activity
20212025
most citedBeyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

565 citations · 2.2k across the 25 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CY2024★ 8 cited

Clio: Privacy-Preserving Insights into Real-World AI Use

Alex Tamkin, Miles McCain, Kunal Handa +18

How are AI assistants being used in the real world? While model providers in theory have a window into this impact via their users' data, both privacy concerns and practical challe…

cs.LG2024★ 2 cited

Sabotage Evaluations for Frontier Models

Joe Benton, Misha Wagner, Eric Christiansen +13

Sufficiently capable models could subvert human oversight and decision-making in important contexts. For example, in the context of AI development, models could covertly sabotage e…

cs.CY2024★ 3 cited

How will advanced AI systems impact democracy?

Christopher Summerfield, Lisa Argyle, Michiel Bakker +20

Advanced AI systems capable of generating humanlike text and multimodal content are now widely available. In this paper, we discuss the impacts that generative artificial intellige…

cs.AI2024★ 73 cited

Collective Constitutional AI: Aligning a Language Model with Public Input

Saffron Huang, Divya Siddarth, Liane Lovitt +4

There is growing consensus that language model (LM) developers should not be the sole deciders of LM behavior, creating a need for methods that enable the broader public to collect…

cs.CR2024★ 39 cited

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Evan Hubinger, Carson Denison, Jesse Mu +36

Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when giv…