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title: "Reut Tsarfaty — papers of 2023 — 7 papers, the most cited first"
description: "Reut Tsarfaty — papers of 2023: 7 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Reut Tsarfaty — papers of 2023 — 7 papers, the most cited first

7 papers · [all years of Reut Tsarfaty](https://md.research.elamur.ai/free/en/authors/reut-tsarfaty/#years)

**[Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design](https://md.research.elamur.ai/free/en/papers/pyatkin-2023-design-choices-crowdsourcing-implicit-discourse/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, et al.*2023 · 19 citations*

- [HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark](https://md.research.elamur.ai/free/en/papers/cohen-2023-heq-large-diverse-hebrew-reading/) — Amir DN Cohen, Hilla Merhav, Yoav Goldberg, et al. · Modern Hebrew · 13 citations
- [Multilingual Sequence-to-Sequence Models for Hebrew NLP](https://md.research.elamur.ai/free/en/papers/eyal-2023-multilingual-sequence-sequence-models-hebrew/) — Matan Eyal, Hila Noga, Roee Aharoni, et al. · Modern Hebrew · 9 citations
- [Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew](https://md.research.elamur.ai/free/en/papers/gueta-2023-explicit-morphological-knowledge-improves-pre/) — Eylon Gueta, Omer Goldman, Reut Tsarfaty · Modern Hebrew · 7 citations
- [Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?](https://md.research.elamur.ai/free/en/papers/shmidman-2023-do-pretrained-contextual-language-models/) — Avi Shmidman, Cheyn Shmuel Shmidman, Dan Bareket, et al. · Ancient Hebrew · 5 citations
- [HeGeL: A Novel Dataset for Geo-Location from Hebrew Text](https://md.research.elamur.ai/free/en/papers/argaman-2023-hegel-novel-dataset-geo-location/) — Tzuf Paz-Argaman, Tal Bauman, Itai Mondshine, et al. · Modern Hebrew · 4 citations
- [The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment](https://md.research.elamur.ai/free/en/papers/hagag-2023-truth-whole-truth-nothing-but/) — Ben Hagag, Reut Tsarfaty · Modern Hebrew