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Dhananjay Ram

Dhananjay Ram has 2 papers in our library, in 2018–2026, most of them on Machine translation, Language models & pretraining, Reasoning; often with James Henderson, Lesly Miculicich, Nikolaos Pappas.

2 papers in our library · 2018–2026

OpenAlex · ORCID · Wikidata · h-index 9 · 30 works · 451 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 172 times in our library · ⭐ Paper Stars ranking: #4804

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

🔬Idiap Research InstituteMartigny-Combe · Switzerland2015–2020 · 11 papers🎓École Polytechnique Fédérale de LausanneLausanne · Switzerland2016–2019 · 8 papers🏢AmazonSeattle · United States2024 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 4Research subjects and languages the work is about.Machine translation · 1 workEfficient models & compression · 1 workLanguage models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Document-Level Neural Machine Translation with Hierarchical Attention Networks (2018 · 415 citations)
    Standard NMT systems translate each sentence in isolation. This ignores discourse links and can hurt the cohesion of a translated document. The authors add document context to a Transformer through a hierarchical attention network (HAN) that reuses the model's own hidden states from the k previous sentences instead…
  2. Reinforcement-aware Knowledge Distillation for LLM Reasoning (2026 · 13 citations)
    Long chain-of-thought reasoning models trained with RL are expensive to run, so practitioners distill them into smaller students.

 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 172 times (of the 149,439 papers whose bibliographies we read); 30 citing papers with a page here →.

Updated

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