--- title: "Prem Natarajan — author profile and papers" description: "Prem Natarajan, Broad Institute: 3 papers on Elamur Research (2020–2022), h-index 39 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/prem-natarajan/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/prem-natarajan/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Prem Natarajan # Prem Natarajan 3 papers on this site · 2020–2022 current affiliation [Broad Institute](https://md.research.elamur.ai/free/en/labs/broad-institute/), Cambridge, United States; [University of Southern California](https://md.research.elamur.ai/free/en/universities/university-of-southern-california/), Los Angeles, United States; [Harvard University](https://md.research.elamur.ai/free/en/universities/harvard-university/), Cambridge, United States; [Yale University](https://md.research.elamur.ai/free/en/universities/yale-university/), New Haven, United States; [Massachusetts General Hospital](https://md.research.elamur.ai/free/en/hospitals/massachusetts-general-hospital/), Boston, United States; [Mass General Brigham](https://ror.org/04py2rh25), Boston, United States Prem Natarajan has 3 papers on this site, in 2020–2022, most of them on [Text generation](https://md.research.elamur.ai/free/en/topics/text-generation/), [Information extraction](https://md.research.elamur.ai/free/en/topics/information-extraction/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Kai-Wei Chang](https://md.research.elamur.ai/free/en/authors/kai-wei-chang/), [Nanyun Peng](https://md.research.elamur.ai/free/en/authors/nanyun-peng/), [Emily Sheng](https://md.research.elamur.ai/free/en/authors/emily-sheng/). [OpenAlex](https://openalex.org/A5066184920) · [ORCID](https://orcid.org/0000-0002-4386-6651) · [**h-index 39**](https://openalex.org/authors/A5066184920) · [277 works](https://openalex.org/works?filter=author.id:A5066184920) · [8 169 citations](https://openalex.org/works?filter=author.id:A5066184920&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [3 works on this site](https://md.research.elamur.ai/free/en/authors/prem-natarajan/#papers) · [706 citations in our library](https://md.research.elamur.ai/free/en/authors/prem-natarajan/cited-by/) · 4 more works in our library The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Prem+Natarajan) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Prem+Natarajan) · [dblp](https://dblp.org/search?q=Prem+Natarajan) · [ACL Anthology](https://aclanthology.org/search/?q=Prem+Natarajan) ## Affiliations - [University of Southern California](https://md.research.elamur.ai/free/en/universities/university-of-southern-california/) · Los Angeles, United States —current · 2006–2026 on 77 papers - [Yale University](https://md.research.elamur.ai/free/en/universities/yale-university/) · New Haven, United States —current · 2026 on 3 papers - [Harvard University](https://md.research.elamur.ai/free/en/universities/harvard-university/) · Cambridge, United States —current · 2026 on 2 papers - [Broad Institute](https://md.research.elamur.ai/free/en/labs/broad-institute/) · Cambridge, United States —current - [Mass General Brigham](https://ror.org/04py2rh25) · Boston, United States —current - [Massachusetts General Hospital](https://md.research.elamur.ai/free/en/hospitals/massachusetts-general-hospital/) · Boston, United States —current - [Natera (United States)](https://ror.org/02anzyy56) · San Carlos, United States —2018–2025 on 3 papers - [Ramakrishna Mission Vivekananda College](https://ror.org/01vemrn05) · Chennai, India —2000–2025 on 2 papers - [Amazon (United States)](https://md.research.elamur.ai/free/en/companies/amazon/) · Seattle, United States —2018–2023 on 12 papers - [Saveetha University](https://ror.org/0034me914) · Chennai, India —2021–2022 on 2 papers From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 10 more institutions on single bylines are not listed. ## Topics [Text generation 2](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Information extraction 1](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Bias, fairness & safety 1](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) ## Works by year ### 2020s [**2022** 1 paper](https://md.research.elamur.ai/free/en/papers/hsu-2022-degree-data-efficient-generation-based/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/) · [**2020** 1 paper](https://md.research.elamur.ai/free/en/papers/sheng-2020-controllable-biases-language-generation/) ## Papers The most cited first (OpenAlex and our library). 1. **[Societal Biases in Language Generation: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/)** *(2021 · 252 citations)* Generation systems such as GPT-2, GPT-3 and chat bots interact directly with users. When their outputs are skewed against demographic groups, the harm to marginalized communities can be more immediate than biases hidden inside classification models. Sheng et al. present what they call the first comprehensive survey… 2. **[DEGREE: A Data-Efficient Generation-Based Event Extraction Model](https://md.research.elamur.ai/free/en/papers/hsu-2022-degree-data-efficient-generation-based/)** *(2022 · 227 citations)* Annotating events (triggers plus role-labelled arguments) is costly. ACE 2005, for instance, needed two rounds of expert annotation. This makes it hard to extend event extraction (EE) to new domains and event types. DEGREE addresses low-resource, end-to-end EE by recasting it as conditional text generation. The model… 3. **[Towards Controllable Biases in Language Generation](https://md.research.elamur.ai/free/en/papers/sheng-2020-controllable-biases-language-generation/)** *(2020 · 166 citations)* The paper addresses societal bias in natural language generation, where model outputs can shape how people perceive demographic groups. ## Also in our library 4 more works of theirs are in our library without a page here yet; they will appear as we publish them. ## Co-authors here 6 co-authors with a page, the most papers together first. - [Kai-Wei Chang](https://md.research.elamur.ai/free/en/authors/kai-wei-chang/) ×3 - [Nanyun Peng](https://md.research.elamur.ai/free/en/authors/nanyun-peng/) ×3 - [Emily Sheng](https://md.research.elamur.ai/free/en/authors/emily-sheng/) ×2 - [I-Hung Hsu](https://md.research.elamur.ai/free/en/authors/i-hung-hsu/) - [Kuan-Hao Huang](https://md.research.elamur.ai/free/en/authors/kuan-hao-huang/) - [Scott Miller](https://md.research.elamur.ai/free/en/authors/scott-miller/) ## Cited by Papers of our library cite their works 706 times (of the 140 884 papers whose bibliographies we read); [71 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/prem-natarajan/cited-by/).