3 papers
cs.CL2025
Do Large Language Models Know What They Are Capable Of?
Casey O. Barkan, Sid Black, Oliver Sourbut
We investigate whether large language models (LLMs) can predict whether they will succeed on a given task and whether their predictions improve as they progress through multi-step…
cs.AI2025
Auditing Games for Sandbagging
Jordan Taylor, Sid Black, Dillon Bowen +10
Future AI systems could conceal their capabilities ('sandbagging') during evaluations, potentially misleading developers and auditors. We stress-tested sandbagging detection techni…
cs.CR2025
RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents
Sid Black, Asa Cooper Stickland, Jake Pencharz +7
Uncontrollable autonomous replication of language model agents poses a critical safety risk. To better understand this risk, we introduce RepliBench, a suite of evaluations designe…