mlsanityData to 7 Oct 2026

Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language

arXiv 2208.01875 ↗First posted 3 Aug 2022cs.CLcited by 3

Not on the map. Why?

Abstract (arXiv)

We present a new pre-trained language model (PLM) for Rabbinic Hebrew, termed Berel (BERT Embeddings for Rabbinic-Encoded Language). Whilst other PLMs exist for processing Hebrew texts (e.g., HeBERT, AlephBert), they are all trained on modern Hebrew texts, which diverges substantially from Rabbinic Hebrew in terms of its lexicographical, morphological, syntactic and orthographic norms. We demonstrate the superiority of Berel on Rabbinic texts via a challenge set of Hebrew homographs. We release the new model and homograph challenge set for unrestricted use.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 7 of its 8 references that are in the map. First posted on arXiv 3 Aug 2022.

Builds on

7 of 8 references.

References · 7

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  4. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  5. 2021AlephBERT:A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application Withcited by 28
  6. 2019What's Wrong with Hebrew NLP? And How to Make it Rightcited by 16
  7. 2021HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognitioncited by 14

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 1.

3 papers.