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# Maayan Zhitomirsky-Geffet

3 paper cards in Mova's library · 2023–2026

Maayan Zhitomirsky-Geffet wrote 3 of the papers Mova reads, in 2023–2026, most of them on [Named entity recognition](https://md.mova.elamur.ai/free/en/docs/papers/topics/named-entity-recognition/); often with [Avshalom Elmalech](https://md.mova.elamur.ai/free/en/docs/papers/authors/avshalom-elmalech/), [Omri Suissa](https://md.mova.elamur.ai/free/en/docs/papers/authors/omri-suissa/), Binyamin Katzoff.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Maayan+Zhitomirsky-Geffet) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Maayan+Zhitomirsky-Geffet) · [dblp](https://dblp.org/search?q=Maayan+Zhitomirsky-Geffet) · [ACL Anthology](https://aclanthology.org/search/?q=Maayan+Zhitomirsky-Geffet) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Maayan+Zhitomirsky-Geffet)

Topics: [Named entity recognition](https://md.mova.elamur.ai/free/en/docs/papers/topics/named-entity-recognition/) 1

## Papers

1. **[Domain-Aware Error Correction for Citation NER in Medieval Hebrew Responsa](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2026-liebeskind-domain-aware-error-correction-citation/)** *(2026)* The task is citation NER in medieval Hebrew Responsa: each token of a citation gets a role (book name, author, reference number, reference word, and so on, or outside).
2. **[Toward a Period-Specific Optimized Neural Network for OCR Error Correction of Historical Hebrew Texts](https://md.mova.elamur.ai/free/en/docs/papers/hbo-2023-suissa-toward-period-specific-optimized-neural/)** *(2023)* The full version of the authors' work on Hebrew OCR post-correction. They align 70% of hand-corrected JPress newspaper articles with their OCR output (Needleman–Wunsch) to learn character-level, period-specific confusions — the commonest being ח→ה (about 8%), ד→ר (5%), ג→נ, ב→כ, ם→ס, ח→ת, ו↔י — and inject them into…
3. **[Optimizing the Neural Network Training for OCR Error Correction of Historical Hebrew Texts](https://md.mova.elamur.ai/free/en/docs/papers/hbo-2023-suissa-optimizing-neural-network-training-ocr/)** *(2023)* OCR of historical Hebrew newspapers (the JPress collection) is noisy, and neural post-correctors need large hand-corrected sets.

## Co-authors (6)

- [Avshalom Elmalech](https://md.mova.elamur.ai/free/en/docs/papers/authors/avshalom-elmalech/) ×2
- [Omri Suissa](https://md.mova.elamur.ai/free/en/docs/papers/authors/omri-suissa/) ×2
- Binyamin Katzoff
- [Jonathan Schler](https://md.mova.elamur.ai/free/en/docs/papers/authors/jonathan-schler/)
- Nati Ben-Gigi
- [Shmuel LIebeskind](https://md.mova.elamur.ai/free/en/docs/papers/authors/shmuel-liebeskind/)
- [← previous Lynn Carlson](https://md.mova.elamur.ai/free/en/docs/papers/authors/lynn-carlson/)
- [next → Mahmoud Reda](https://md.mova.elamur.ai/free/en/docs/papers/authors/mahmoud-reda/)
- [↑ back to Authors](https://md.mova.elamur.ai/free/en/docs/papers/authors/)