1 citations · 1 across the 11 of their papers we have counts for
11 papers
Ontology-Guided Diffusion for Zero-Shot Visual Sim2Real Transfer
Mohamed Youssef, Mayar Elfares, Anna-Maria Meer +2
Bridging the simulation-to-reality (sim2real) gap remains challenging as labelled real-world data is scarce. Existing diffusion-based approaches rely on unstructured prompts or sta…
ToM-SSI: Evaluating Theory of Mind in Situated Social Interactions
Matteo Bortoletto, Constantin Ruhdorfer, Andreas Bulling
Most existing Theory of Mind (ToM) benchmarks for foundation models rely on variations of the Sally-Anne test, offering only a very limited perspective on ToM and neglecting the co…
ProToM: Promoting Prosocial Behaviour via Theory of Mind-Informed Feedback
Matteo Bortoletto, Yichao Zhou, Lance Ying +2
While humans are inherently social creatures, the challenge of identifying when and how to assist and collaborate with others - particularly when pursuing independent goals - can h…
The Yokai Learning Environment: Tracking Beliefs Over Space and Time
Constantin Ruhdorfer, Matteo Bortoletto, Johannes Forkel +2
The ability to cooperate with unknown partners is a central challenge in cooperative AI and widely studied in the form of zero-shot coordination (ZSC), which evaluates an algorithm…
Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
Constantin Ruhdorfer, Matteo Bortoletto, Victor Oei +2
We introduce Unsupervised Partner Design (UPD), a population-free multi-agent reinforcement learning method for robust ad-hoc teamwork. UPD generates training partners on-the-fly a…
Explicit Modelling of Theory of Mind for Belief Prediction in Nonverbal Social Interactions
Matteo Bortoletto, Constantin Ruhdorfer, Lei Shi +1
We propose MToMnet - a Theory of Mind (ToM) neural network for predicting beliefs and their dynamics during human social interactions from multimodal input. ToM is key for effectiv…
The Overcooked Generalisation Challenge: Evaluating Cooperation with Novel Partners in Unknown Environments Using Unsupervised Environment Design
Constantin Ruhdorfer, Matteo Bortoletto, Anna Penzkofer +1
We introduce the Overcooked Generalisation Challenge (OGC) - a new benchmark for evaluating reinforcement learning (RL) agents on their ability to cooperate with unknown partners i…
Brittle Minds, Fixable Activations: Understanding Belief Representations in Language Models
Matteo Bortoletto, Constantin Ruhdorfer, Lei Shi +1
Despite growing interest in Theory of Mind (ToM) tasks for evaluating language models (LMs), little is known about how LMs internally represent mental states of self and others. Un…
Limits of Theory of Mind Modelling in Dialogue-Based Collaborative Plan Acquisition
Matteo Bortoletto, Constantin Ruhdorfer, Adnen Abdessaied +2
Recent work on dialogue-based collaborative plan acquisition (CPA) has suggested that Theory of Mind (ToM) modelling can improve missing knowledge prediction in settings with asymm…
Neural Reasoning About Agents' Goals, Preferences, and Actions
Matteo Bortoletto, Lei Shi, Andreas Bulling
We propose the Intuitive Reasoning Network (IRENE) - a novel neural model for intuitive psychological reasoning about agents' goals, preferences, and actions that can generalise pr…
Exploring Natural Language Processing Methods for Interactive Behaviour Modelling
Guanhua Zhang, Matteo Bortoletto, Zhiming Hu +3
Analysing and modelling interactive behaviour is an important topic in human-computer interaction (HCI) and a key requirement for the development of intelligent interactive systems…