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Ratish Puduppully

Ratish Puduppully has 4 papers in our library, in 2019–2023, most of them on Text generation, Machine translation; often with Mirella Lapata, Pratyush Kumar, Anoop Kunchukuttan.

4 papers in our library · 2019–2023

OpenAlex · ORCID · h-index 13 · 57 works · 787 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 395 citations in our library · 4 more in our library without a page yet · ⭐ Paper Star rank #2999

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

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.

 Concepts, shelves and topics

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

 Works by year

2020s

2010s

 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. Data-to-text Generation with Entity Modeling (2019 · 180 citations)
    Neural encoder-decoder systems that turn structured tables into text usually handle entities such as players and teams as ordinary vocabulary items.
  3. IndicBART: A Pre-trained Model for Indic Natural Language Generation (2022 · 141 citations)
    Large multilingual generation models such as mBART50 and mT5 cover Indic languages poorly. Their training data is dominated by high-resource languages, their vocabularies give small languages little room, and they are costly to fine-tune and run. The authors instead build IndicBART, a compact mBART-style…
  4. Data-to-text Generation with Macro Planning (2021 · 98 citations)
    Neural encoder-decoder systems for data-to-text generation write fluent prose. However, they often hallucinate facts, select content poorly and order it incoherently, and these problems worsen in long, multi-paragraph outputs such as sports reports. Puduppully and Lapata revisit the classic pipeline idea of…

All works

8 works of theirs in our library, the most cited first; 4 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. Data-to-text Generation with Entity ModelingRatish Puduppully, Li Dong, Mirella LapataAnnual Meeting of the Association for… · 180 citations
  3. Airavata: Introducing Hindi Instruction-tuned LLM (original ↗)Jay Gala et al.2024 · arXiv:2401.15006 · 31 citations · no summary yet
  4. Transition-Based Syntactic Linearization with Lookahead Features (original ↗)Ratish Puduppully, Yue Zhang, Manish Shrivastava2016 · Proceedings of the 2016 Conference of the North… · 30 citations · no summary yet
  5. How Good is Zero-Shot MT Evaluation for Low Resource Indian Languages? (original ↗)Anushka Singh et al.2024 · Proceedings of the 62nd Annual Meeting of the… · 15 citations · no summary yet
  6. The Reasoning Lingua Franca: A Double-Edged Sword for Multilingual AI (original ↗)Alan Saji et al.2026 · Proceedings of the 19th Conference of the… · 3 citations · no summary yet

 Co-authors here

10 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 395 times (of the 141,840 papers whose bibliographies we read); 24 citing papers with a page here →.

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