activity
20182026
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 2.9k across the 34 of their papers we have counts for

collaborators
Showing 2025Show all

9 papers · 1 filter

cs.CR2025

Best Practices for Biorisk Evaluations on Open-Weight Bio-Foundation Models

Boyi Wei, Zora Che, Nathaniel Li +10

Open-weight bio-foundation models present a dual-use dilemma. While holding great promise for accelerating scientific research and drug development, they could also enable bad acto…

cs.LG2025★ 3 cited

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.AI2025★ 3 cited

A Definition of AGI

Dan Hendrycks, Dawn Song, Christian Szegedy +30

The lack of a concrete definition for Artificial General Intelligence (AGI) obscures the gap between today's specialized AI and human-level cognition. This paper introduces a quant…

cs.CL2025

MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

Yu Ying Chiu, Michael S. Lee, Rachel Calcott +17

As AI systems progress, we rely more on them to make decisions with us and for us. To ensure that such decisions are aligned with human values, it is imperative for us to understan…

cs.AI2025

TextQuests: How Good are LLMs at Text-Based Video Games?

Long Phan, Mantas Mazeika, Andy Zou +1

Evaluating AI agents within complex, interactive environments that mirror real-world challenges is critical for understanding their practical capabilities. While existing agent ben…

cs.LG2025★ 1 cited

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

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs

Mantas Mazeika, Xuwang Yin, Rishub Tamirisa +8

As AIs rapidly advance and become more agentic, the risk they pose is governed not only by their capabilities but increasingly by their propensities, including goals and values. Tr…

cs.CY2025★ 15 cited

International AI Safety Report

Yoshua Bengio, Sören Mindermann, Daniel Privitera +93

The first International AI Safety Report comprehensively synthesizes the current evidence on the capabilities, risks, and safety of advanced AI systems. The report was mandated by…

cs.LG2025★ 23 cited

Humanity's Last Exam

Long Phan, Alice Gatti, Ziwen Han +1168

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…