2 citations · 3 across the 7 of their papers we have counts for
8 papers
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…
AI Security Leaderboard: Methodology, Results and Minimal Standard
Jasper Timm, Lukas Struppek, Ziwei Xu +12
The AI Security Leaderboard is an independent benchmark that ranks the safeguards of frontier AI models from least to most secure. It tests models against the FARAI Minimal Stan…
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…
ZeroDayBench: Evaluating LLM Agents on Unseen Zero-Day Vulnerabilities for Cyberdefense
Nancy Lau, Louis Sloot, Jyoutir Raj +6
Large language models (LLMs) are increasingly being deployed as software engineering agents that autonomously contribute to repositories. A major benefit these agents present is th…
WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference
Sihan Chen, Dan Zhao, Jongwoo Ko +5
The growing computational demands of large language models (LLMs) make efficient inference and activation strategies increasingly critical. While recent approaches, such as Mixture…
WinClick: GUI Grounding with Multimodal Large Language Models
Zheng Hui, Yinheng Li, Dan zhao +3
Graphical User Interface (GUI) tasks are vital for automating workflows such as software testing, user interface navigation. For users, the GUI is the most intuitive platform for i…
VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Tasks
Lawrence Jang, Yinheng Li, Dan Zhao +5
Videos are often used to learn or extract the necessary information to complete tasks in ways different than what text and static imagery alone can provide. However, many existing…
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci +9
Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning…