One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMO

Measuring Open-Source Llama Nemotron Models on DeepResearch Bench

The Open Evaluation Standard: Benchmarking NVIDIA Nemotron 3 Nano with NeMo Evaluator

(LoRA) Fine-Tuning FLUX.1-dev on Consumer Hardware

Accelerate your models with 🤗 Optimum Intel and OpenVINO

Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework

arXiv:2602. 18008v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promise in constructing mechanistic models from data.

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents

Accelerating PyTorch distributed fine-tuning with Intel technologies

Uncovering Hidden Leptonic Correlations with Flow Matching and Autoencoders

arXiv:2608. 15042v1 Announce Type: cross Abstract: We perform a global search for values of the Yukawa matrices and Majorana masses in the Type-I seesaw mechanism.

Fine-tuned Normalizing Flows for ALICE Zero Degree Calorimeter Fast Simulation

arXiv:2608. 12795v1 Announce Type: cross Abstract: Simulating the ALICE Zero Degree Calorimeter (ZDC) neutron detector responses at the LHC is computationally expensive, requiring complex Monte Carlo chains.

NeuroAda: Activating Each Neuron's Potential for Parameter-Efficient Fine-Tuning

arXiv:2510. 18940v2 Announce Type: replace-cross Abstract: Existing parameter-efficient fine-tuning (PEFT) methods primarily fall into two categories: addition-based and selective in-situ adaptation.

Welcome the NVIDIA Llama Nemotron Nano VLM to Hugging Face Hub