Meriem Boubdir

collaborators

4 papers

cs.CL2026

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

NVIDIA, :, Aaron Blakeman +571

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.CL2026

Detecting Data Contamination in LLMs via In-Context Learning

MichaÅ Zawalski, Meriem Boubdir, Klaudia BaÅazy +2

We present Contamination Detection via Context (CoDeC), a practical and accurate method to detect and quantify training data contamination in large language models. CoDeC distingui…

cs.CL2025

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…

hep-ex2025

Measurements of charm mixing and $C P$ violation using $D^{0} \to K^{\pm} I ¨ ^{\mp}$ decays

LHCb collaboration, R. Aaij, B. Adeva +766

Measurements of charm mixing and $C P$ violation parameters from the decay-time-dependent ratio of $D^{0} \to K^{+} I ¨ ^{-}$ to $D^{0} \to K^{-} I ¨ ^{+}$ decay rates and the charge-conjugat…

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

Detecting Data Contamination in LLMs via In-Context Learning

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

Measurements of charm mixing and CP violation using D0→K±I¨∓ decays

Measurements of charm mixing and $C P$ violation using $D^{0} \to K^{\pm} I ¨ ^{\mp}$ decays