🧑‍🔬 Oleksii Kuchaiev

🏛️ Affiliations

🎓University of California, BerkeleyBerkeley · United States2026 · 1 papercurrent🎓University of California, IrvineIrvine · United States2008–2011 · 11 papers🏢NvidiaSanta Clara · United States2019–2025 · 10 papers🏢NvidiaReading · United Kingdom2020–2025 · 5 papers🎓University of Wisconsin SystemMadison · United States2023 · 2 papers🏢MicrosoftRedmond · United States2013–2014 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. NeMo: a toolkit for building AI applications using Neural Modules (2019 · 244 citations)
   Deep learning code is usually built around raw tensors whose axes have no declared meaning. Architecture, training logic and infrastructure also tend to end up tangled in one script, so combining components from different authors is fragile and requires debugging. The authors present NeMo, an open-source Python…
2. HelpSteer2: Open-source dataset for training top-performing reward models (2024 · 82 citations)
   Reward models that steer LLMs toward human-preferred outputs need good preference data. Openly licensed collections such as HH-RLHF, Open Assistant and HelpSteer have aged, and sets distilled from GPT-4 and similar proprietary systems carry commercial-use restrictions. The NVIDIA authors address this gap with…
3. HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM (2024 · 72 citations)
   Open helpfulness preference datasets usually give only an overall rating or a pairwise ranking. They do not say why one answer is better, so trained models can pick up shallow cues, such as preferring longer replies whether or not they are useful. The NVIDIA team built HelpSteer to address this. It is a…

All works

6 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Jasper: An End-to-End Convolutional Neural Acoustic Model ↗Interspeech (USB) · no summary yetJason Li et al.2019 · 263 citations
2. NeMo: a toolkit for building AI applications using Neural ModulesarXiv:1909.09577Oleksii Kuchaiev, Jason Li, Huyen Nguyen, et al.2019 · 244 citations
3. HelpSteer2: Open-source dataset for training top-performing reward modelsarXiv:2406.08673Zhilin Wang, Yi Dong, Olivier Delalleau, et al.2024 · 82 citations
4. HelpSteer: Multi-attribute Helpfulness Dataset for SteerLMConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Zhilin Wang, Yi Dong, Jiaqi Zeng, et al.2024 · 72 citations
5. HelpSteer2-Preference: Complementing Ratings with Preferences ↗arXiv:2410.01257 · no summary yetZhilin Wang et al.2024 · 57 citations
6. Before They Can Solve: Predicting Post-Training Coding-Agent Performance from Base Models ↗arXiv (Cornell University) · no summary yetTan Yu et al.2026

🤝 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

• Daniel Egert ×2
• Jiaqi Zeng ×2
• Makesh Narsimhan Sreedhar ×2
• Olivier Delalleau ×2
• Yi Dong ×2
• Zhilin Wang ×2
• Aidan Swope
• Boris Ginsburg
• Gerald Shen
• Huyen Nguyen
• Neel Kant
• Oleksii Hrinchuk

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference of the North American Chapter of the Association for Computational Linguistics (NAACL): NAACL 2024
• Interspeech (USB)

🔗 Cited by

Papers of our library cite their works 605 times (of the 149,439 papers whose bibliographies we read); 141 citing papers with a page here →.

Updated 2 November 2026

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