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Rishabh Bhardwaj

Rishabh Bhardwaj has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Bias, fairness & safety, Ancient Greek; often with Soujanya Poria.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 12 · 43 works · 577 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 137 times in our library · ⭐ Paper Stars ranking: #6859

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

🎓Nanyang Technological UniversitySingapore · Singapore2021–2026 · 3 paperscurrent🎓Singapore University of Technology and DesignSingapore · Singapore2019–2025 · 28 papers🎓National University of SingaporeSingapore · Singapore2019–2020 · 3 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.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksSafety Research · 2 worksSocial Sciences · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Bias, fairness & safety · 2 worksLanguage models & pretraining · 2 worksAncient Greek · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment (2023 · 108 citations)
    Large language models can still be pushed into producing dangerous content. Older safety probes, such as appending Chain-of-Thought cues to harmful questions, are now mostly refused by current models. The authors present Red-Eval, a red-teaming benchmark based on Chain of Utterances (CoU) prompting. The prompt stages…
  2. Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic (2024 · 59 citations)
    Fine-tuning a safety-aligned LLM on ordinary, harmless data tends to weaken its safety guardrails. The authors propose RESTA (REstoring Safety through Task Arithmetic), which repairs this damage after fine-tuning. They compute a safety vector as the weight difference between a safety-aligned base model and its…

 Co-authors here

1 co-author 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 137 times (of the 149,439 papers whose bibliographies we read); 33 citing papers with a page here →.

Updated

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