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Haim Dubossarsky

22 papers · 2017–2026 · 5 venues · across top CS/AI venues

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Papers

Benchmarking Hate Speech Detection in Azerbaijani with Turkish Cross-Lingual Transfer and Transformer Models EACL 2026 Language Matters: Target-Language Supervision for Political Bias Detection in Turkish News EACL 2026 Rethinking Metrics for Lexical Semantic Change Detection EACL 2026 Definition Generation for Word Meaning Modeling: Monolingual, Multilingual, and Cross-Lingual Perspectives EMNLP 2025 LSC-Eval: A General Framework to Evaluate Methods for Assessing Dimensions of Lexical Semantic Change Using LLM-Generated Synthetic Data ACL 2025 Multilinguality Does not Make Sense: Investigating Factors Behind Zero-Shot Cross-Lingual Transfer in Sense-Aware Tasks EMNLP 2025 SenWiCh: Sense-Annotation of Low-Resource Languages for WiC using Hybrid Methods ACL 2025 Analyzing Semantic Change through Lexical Replacements ACL 2024 Atomic Inference for NLI with Generated Facts as Atoms EMNLP 2024 (Chat)GPT v BERT Dawn of Justice for Semantic Change Detection EACL 2024 Computational modeling of semantic change EACL 2024 Strengthening the WiC: New Polysemy Dataset in Hindi and Lack of Cross Lingual Transfer COLING 2024 Toward Sentiment Aware Semantic Change Analysis EACL 2024 Logical Reasoning with Span-Level Predictions for Interpretable and Robust NLI Models EMNLP 2022 DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages EMNLP 2021 Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training EMNLP 2020 SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection SemEval 2020 The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures EMNLP 2020 Proceedings of TyP-NLP: The First Workshop on Typology for Polyglot NLP ACL 2019 Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change ACL 2019 Coming to Your Senses: on Controls and Evaluation Sets in Polysemy Research EMNLP 2018 Outta Control: Laws of Semantic Change and Inherent Biases in Word Representation Models EMNLP 2017