3 citations · 7 across the 5 of their papers we have counts for
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cs.CV2025★ 1 cited
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…
cs.CY2025★ 3 cited
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…
cs.CL2025
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…