Waleffe, Roger

An Empirical Study of Mamba-based Language Models

Waleffe, R., Byeon, W., Riach, D., Norick, B., Korthikanti, V., Dao, T., Gu, A., Hatamizadeh, A., Singh, S., Narayanan, D., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

Llama-Nemotron: Efficient Reasoning Models

Bercovich, A., Levy, I., Golan, I., Dabbah, M., El-Yaniv, R., Puny, O., Galil, I., Moshe, Z., Ronen, T., Nabwani, N., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

LatentMoE: Toward Optimal Accuracy per FLOP and Parameter in Mixture of Experts

Elango, V., Bhatia, N., Waleffe, R., Shafipour, R., Asida, T., Khattar, A., Assaf, N., Golub, M., Guman, J., Mitra, T., et al. (2026) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0

Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

NVIDIA, :, Blakeman, A., Basant, A., Khattar, A., Renduchintala, A., Bercovich, A., Ficek, A., Bjorlin, A., Taghibakhshi, A., et al. (2025) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0