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Gautam Siddharth Kashyap

Gautam Siddharth Kashyap has 4 papers in our library, in 2026, most of them on Language models & pretraining, Question answering, Low-resource languages; often with Usman Naseem, Rafiq Ali, Sushant Kumar Ray.

4 papers in our library · 2026

OpenAlex · ORCID · h-index 16 · 71 works · 1,047 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 3 times in our library · ⭐ Paper Stars ranking: #10475

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

🎓Macquarie UniversitySydney · Australia2025–2026 · 15 papersEducation since 2025 · PhD Computer ScienceEmploymentcurrent🎓Jamia HamdardNew Delhi · India2018–2025 · 11 papersEducation 2018–2021 · BSc Computer ScienceEducation 2021–2023 · Master of Computer Applications🎓Indraprastha Institute of Information Technology DelhiDelhi · India2023–2025 · 6 papersEmployment 2023–2024 · Research Assistant
🏛️Microsoft Inc.Texas, USA · United States2024Employment 2024 · Research Assistant
🏛️Tech Mahindra (Americas) IncTexas, USA · United States2024Employment 2024 · Research Assistant
🎓University of StirlingStirling · United Kingdom2021–2023Employment 2021–2023 · Research Assistant
🏛️Upwork Global IncNew Delhi · India2021Employment since 2021 · Freelance Researcher
🏛️Recon AppMagic Pvt. LtdNew Delhi · India2018Employment 2018 · Intern Web Developer
🏛️TTE Delhi (WCSC)New Delhi · India2017–2018Education 2017–2018 · Certificate in Software Testing
🏛️Vandana International SchoolNew Delhi · India2014–2017Education 2014–2015 · O-Levels/10th CBSE BoardEducation 2016–2017 · A-Levels/12th CBSE Board

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Do Large Language Models Reflect Demographic Pluralism in Safety? (2026 · 3 citations)
    Safety judgments about LLM outputs differ across communities, yet widely used alignment resources such as ANTHROPIC-HH and DICES draw on narrow annotator pools.
  2. Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning? (2026 · 1 citation)
    The paper questions a common assumption in industrial clinical question answering (CQA): that a model must be fine-tuned on medical data to perform well.
  3. MaiBERT: A Pre-training Corpus and Language Model for Low-Resourced Maithili Language (2026 · 1 citation)
    Maithili, an Indo-Aryan language spoken by millions in Nepal's Terai and in Bihar, has almost no pretrained models or standard datasets.
  4. Are Large Language Models Economically Viable for Industry Deployment? (2026)
    Industry teams choosing an LLM must weigh energy, latency, hardware use and cost, but common benchmarks report mostly accuracy.

 Co-authors here

8 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 3 times (of the 149,439 papers whose bibliographies we read).

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