezzelle Language and Linguistics Compass 15 (6), elnc3.12417, 2021 | 10 | 2021 |
| Be precise or fuzzy: Learning the meaning of cardinals and quantifiers from vision S Pezzelle, M Marelli, R Bernardi arXiv preprint arXiv:1702.05270, 2017 | 10 | 2017 |
| Learning quantification from images: A structured neural architecture I Sorodoc, S Pezzelle, A Herbelot, M Dimiccoli, R Bernardi Natural Language Engineering 24 (3), 363-392, 2018 | 9 | 2018 |
| Word representation learning in multimodal pre-trained transformers: An intrinsic evaluation S Pezzelle, E Takmaz, R Fernández Transactions of the Association for Computational Linguistics 9, 1563-1579, 2021 | 7 | 2021 |
| Building a bagpipe with a bag and a pipe: Exploring conceptual combination in vision S Pezzelle, R Shekhar, R Bernardi Proceedings of the 5th Workshop on Vision and Language, 60-64, 2016 | 7 | 2016 |
| Quantifiers in a multimodal world: Hallucinating vision with language and sound A Testoni, S Pezzelle, R Bernardi Proceedings of the workshop on cognitive modeling and computational …, 2019 | 6 | 2019 |
| The wisdom of masses: majority, subjectivity, and semantic similarity in the evaluation of VQA S Jolly, S Pezzelle, T Klein, A Dengel, M Nabi arXiv preprint arXiv:1809.04344, 2018 | 6 | 2018 |
| Some of them can be guessed! Exploring the effect of linguistic context in predicting quantifiers S Pezzelle, S Steinert-Threlkeld, R Bernardi, J Szymanik arXiv preprint arXiv:1806.00354, 2018 | 6 | 2018 |
| Less descriptive yet discriminative: Quantifying the properties of multimodal referring utterances via CLIP E Takmaz, S Pezzelle, R Fernández Proceedings of the workshop on cognitive modeling and computational …, 2022 | 5 | 2022 |
| The LAMBADA dataset: Word prediction requiring a broad discourse context. arXiv 2016 D Paperno, G Kruszewski, A Lazaridou, QN Pham, R Bernardi, S Pezzelle, ... arXiv preprint arXiv:1606.06031, 0 | 5 | |
Raffaella BernardiUniversity of TrentoVerified email at unitn.it
