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Mitodru Niyogi

Mitodru Niyogi has 2 papers in our library, in 2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Low-resource languages; often with Arnab Bhattacharya, Eric Gaussier.

2 papers in our library · 2026

OpenAlex · h-index 2 · 9 works · 12 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #10580

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

🔬Centre National de la Recherche ScientifiqueParis · France2024–2026 · 3 paperscurrent🎓Université Grenoble AlpesSaint-Martin-d'Hères · France2024–2026 · 3 paperscurrent🎓Institut polytechnique de GrenobleGrenoble · France2024–2026 · 2 paperscurrent🔬Laboratoire d'Informatique de GrenobleGrenoble · France2024–2026 · 2 paperscurrent🎓Indian Institute of Technology KanpurKanpur · India2016–2018 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksLaw · 1 workPolitical Science and International Relations · 1 workSocial Sciences · 1 work

🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 1 workLow-resource languages · 1 workMorphology · 1 workMultilingual & cross-lingual NLP · 1 workLegal AI · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages (2026 · 5 citations)
    Multilingual LLMs often serve Indian languages poorly. They are trained mostly on English, their shared tokenizers split morphologically rich words into too many pieces, and they suffer from the curse of multilinguality. Adapting such models is also costly. The authors take a different route with Paramanu, a family…
  2. AYN: A Tiny Yet Competitive Indian Legal Language Model Pretrained from Scratch (2026)
    Large decoder-only LLMs are expensive to train and run. They also learn mostly from Western legal material, so they fit Indian jurisprudence poorly, with its archaic vocabulary, dense citation patterns and code-switching. The authors test whether a tiny language model (under 100M parameters), trained from scratch on…

 Co-authors here

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

Venues

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

 Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read).

Updated

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