Self Motivation
Self-motivation, the internal drive to pursue goals, is a complex phenomenon increasingly investigated through computational lenses. Current research focuses on modeling the interplay between motivations, emotions, and actions using graph-based frameworks and large language models (LLMs), often incorporating techniques like reinforcement learning and adaptive prompting to enhance agent performance and generate diverse motivational messages. This work aims to improve understanding of self-motivation's underlying mechanisms and develop effective computational tools for applications such as personalized education, therapeutic interventions, and the design of more engaging human-computer interfaces.
Papers
Sensing of inspiration events from speech: comparison of deep learning and linguistic methods
Aki Härmä, Ulf Grossekathöfer, Okke Ouweltjes, Venkata Srikanth Nallanthighal
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
Julien Siems, Konstantin Ditschuneit, Winfried Ripken, Alma Lindborg, Maximilian Schambach, Johannes S. Otterbach, Martin Genzel