Haim Dubossarsky
Haim Dubossarsky
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Zitiert von
Zitiert von
SemEval-2020 task 1: Unsupervised lexical semantic change detection
D Schlechtweg, B McGillivray, S Hengchen, H Dubossarsky, ...
arXiv preprint arXiv:2007.11464, 2020
Outta control: Laws of semantic change and inherent biases in word representation models
H Dubossarsky, D Weinshall, E Grossman
Proceedings of the 2017 conference on empirical methods in natural language …, 2017
Time-out: Temporal referencing for robust modeling of lexical semantic change
H Dubossarsky, S Hengchen, N Tahmasebi, D Schlechtweg
arXiv preprint arXiv:1906.01688, 2019
Quantifying the structure of free association networks across the life span.
H Dubossarsky, S De Deyne, TT Hills
Developmental psychology 53 (8), 1560, 2017
A bottom up approach to category mapping and meaning change.
H Dubossarsky, Y Tsvetkov, C Dyer, E Grossman
NetWordS, 66-70, 2015
Verbs change more than nouns: A bottom-up computational approach to semantic change
H Dubossarsky, D Weinshall, E Grossman
Lingue e linguaggio 15 (1), 7-28, 2016
Avoiding the hypothesis-only bias in natural language inference via ensemble adversarial training
J Stacey, P Minervini, H Dubossarsky, S Riedel, T Rocktäschel
arXiv preprint arXiv:2004.07790, 2020
DWUG: A large resource of diachronic word usage graphs in four languages
D Schlechtweg, N Tahmasebi, S Hengchen, H Dubossarsky, ...
arXiv preprint arXiv:2104.08540, 2021
Challenges for computational lexical semantic change
S Hengchen, N Tahmasebi, D Schlechtweg, H Dubossarsky
Computational approaches to semantic change 6, 341, 2021
The human brain reactivates context-specific past information at event boundaries of naturalistic experiences
A Hahamy, H Dubossarsky, TEJ Behrens
Nature neuroscience 26 (6), 1080-1089, 2023
The secret is in the spectra: Predicting cross-lingual task performance with spectral similarity measures
H Dubossarsky, I Vulić, R Reichart, A Korhonen
arXiv preprint arXiv:2001.11136, 2020
Coming to your senses: on controls and evaluation sets in polysemy research
H Dubossarsky, E Grossman, D Weinshall
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
Semantic change at large: A computational approach for semantic change research
H Dubossarsky
Ph. D. thesis, Hebrew University of Jerusalem, Edmond and Lily Safra Center …, 2018
Logical reasoning with span-level predictions for interpretable and robust NLI models
J Stacey, P Minervini, H Dubossarsky, M Rei
arXiv preprint arXiv:2205.11432, 2022
(Chat) GPT v BERT: Dawn of Justice for Semantic Change Detection
F Periti, H Dubossarsky, N Tahmasebi
arXiv preprint arXiv:2401.14040, 2024
Computational modeling of semantic change
N Tahmasebi, H Dubossarsky
arXiv preprint arXiv:2304.06337, 2023
Logical reasoning for natural language inference using generated facts as atoms
J Stacey, P Minervini, H Dubossarsky, OM Camburu, M Rei
arXiv preprint arXiv:2305.13214, 2023
The Time-Embedding Travelers at WiC-ITA.
F Periti, H Dubossarsky
The finer they get: Combining fine-tuned models for better semantic change detection
W Zhou, N Tahmasebi, H Dubossarsky
Proceedings of the 24th Nordic Conference on Computational Linguistics …, 2023
Analyzing Semantic Change through Lexical Replacements
F Periti, P Cassotti, H Dubossarsky, N Tahmasebi
arXiv preprint arXiv:2404.18570, 2024
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