🔗 Who cites «Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models»

38 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · ← back to «Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models»

1. Llama-Nemotron: Efficient Reasoning ModelsarXiv:2505.00949Akhiad Bercovich, Itay Levy, Izik Golan, et al.2025 · 76 citations
2. Kimi Linear: An Expressive, Efficient Attention ArchitecturearXiv:2510.26692Kimi Team, Yu Zhang, Zongyu Lin, et al.2025 · 51 citations
3. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning ModelarXiv:2508.14444NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.2025 · 39 citations
4. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
5. Nemotron-CrossThink: Scaling Self-Learning beyond Math ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.2026 · 9 citations
6. A Sovereign, Open-Source Foundation Model for German and EnglisharXiv:2607.09424Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.2026 · 2 citations
7. EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.2026
8. Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid ArchitecturesFindings of the Association for Computational LinguisticsShenran Wang, Timothy Tin-Long Tse, Jian Zhu2026
9. XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake DetectionFindings of the Association for Computational LinguisticsKwok-Ho Ng, Tingting Song, Yongdong WU, et al.2026

29 more papers of our library cite it; they have no page here yet.

This page in Markdown → https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/cited-by/