3 citations · 7 across the 5 of their papers we have counts for
5 papers
Pressure Reveals Character: Behavioural Alignment Evaluation at Depth
Nora Petrova, John Burden
Evaluating alignment in language models requires testing how they behave under realistic pressure, not just what they claim they would do. While alignment failures increasingly cau…
I Spy With My Model's Eye: Visual Search as a Behavioural Test for MLLMs
John Burden, Jonathan Prunty, Ben Slater +3
Multimodal large language models (MLLMs) achieve strong performance on vision-language tasks, yet their visual processing is opaque. Most black-box evaluations measure task accurac…
Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibility
Maurice Chiodo, Dennis Müller, Paul Siewert +3
We use the notion of oracle machines and reductions from computability theory to formalise different Human-in-the-loop (HITL) setups for AI systems, distinguishing between trivial…
Framing the Game: How Context Shapes LLM Decision-Making
Isaac Robinson, John Burden
Large Language Models (LLMs) are increasingly deployed across diverse contexts to support decision-making. While existing evaluations effectively probe latent model capabilities, t…
Evaluating AI Evaluation: Perils and Prospects
John Burden
As AI systems appear to exhibit ever-increasing capability and generality, assessing their true potential and safety becomes paramount. This paper contends that the prevalent evalu…