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Ionut Sorodoc
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2020 – today
- 2024
- [c11]Philipp Christmann, Svitlana Vakulenko, Ionut Sorodoc, Bill Byrne, Adrià de Gispert:
Retrieving Contextual Information for Long-Form Question Answering using Weak Supervision. EMNLP (Findings) 2024: 14301-14310 - 2022
- [c10]Ionut Sorodoc, Laura Aina, Gemma Boleda:
Challenges in including extra-linguistic context in pre-trained language models. Insights@ACL 2022: 134-138 - 2021
- [c9]Ionut-Teodor Sorodoc, Gemma Boleda, Marco Baroni:
Controlled tasks for model analysis: Retrieving discrete information from sequences. BlackboxNLP@EMNLP 2021: 468-478 - [e1]Ionut-Teodor Sorodoc, Madhumita Sushil, Ece Takmaz, Eneko Agirre:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop, EACL 2021, Online, April 19-23, 2021. Association for Computational Linguistics 2021, ISBN 978-1-954085-04-6 [contents] - 2020
- [c8]Ionut-Teodor Sorodoc, Kristina Gulordava, Gemma Boleda:
Probing for Referential Information in Language Models. ACL 2020: 4177-4189 - [i7]Germán Kruszewski, Ionut-Teodor Sorodoc, Tomás Mikolov:
Class-Agnostic Continual Learning of Alternating Languages and Domains. CoRR abs/2004.03340 (2020)
2010 – 2019
- 2019
- [c7]Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera
, Gemma Boleda:
What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue. NAACL-HLT (1) 2019: 3772-3783 - [i6]Alba Maria Hererra-Palacio, Carles Ventura, Carina Silberer, Ionut-Teodor Sorodoc, Gemma Boleda, Xavier Giró-i-Nieto:
Recurrent Instance Segmentation using Sequences of Referring Expressions. ViGIL@NeurIPS 2019 - [i5]Laura Aina, Carina Silberer, Matthijs Westera, Ionut-Teodor Sorodoc, Gemma Boleda:
What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue. CoRR abs/1905.06649 (2019) - [i4]Alba Herrera-Palacio, Carles Ventura, Carina Silberer, Ionut-Teodor Sorodoc, Gemma Boleda, Xavier Giró-i-Nieto:
Recurrent Instance Segmentation using Sequences of Referring Expressions. CoRR abs/1911.02103 (2019) - 2018
- [j1]Ionut Sorodoc, Sandro Pezzelle
Learning quantification from images: A structured neural architecture. Nat. Lang. Eng. 24(3): 363-392 (2018) - [c6]Sandro Pezzelle, Ionut-Teodor Sorodoc, Raffaella Bernardi:
Comparatives, Quantifiers, Proportions: a Multi-Task Model for the Learning of Quantities from Vision. NAACL-HLT 2018: 419-430 - [c5]Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera
AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library. SemEval@NAACL-HLT 2018: 65-69 - [i3]Sandro Pezzelle, Ionut-Teodor Sorodoc, Raffaella Bernardi:
Comparatives, Quantifiers, Proportions: A Multi-Task Model for the Learning of Quantities from Vision. CoRR abs/1804.05018 (2018) - [i2]Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera, Gemma Boleda:
AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library. CoRR abs/1805.05370 (2018) - 2017
- [c4]Ionut Sorodoc, Jey Han Lau, Nikolaos Aletras, Timothy Baldwin:
Multimodal Topic Labelling. EACL (2) 2017: 701-706 - [i1]Ionut Sorodoc, Sandro Pezzelle, Aurélie Herbelot, Mariella Dimiccoli, Raffaella Bernardi:
Pay Attention to Those Sets! Learning Quantification from Images. CoRR abs/1704.02923 (2017) - 2016
- [c3]Ionut Sorodoc, Angeliki Lazaridou, Gemma Boleda, Aurélie Herbelot
"Look, some Green Circles!": Learning to Quantify from Images. VL@ACL 2016 - [c2]Sandro Pezzelle, Ionut Sorodoc, Aurélie Herbelot, Raffaella Bernardi:
Imparare a Quantificare Guardando (Learning to Quantify by Watching). CLiC-it/EVALITA 2016 - 2014
- [c1]Anca Dinu, Liviu P. Dinu, Ionut Sorodoc:
Aggregation methods for efficient collocation detection. LREC 2014: 4041-4045
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