6 citations · 19 across the 14 of their papers we have counts for
7 papers · 1 filter
Improving Evaluation Realism with Inference-Time Compute and Deployment Scaffolds
Axel Ahlqvist, Richard Guan, Juan-Pablo Rivera +6
A core obstacle to alignment evaluation is evaluation awareness: capable models can tell when they are being tested rather than deployed, weakening the conclusions a safety evaluat…
EvalDetectBench: A Benchmark for Measuring Evaluation Awareness in Frontier Language Models
Xinning Li, Kemunto Ochwang'i, Aryasomayajula Ram Bharadwaj +2
Frontier large language models can often recognize when they are being evaluated, a capability known as evaluation awareness. If models behave differently in evaluations than in de…
Prefill Awareness in Large Language Models
Andy Wang, Parv Mahajan, David Demitri Africa +3
Safety-relevant studies of language models, including alignment and jailbreaking evaluations and AI control protocols, often rely on prefilling model outputs. If AI models can reco…
Evaluating whether AI models would sabotage AI safety research
Robert Kirk, Alexandra Souly, Kai Fronsdal +2
We evaluate the propensity of frontier models to sabotage or refuse to assist with safety research when deployed as AI research agents within a frontier AI company. We apply two co…
Seven simple steps for log analysis in AI systems
Magda Dubois, Ekin Zorer, Maia Hamin +17
AI systems produce large volumes of logs as they interact with tools and users. Analysing these logs can help understand model capabilities, propensities, and behaviours, or assess…
UK AISI Alignment Evaluation Case-Study
Alexandra Souly, Robert Kirk, Jacob Merizian +2
This technical report presents methods developed by the UK AI Security Institute for assessing whether advanced AI systems reliably follow intended goals. Specifically, we evaluate…
When Do LLM Preferences Predict Downstream Behavior?
Katarina Slama, Alexandra Souly, Dishank Bansal +3
Preference-driven behavior in LLMs may be a necessary precondition for AI misalignment such as sandbagging: models cannot strategically pursue misaligned goals unless their behavio…