🧑‍🔬 Yova Kementchedjhieva

🏛️ Affiliations

🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2024–2026 · 7 paperscurrent🎓Technical University of DenmarkKongens Lyngby · Denmark2026 · 1 papercurrent🎓University of CopenhagenCopenhagen · Denmark2018–2025 · 31 papers🎓University of EdinburghEdinburgh · United Kingdom2016–2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction (2019 · 53 citations)
   The paper examines how far the MUSE benchmark for bilingual dictionary induction (BDI) can be trusted. This task is commonly used for the intrinsic evaluation of cross-lingual word embeddings. The MUSE dictionaries (110 language pairs) were generated automatically and were not cleaned manually. The authors worked…
2. Cultural Adaptation of Recipes (2024 · 50 citations)
   Recipes are procedural texts that depend on culturally specific knowledge: which ingredients are common, how quantities are expressed, what equipment a kitchen has, and the order in which steps are done.
3. ‘Indicatements' that character language models learn English morpho-syntactic units and regularities (2018 · 17 citations)
   The paper asks whether a character-level language model that reads raw, unsegmented English actually picks up morphology, or only seems to because it shares parameters across similar strings.
4. Why is unsupervised alignment of English embeddings from different algorithms so hard? (2018 · 14 citations)
   The authors ask when unsupervised bilingual dictionary induction can work at all. To remove differences between languages, they align English with English. They train 300-dimensional embeddings with five algorithms (Hyperwords-SVD, Hyperwords-SGNS, CBOW, GloVe, FastText) on two disjoint 10% samples of a March 2018…
5. JEEM: Vision-Language Understanding in Four Arabic Dialects (2026 · 11 citations)
   JEEM addresses a gap in evaluating vision-language models (VLMs) for Arabic. Existing Arabic multimodal data mostly comes from translated or relabeled Western images, and it is written in MSA or covers only one dialect. The authors built a benchmark with images from Jordan, the Emirates, Egypt and Morocco, one…
6. REVEAL: Retrieval-Enhanced Verification for Multimodal Fact-Checking (2026)
   Most automated fact-checking work targets text-only claims, but much real misinformation pairs images with text.

All works

8 works of theirs in our library, the most cited first; 6 with a page here, the others link their original until we summarise them.

1. Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary InductionEMNLP-IJCNLP 2019 (Hong Kong)Yova Kementchedjhieva, Mareike Hartmann, Anders Sgaard2019 · 53 citations
2. Cultural Adaptation of RecipesTransactions of the Association for Computational Linguistics (TACL)Yong Cao, Yova Kementchedjhieva, Ruixiang Cui, et al.2024 · 50 citations
3. An Exploration of Encoder-Decoder Approaches to Multi-Label Classification for Legal and Biomedical Text ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetYova Kementchedjhieva, Ilias Chalkidis2023 · 28 citations
4. ‘Indicatements' that character language models learn English morpho-syntactic units and regularitiesEMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLPYova Kementchedjhieva, Adam Lopez2018 · 17 citations
5. Grammatical Error Correction through Round-Trip Machine Translation ↗Findings of the Association for Computational Linguistics: EACL 2023 · no summary yetYova Kementchedjhieva, Anders Søgaard2023 · 16 citations
6. Why is unsupervised alignment of English embeddings from different algorithms so hard?Conference on Empirical Methods in Natural Language Processing (EMNLP)Mareike Hartmann, Yova Kementchedjhieva, Anders Søgaard2018 · 14 citations
7. JEEM: Vision-Language Understanding in Four Arabic DialectsFindings of the Association for Computational LinguisticsKarima Kadaoui, Hanin Atwany, Hamdan Al-Ali, et al.2026 · 11 citations
8. REVEAL: Retrieval-Enhanced Verification for Multimodal Fact-CheckingFact Extraction and VERification Workshop (FEVER)Amina Tariq, Yova Kementchedjhieva2026

🤝 Co-authors here

12 of 17 co-authors with a page, the most papers together first.

• Mareike Hartmann ×2
• Abdelrahman Mohamed
• Adam Lopez
• Ali Mekky
• Anders Søgaard
• Antonia Karamolegkou
• Daniel Hershcovich
• Ekaterina Artemova
• Hamdan Al-Ali
• Hanan Aldarmaki
• Hanin Atwany
• Karima Kadaoui

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP: EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP 2018
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2018
• Fact Extraction and VERification Workshop (FEVER): FEVER 2026
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Conference on Neural Information Processing Systems (NeurIPS)
• Transactions of the Association for Computational Linguistics (TACL): Transactions of the Association for Computational Linguistics (TACL) 2024
• EMNLP-IJCNLP 2019 (Hong Kong)
• Findings of the Association for Computational Linguistics: ACL 2023
• Findings of the Association for Computational Linguistics: EACL 2023

🔗 Cited by

Papers of our library cite their works 184 times (of the 149,439 papers whose bibliographies we read); 48 citing papers with a page here →.

Updated 2 November 2026

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