--- title: "Alex Kondratenko — author profile and papers · Reasoning" description: "Alex Kondratenko: 2 papers on Elamur Research (2025), h-index 1 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/alex-kondratenko/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/alex-kondratenko/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Alex Kondratenko # Alex Kondratenko Alex Kondratenko has 2 papers in our library, in 2025, most of them on [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Abhinav Khattar](https://md.research.elamur.ai/free/en/authors/abhinav-khattar/), [Akhiad Bercovich](https://md.research.elamur.ai/free/en/authors/akhiad-bercovich/), [Aleksander Ficek](https://md.research.elamur.ai/free/en/authors/aleksander-ficek/). 2 papers in our library · 2025 [OpenAlex](https://openalex.org/A5121334375) · [**h-index 1**](https://openalex.org/authors/A5121334375) · [4 works](https://openalex.org/works?filter=author.id:A5121334375) · [1 citations](https://openalex.org/works?filter=author.id:A5121334375&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/alex-kondratenko/#papers) · [🔗 Cited 66 times in our library](https://md.research.elamur.ai/free/en/authors/alex-kondratenko/cited-by/) · [⭐ Paper Stars ranking: #7407](https://md.research.elamur.ai/free/en/paper-stars/page/75/#star-7407) 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=Alex+Kondratenko) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Alex+Kondratenko) · [dblp](https://dblp.org/search?q=Alex+Kondratenko) · [ACL Anthology](https://aclanthology.org/search/?q=Alex+Kondratenko) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 2 Research subjects and languages the work is about.[Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2025** 2 papers](https://md.research.elamur.ai/free/en/authors/alex-kondratenko/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)** *(2025 · 39 citations)* Reasoning models spend most of their compute producing long chains of thought. In standard Transformers, the attention KV cache makes such long generations slow and memory-hungry. NVIDIA addresses this with Nemotron-Nano-9B-v2, which uses the Nemotron-H hybrid design: most self-attention layers are replaced by… 2. **[Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)** *(2025 · 27 citations)* NVIDIA presents Nemotron 3 Nano 30B-A3B, an open language model for agentic use, reasoning and chat that aims for a better balance between accuracy and inference speed. ## Co-authors here 7 co-authors with a page, the most papers together first. - [Abhinav Khattar](https://md.research.elamur.ai/free/en/authors/abhinav-khattar/) ×2 - [Akhiad Bercovich](https://md.research.elamur.ai/free/en/authors/akhiad-bercovich/) ×2 - [Aleksander Ficek](https://md.research.elamur.ai/free/en/authors/aleksander-ficek/) ×2 - [Aaron Grattafiori](https://md.research.elamur.ai/free/en/authors/aaron-grattafiori/) - [Aarti Basant](https://md.research.elamur.ai/free/en/authors/aarti-basant/) - [Adithya Renduchintala](https://md.research.elamur.ai/free/en/authors/adithya-renduchintala/) - [NVIDIA: Aaron Blakeman](https://md.research.elamur.ai/free/en/authors/nvidia-aaron-blakeman/) ## Cited by Papers of our library cite their works 66 times (of the 149,439 papers whose bibliographies we read); [12 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/alex-kondratenko/cited-by/). Updated 30 October 2026