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Jay Gala

Jay Gala has 2 papers in our library, in 2023–2025, most of them on Machine translation, Multilingual & cross-lingual NLP, Evaluation & benchmarks; often with David Stap, Genta Indra Winata, Kenneth Christian Enevoldsen.

2 papers in our library · 2023–2025

OpenAlex · ORCID · h-index 6 · 24 works · 161 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 360 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4180

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

🎓Dwarkadas J. Sanghvi College of EngineeringMumbai · India2020–2022 · 7 papers🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2024 · 6 papers🎓Narsee Monjee Institute of Management StudiesMumbai · India2023–2025 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

 Concepts, shelves and topics

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 3Research subjects and languages the work is about.Machine translation · 1 workEvaluation & benchmarks · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20251 paperMMTEB: Massive Multilingual Text Embedding Benchmark20231 paperIndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages

 Papers

The most cited first (OpenAlex and our library).

  1. IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages (2023 · 200 citations)
    India's 22 scheduled languages have been poorly served by machine translation. Before this work, no public parallel data covered all of them, no benchmark spanned all 22 with India-relevant material, and no open or commercial model supported the full set. The authors address this on four fronts: training data…
  2. 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.

All works

4 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. IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian LanguagesJay Gala, Pranjal A. Chitale, Raghavan AK, et al.arXiv:2305.16307 · 200 citations
  2. MMTEB: Massive Multilingual Text Embedding BenchmarkKenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.arXiv:2502.13595 · 101 citations
  3. CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark · original ↗ · no summary yet · arXiv:2406.05967David Romero et al.2024 · 87 citations
  4. Airavata: Introducing Hindi Instruction-tuned LLM · original ↗ · no summary yet · arXiv:2401.15006Jay Gala et al.2024 · 31 citations

 Co-authors here

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

 Cited by

Papers of our library cite their works 360 times (of the 141,840 papers whose bibliographies we read); 24 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/jay-gala/