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Hareesh Bahuleyan

Hareesh Bahuleyan has 2 papers in our library, in 2019–2022, most of them on Text generation; often with Jackie Chi Kit Cheung, Kushal Arora, Layla El Asri.

2 papers in our library · 2019–2022

OpenAlex · ORCID · h-index 11 · 22 works · 564 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 193 times in our library · ⭐ Paper Stars ranking: #3451

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

🎓Indian Institute of Technology MadrasChennai · India2016–2021 · 6 papers🎓University of WaterlooWaterloo · Canada2017–2019 · 5 papers🏢BorealisVienna · Austria2021 · 2 papers🎓University of WindsorWindsor · Canada2021 · 2 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.

 Concepts, shelves and topics

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

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Text generation · 1 work

 Works by year

2020s

20221 paperWhy Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation

2010s

20191 paperDisentangled Representation Learning for Non-Parallel Text Style Transfer

 Papers

The most cited first (OpenAlex and our library).

  1. Disentangled Representation Learning for Non-Parallel Text Style Transfer (2019 · 397 citations)
    The paper tackles separating style from content inside the latent vector of a neural text generator, so sentences can be rewritten in a different style without parallel training pairs.
  2. Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation (2022 · 80 citations)
    Neural text generators often produce repetitive, dull, incoherent or hallucinated output. A common explanation is exposure bias: models trained with teacher forcing always see gold contexts during training, but at generation time they condition on their own earlier predictions. Whether this mismatch actually harms…

 Co-authors here

5 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 193 times (of the 141,840 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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