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20202026
most citedNemotron-4 340B Technical Report

7 citations · 29 across the 20 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.AI2026

MLLMs Fail to Refuse when Using Tools Agentically

Rikiya Takehi, Ryo Hachiuma, Shaona Ghosh +3

Agentic multimodal large language models (MLLMs) have recently pushed the frontier of visual reasoning by calling tools such as zooming and tagging. Despite the recent strong succe…

cs.AI2026

MLCommons Jailbreak Benchmark v1.0

Carsten Maple, Cagatay Yucel, Isaac Holeman +33

Modern AI systems are designed to refuse hazardous requests. A jailbreak is a prompt crafted to bypass those safeguards and elicit outputs that the system would normally refuse to…

cs.AI2026

Nemotron 3.5 Content Safety Moderator: A Compact Multimodal, Multilingual, and Reasoning Enabled Content Safety Moderator

Varun Singh, Anuj Doshi, Makesh Narsimhan Sreedhar +2

Safety moderation for deployed AI applications is moving beyond text-only prompts: systems increasingly need to judge images, documents, screenshots, and generated responses under…

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.LG2026

Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence

NVIDIA, :, Amala Sanjay Deshmukh +204

We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 N…

cs.CR2026★ 1 cited

Architecting Secure AI Agents: Perspectives on System-Level Defenses Against Indirect Prompt Injection Attacks

Chong Xiang, Drew Zagieboylo, Shaona Ghosh +5

AI agents, predominantly powered by large language models (LLMs), are vulnerable to indirect prompt injection, in which malicious instructions embedded in untrusted data can trigge…

cs.CY2026★ 1 cited

Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions

Saleh Afroogh, Syed Ishtiaque Ahmed, Petra Ahrweiler +46

This study provides a cross-disciplinary examination of Explainable Artificial Intelligence (XAI) approaches-focusing on deep neural networks (DNNs) and large language models (LLMs…