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Haim Dubossarsky
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2020 – today
- 2024
- [c17]Francesco Periti, Pierluigi Cassotti, Haim Dubossarsky, Nina Tahmasebi:
Analyzing Semantic Change through Lexical Replacements. ACL (1) 2024: 4495-4510 - [c16]Haim Dubossarsky, Farheen Dairkee:
Strengthening the WiC: New Polysemy Dataset in Hindi and Lack of Cross Lingual Transfer. LREC/COLING 2024: 15341-15349 - [c15]Roksana Goworek, Haim Dubossarsky:
Toward Sentiment Aware Semantic Change Analysis. EACL (Student Research Workshop) 2024: 350-357 - [c14]Francesco Periti, Haim Dubossarsky, Nina Tahmasebi:
(Chat)GPT v BERT Dawn of Justice for Semantic Change Detection. EACL (Findings) 2024: 420-436 - [c13]Avital Hahamy, Haim Dubossarsky, Timothy Behrens:
Integrating Cognitive Neuroscience Insights into NLP: A New Approach to Understanding Narrative Processing (Abstract). Text2Story@ECIR 2024: 149 - [c12]Eszter Zsisku, Arkaitz Zubiaga, Haim Dubossarsky:
Hate Speech Detection and Reclaimed Language: Mitigating False Positives and Compounded Discrimination. WebSci 2024: 241-249 - [i11]Francesco Periti, Haim Dubossarsky, Nina Tahmasebi:
(Chat)GPT v BERT: Dawn of Justice for Semantic Change Detection. CoRR abs/2401.14040 (2024) - [i10]Francesco Periti, Pierluigi Cassotti, Haim Dubossarsky, Nina Tahmasebi:
Analyzing Semantic Change through Lexical Replacements. CoRR abs/2404.18570 (2024) - 2023
- [c11]Francesco Periti, Haim Dubossarsky:
The Time-Embedding Travelers at WiC-ITA. EVALITA 2023 - [c10]Wei Zhou, Nina Tahmasebi, Haim Dubossarsky:
The Finer They Get: Combining Fine-Tuned Models For Better Semantic Change Detection. NoDaLiDa 2023: 518-528 - [i9]Nina Tahmasebi, Haim Dubossarsky:
Computational modeling of semantic change. CoRR abs/2304.06337 (2023) - [i8]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Oana-Maria Camburu, Marek Rei:
Logical Reasoning for Natural Language Inference Using Generated Facts as Atoms. CoRR abs/2305.13214 (2023) - 2022
- [c9]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Marek Rei:
Logical Reasoning with Span-Level Predictions for Interpretable and Robust NLI Models. EMNLP 2022: 3809-3823 - [e2]Nina Tahmasebi, Syrielle Montariol, Andrey Kutuzov, Simon Hengchen, Haim Dubossarsky, Lars Borin:
Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, LChange@ACL 2022, Dublin, Ireland, May 26-27, 2022. Association for Computational Linguistics 2022, ISBN 978-1-955917-42-1 [contents] - [i7]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Marek Rei:
Logical Reasoning with Span Predictions: Span-level Logical Atoms for Interpretable and Robust NLI Models. CoRR abs/2205.11432 (2022) - 2021
- [c8]Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen, Haim Dubossarsky, Barbara McGillivray:
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages. EMNLP (1) 2021: 7079-7091 - [e1]Nina Tahmasebi, Adam Jatowt, Yang Xu, Simon Hengchen, Syrielle Montariol, Haim Dubossarsky:
Proceedings of The 2nd International Workshop on Computational Approaches to Historical Language Change 2021, LChange@ACL-IJCNLP 2021, Online, August 6, 2021. Association for Computational Linguistics 2021, ISBN 978-1-954085-60-2 [contents] - [i6]Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg, Haim Dubossarsky:
Challenges for Computational Lexical Semantic Change. CoRR abs/2101.07668 (2021) - [i5]Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen, Haim Dubossarsky, Barbara McGillivray:
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages. CoRR abs/2104.08540 (2021) - 2020
- [c7]Haim Dubossarsky, Ivan Vulic, Roi Reichart, Anna Korhonen:
The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures. EMNLP (1) 2020: 2377-2390 - [c6]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Sebastian Riedel, Tim Rocktäschel:
Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training. EMNLP (1) 2020: 8281-8291 - [c5]Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky, Nina Tahmasebi:
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection. SemEval@COLING 2020: 1-23 - [i4]Haim Dubossarsky, Ivan Vulic, Roi Reichart, Anna Korhonen:
Lost in Embedding Space: Explaining Cross-Lingual Task Performance with Eigenvalue Divergence. CoRR abs/2001.11136 (2020) - [i3]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Sebastian Riedel, Tim Rocktäschel:
There is Strength in Numbers: Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training. CoRR abs/2004.07790 (2020) - [i2]Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky, Nina Tahmasebi:
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection. CoRR abs/2007.11464 (2020)
2010 – 2019
- 2019
- [c4]Haim Dubossarsky, Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg:
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change. ACL (1) 2019: 457-470 - [i1]Haim Dubossarsky, Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg:
Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change. CoRR abs/1906.01688 (2019) - 2018
- [b1]Haim Dubossarsky:
Semantic change at large: a computational approach for semantic change research (שער נוסף בעברית: שינוי משמעות הולך בגדולות : גישה חישובית למחקר של שינוי סמנטי). Hebrew University of Jerusalem, Israel, 2018 - [c3]Haim Dubossarsky, Eitan Grossman, Daphna Weinshall:
Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research. EMNLP 2018: 1732-1740 - 2017
- [c2]Haim Dubossarsky, Daphna Weinshall, Eitan Grossman:
Outta Control: Laws of Semantic Change and Inherent Biases in Word Representation Models. EMNLP 2017: 1136-1145 - 2015
- [c1]Haim Dubossarsky, Yulia Tsvetkov, Chris Dyer, Eitan Grossman:
A bottom up approach to category mapping and meaning change. NetWordS 2015: 66-70
Coauthor Index
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last updated on 2024-10-07 21:26 CEST by the dblp team
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