177 citations · 251 across the 14 of their papers we have counts for
6 papers · 1 filter
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
NVIDIA, :, Aarti Basant +214
We introduce Nemotron-Nano-9B-v2, a hybrid Mamba-Transformer language model designed to increase throughput for reasoning workloads while achieving state-of-the-art accuracy compar…
OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique
Wasi Uddin Ahmad, Somshubra Majumdar, Aleksander Ficek +6
Recent advancements in reasoning-based Large Language Models (LLMs), particularly their potential through test-time scaling, have created significant opportunities for distillation…
Llama-Nemotron: Efficient Reasoning Models
Akhiad Bercovich, Itay Levy, Izik Golan +132
We introduce the Llama-Nemotron series of models, an open family of heterogeneous reasoning models that deliver exceptional reasoning capabilities, inference efficiency, and an ope…
Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models
NVIDIA, :, Aaron Blakeman +198
As inference-time scaling becomes critical for enhanced reasoning capabilities, it is increasingly becoming important to build models that are efficient to infer. We introduce Nemo…
OpenCodeReasoning: Advancing Data Distillation for Competitive Coding
Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar +5
Since the advent of reasoning-based large language models, many have found great success from distilling reasoning capabilities into student models. Such techniques have significan…
Automatic Heteronym Resolution Pipeline Using RAD-TTS Aligners
Jocelyn Huang, Evelina Bakhturina, Oktai Tatanov
Grapheme-to-phoneme (G2P) transduction is part of the standard text-to-speech (TTS) pipeline. However, G2P conversion is difficult for languages that contain heteronyms -- words th…