activity
20162026
most citedGaussian Error Linear Units (GELUs)

3.2k citations · 9.8k across the 51 of their papers we have counts for

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Showing cs.CYShow all

8 papers · 1 filter

cs.CY2026

Open Technical Problems in Open-Weight AI Model Risk Management

Stephen Casper, Kyle O'Brien, Shayne Longpre +19

Frontier AI models with openly available weights are steadily becoming more powerful and widely adopted. However, compared to proprietary models, open-weight models pose different…

cs.CY2023★ 22 cited

AI Deception: A Survey of Examples, Risks, and Potential Solutions

Peter S. Park, Simon Goldstein, Aidan O'Gara +2

This paper argues that a range of current AI systems have learned how to deceive humans. We define deception as the systematic inducement of false beliefs in the pursuit of some ou…

cs.CY2023★ 57 cited

An Overview of Catastrophic AI Risks

Dan Hendrycks, Mantas Mazeika, Thomas Woodside

Rapid advancements in artificial intelligence (AI) have sparked growing concerns among experts, policymakers, and world leaders regarding the potential for increasingly advanced AI…

cs.CY2023★ 16 cited

Natural Selection Favors AIs over Humans

Dan Hendrycks

For billions of years, evolution has been the driving force behind the development of life, including humans. Evolution endowed humans with high intelligence, which allowed us to b…

cs.CY2022★ 8 cited

Actionable Guidance for High-Consequence AI Risk Management: Towards Standards Addressing AI Catastrophic Risks

Anthony M. Barrett, Dan Hendrycks, Jessica Newman +1

Artificial intelligence (AI) systems can provide many beneficial capabilities but also risks of adverse events. Some AI systems could present risks of events with very high or cata…

cs.CY2022★ 18 cited

X-Risk Analysis for AI Research

Dan Hendrycks, Mantas Mazeika

Artificial intelligence (AI) has the potential to greatly improve society, but as with any powerful technology, it comes with heightened risks and responsibilities. Current AI rese…

cs.CY2020★ 290 cited

Measuring Massive Multitask Language Understanding

Dan Hendrycks, Collin Burns, Steven Basart +4

We propose a new test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attai…

cs.CY2020★ 100 cited

Aligning AI With Shared Human Values

Dan Hendrycks, Collin Burns, Steven Basart +4

We show how to assess a language model's knowledge of basic concepts of morality. We introduce the ETHICS dataset, a new benchmark that spans concepts in justice, well-being, dutie…