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researcher

M. Andersch

10 papers hereh-index 12897 citations23 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7
  • last author1

Across the 8 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG4
  • cs.DC1
  • cs.NE1

identity via Semantic Scholar / OpenAlex

activity
20182026
most citedReducing Activation Recomputation in Large Transformer Models

55 citations · 58 across the 10 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

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

NVIDIA, :, Aaron Blakeman +572

We introduce Nemotron 3 Ultra, a 550 billion total and 55 billion active parameter Mixture-of-Experts Hybrid Mamba-Attention language model. We pre-trained Nemotron 3 Ultra on 20 t…

cs.CL2025★ 1 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

Pretraining Large Language Models with NVFP4

NVIDIA, Felix Abecassis, Anjulie Agrusa +87

Large Language Models (LLMs) today are powerful problem solvers across many domains, and they continue to get stronger as they scale in model size, training set size, and training…

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…

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