Ruaridh Mon-Williams — accepted AI-conference papers

2025

Learning Precise Affordances from Egocentric Videos for Robotic Manipulation

Gen Li, Nikolaos Tsagkas, Jifei Song, Ruaridh Mon-Williams, Sethu Vijayakumar, Kun Shao +1

ICCV 2025poster

Affordance, defined as the potential actions that an object offers, is crucial for embodied AI agents. For example, such knowledge directs an agent to grasp a knife by the handle for cutting or by the blade for safe handover. While existing approaches have made notable progress, affordance research…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2025

Partner Modelling Emerges in Recurrent Agents (But Only When It Matters)

Ruaridh Mon-Williams, Max Taylor-Davies, Elizabeth Mieczkowski, Natalia Vélez, Neil R Bramley, Yanwei Wang +2

NeurIPS 2025poster

Humans are remarkably adept at collaboration, able to infer the strengths and weaknesses of new partners in order to work successfully towards shared goals. To build AI systems with this capability, we must first understand its building blocks: does such flexibility require explicit, dedicated mecha…

Cited by 0 Source ↗Scholar ↗