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Saba Sturua

Saba Sturua has 2 papers in our library, in 2023–2025, most of them on Multilingual & cross-lingual NLP, Evaluation & benchmarks; often with Bo Wang, David Stap, Genta Indra Winata.

2 papers in our library · 2023–2025

OpenAlex · ORCID · h-index 4 · 15 works · 74 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 238 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4775

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢Jina AIBerlin · Germany2024–2025 · 6 papers

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

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20251 paperMMTEB: Massive Multilingual Text Embedding Benchmark20231 paperJina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents

 Papers

The most cited first (OpenAlex and our library).

  1. MMTEB: Massive Multilingual Text Embedding Benchmark (2025 · 101 citations)
    Embedding models are usually tested on narrow benchmarks that cover few languages, domains and task types, and full evaluation is often too costly for communities with little compute.
  2. Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents (2023 · 75 citations)
    Most open-source text embedding models inherit BERT's 512-token input limit. Long documents must therefore be truncated or split into chunks, which fragments their meaning and multiplies the number of vectors to store and search. The Jina AI team presents Jina Embeddings v2, an English embedding suite that accepts…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. jina-embeddings-v3: Multilingual Embeddings With Task LoRAarXiv:2409.10173 · original ↗ · no summary yetSaba Sturua et al.2024 · 109 citations
  2. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 101 citations
  3. Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long DocumentsarXiv:2310.19923Michael Gunther, Jackmin Ong, Isabelle Mohr, et al.2023 · 75 citations

 Co-authors here

5 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 238 times (of the 141,840 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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