activity
20242026
most citedHumanity's Last Exam

18 citations · 18 across the 2 of their papers we have counts for

collaborators

6 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.LG202618 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1144

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…

cs.LG2026

The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems

Richard Ren, Arunim Agarwal, Mantas Mazeika +13

As large language models (LLMs) become more capable and agentic, the requirement for trust in their outputs grows significantly, yet at the same time concerns have been mounting th…

cs.LG2025

Remote Labor Index: Measuring AI Automation of Remote Work

Mantas Mazeika, Alice Gatti, Cristina Menghini +44

AIs have made rapid progress on research-oriented benchmarks of knowledge and reasoning, but it remains unclear how these gains translate into economic value and automation. To mea…

cs.LG2025

Tamper-Resistant Safeguards for Open-Weight LLMs

Rishub Tamirisa, Bhrugu Bharathi, Long Phan +12

Rapid advances in the capabilities of large language models (LLMs) have raised widespread concerns regarding their potential for malicious use. Open-weight LLMs present unique chal…

cs.LG2024

Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?

Richard Ren, Steven Basart, Adam Khoja +9

As artificial intelligence systems grow more powerful, there has been increasing interest in "AI safety" research to address emerging and future risks. However, the field of AI saf…