🧑‍🔬 Sumanth Dathathri

Affiliations

• Google DeepMind (United Kingdom) · London, United Kingdom — current · 2024–2026 on 3 papers
• California Institute of Technology · Pasadena, United States — 2016–2021 on 15 papers
• Hong Kong University of Science and Technology · Hong Kong, Hong Kong — 2019–2020 on 2 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.

Topics

Language models & pretraining2Text generation1

Papers

The most cited first (OpenAlex and our library).

1. Plug and Play Language Models: A Simple Approach to Controlled Text Generation (2019 · 562 citations)
   Large pretrained Transformer language models write fluent text, but steering what they produce, such as the topic or sentiment, usually means changing the architecture or retraining on labelled data.
2. Challenges in Detoxifying Language Models (2021 · 206 citations)
   This DeepMind study asks how well current detoxification methods for English language models (LMs) actually work, and what they cost.

Co-authors here

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

• Amelia Glaese
• Andrea Madotto
• Jason Yosinski
• Johannes Welbl
• John Mellor
• Jonathan Uesato
• Lisa Anne Hendricks
• Po-Sen Huang
• Pushmeet Kohli
• Rosanne Liu

Cited by

Papers of our library cite their works 749 times (of the 140 884 papers whose bibliographies we read); 92 citing papers with a page here →.

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