Who cites «Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All»
23 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card
- A New State-of-the-Art BERT Model for Judeo-Arabic — 2026 · Proceedings of the Fourth Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA 2026) @ LREC 2026
- Annotation Matters: Resolving Cross-Corpus Performance Drops in Hebrew Offensive Language Detection — our card · 2026 · Proceedings of Computational Affective Science (CAS) @ LREC 2026
- HalleluBERT: Let Every Token That Has Meaning Bear Its Weight — our card · 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
- Hebrew Diacritics Restoration using Visual Representation — our card · 2026 · Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)
- A Classifier of Word-Level Variants in Witnesses of Biblical Hebrew Manuscripts — our card · 2025 · Findings of the Association for Computational Linguistics: ACL 2025
- An Annotation Scheme for Factuality and Its Application to Parliamentary Proceedings — 2025 · Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era
- LCHAIM - Investigating Long Context Reasoning in Hebrew — our card · 2025 · Findings of the Association for Computational Linguistics: ACL 2025
- NeoDictaBERT: Pushing the Frontier of BERT models for Hebrew — our card · 2025 · arXiv:2510.20386
- Restoring Missing Spaces in Scraped Hebrew Social Media — our card · 2025 · Proceedings of the Tenth Workshop on Noisy and User-generated Text
- Systematic Textual Availability of Manuscripts — our card · 2025 · Proceedings of the 5th Conference on Language, Data and Knowledge
- TafBERTa: Learning Grammatical Rules from Small-Scale Language Acquisition Data in Hebrew — our card · 2025 · Proceedings of the First BabyLM Workshop
- Embible: Reconstruction of Ancient Hebrew and Aramaic Texts Using Transformers — our card · 2024 · Findings of the Association for Computational Linguistics: EACL 2024
- MsBERT: A New Model for the Reconstruction of Lacunae in Hebrew Manuscripts — our card · 2024 · Proceedings of the 1st Workshop on Machine Learning for Ancient Languages (ML4AL 2024)
- OtoBERT: Identifying Suffixed Verbal Forms in Modern Hebrew Literature — our card · 2024 · Proceedings of the Third Workshop on Text Simplification, Accessibility and Readability (TSAR 2024)
- Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
- DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew — our card · 2023 · arXiv:2308.16687
- Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew — our card · 2023 · arXiv:2311.00658
- HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark — our card · 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- HeRo: RoBERTa and Longformer Hebrew Language Models — our card · 2023 · arXiv:2304.11077
- Is Probing All You Need? Indicator Tasks as an Alternative to Probing Embedding Spaces — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
- Multilingual Sequence-to-Sequence Models for Hebrew NLP — our card · 2023 · Findings of the Association for Computational Linguistics: ACL 2023
- Temporal Relation Classification in Hebrew — our card · 2023 · Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings)
- ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development — our card · 2023 · arXiv:2307.08720