36 citations · 57 across the 22 of their papers we have counts for
4 papers · 1 filter
Feasibility with Language Models for Open-World Compositional Zero-Shot Learning
Jae Myung Kim, Stephan Alaniz, Cordelia Schmid +1
Humans can easily tell if an attribute (also called state) is realistic, i.e., feasible, for an object, e.g. fire can be hot, but it cannot be wet. In Open-World Compositional Zero…
In-Context Impersonation Reveals Large Language Models' Strengths and Biases
Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto +2
In everyday conversations, humans can take on different roles and adapt their vocabulary to their chosen roles. We explore whether LLMs can take on, that is impersonate, different…
Modeling Conceptual Understanding in Image Reference Games
Rodolfo Corona, Stephan Alaniz, Zeynep Akata
An agent who interacts with a wide population of other agents needs to be aware that there may be variations in their understanding of the world. Furthermore, the machinery which t…
Deep Reinforcement Learning with Model Learning and Monte Carlo Tree Search in Minecraft
Stephan Alaniz
Deep reinforcement learning has been successfully applied to several visual-input tasks using model-free methods. In this paper, we propose a model-based approach that combines lea…