activity
20242026
most citedNVIDIA Nemotron 3: Efficient and Open Intelligence

1 citations · 1 across the 7 of their papers we have counts for

collaborators

12 papers

cs.CL2026

CRoCoDiL: Continuous and Robust Conditioned Diffusion for Language

Roy Uziel, Omer Belhasin, Itay Levy +4

Masked Diffusion Models (MDMs) provide an efficient non-causal alternative to autoregressive generation but often struggle with token dependencies and semantic incoherence due to t…

cs.LG2026

Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aakshita Chandiramani +544

We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…

cs.CV2026

Wid3R: Wide Field-of-View 3D Reconstruction via Camera Model Conditioning

Dongki Jung, Jaehoon Choi, Adil Qureshi +3

We present Wid3R, a feed-forward neural network for multi-view visual geometry reconstruction that supports wide field-of-view camera models. Unlike existing methods that assume re…

cs.CL20251 cited

NVIDIA Nemotron 3: Efficient and Open Intelligence

NVIDIA, :, Aaron Blakeman +356

We introduce the Nemotron 3 family of models - Nano, Super, and Ultra. These models deliver strong agentic, reasoning, and conversational capabilities. The Nemotron 3 family uses a…

cs.CL2025

Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aaron Blakeman +311

We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. Nemotron 3 Nano was pretrained on 25 trillion text tokens, including more than 3 t…

cs.CV2025

Advancing Image Classification with Discrete Diffusion Classification Modeling

Omer Belhasin, Shelly Golan, Ran El-Yaniv +1

Image classification is a well-studied task in computer vision, and yet it remains challenging under high-uncertainty conditions, such as when input images are corrupted or trainin…