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description: "Ondřej Bojar, Charles University: 30 papers on Elamur Research (2008–2026), h-index 38 — affiliations, topics, co-authors and who cites…"
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# Ondřej Bojar · page 2

30 papers in our library · 2008–2026 · page 2 of 2

[The profile, affiliations and co-authors →](https://md.research.elamur.ai/free/en/authors/ondrej-bojar/)

## Papers

The most cited first (OpenAlex and our library).

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26. **[Phrase-Based and Deep Syntactic English-to-Czech Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/bojar-2008-phrase-based-deep-syntactic-english/)** *(2008 · 37 citations)* The paper reports two English-to-Czech systems for WMT 2008. The first is a factored phrase-based system in Moses. Its target side is generated in two steps: word forms first, then full morphological tags, with six language models, including 7-gram models over tags. It is the stronger system, at 16.4 BLEU on the…
27. **[Automatic MT Error Analysis: Hjerson Helping Addicter](https://md.research.elamur.ai/free/en/papers/berka-2012-automatic-mt-error-analysis-hjerson/)** *(2012 · 17 citations)* The paper presents an open-source tool for detailed MT error analysis. It joins two systems: Hjerson, the automatic classifier from Popović (2011), and Addicter, which brings alignment, a web interface and a corpus browser. Errors are found by comparing the output with the reference through a chosen word alignment…
28. **[Current state of LLMs for Arabic dialectal machine translation](https://md.research.elamur.ai/free/en/papers/jon-2026-current-state-llms-arabic-dialectal/)** *(2026 · 2 citations)* Jon, Bondok and Bojar ask how well current large language models translate between English and spoken Arabic varieties, as opposed to Modern Standard Arabic.
29. **[Machine Translation for Low-Resource Languages through Monolingual Data and LLM: A Case Study of English-to-Basque](https://md.research.elamur.ai/free/en/papers/luu-2026-machine-translation-low-resource-languages/)** *(2026)* The paper examines whether an English-to-Basque machine translation system can be built without any genuine parallel data, using only Basque monolingual text and LLMs.
30. **[Training data generation for context-dependent rubric-based short answer grading](https://md.research.elamur.ai/free/en/papers/sindelar-2026-training-data-generation-context-dependent/)** *(2026)* Automatically grading short open-ended answers needs a lot of domain-specific training data with rubrics and both correct and incorrect answers, but suitable data such as past OECD PISA items are confidential.

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