3 papers
cs.CL2025
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…
cs.CL2024
NVLM: Open Frontier-Class Multimodal LLMs
Wenliang Dai, Nayeon Lee, Boxin Wang +7
We introduce NVLM 1.0, a family of frontier-class multimodal large language models (LLMs) that achieve state-of-the-art results on vision-language tasks, rivaling the leading propr…
cs.LG2024
PHI-S: Distribution Balancing for Label-Free Multi-Teacher Distillation
Mike Ranzinger, Jon Barker, Greg Heinrich +3
Various visual foundation models have distinct strengths and weaknesses, both of which can be improved through heterogeneous multi-teacher knowledge distillation without labels, te…