Stimulus Generation

Stimulus generation research focuses on creating controlled stimuli for various scientific investigations, aiming to understand how humans process information across different modalities (visual, textual). Current efforts utilize diverse approaches, including generative adversarial networks (GANs), reinforcement learning (RL), and transformer-based models, to generate stimuli with specific properties, such as controlling visual concepts or matching neural network activations. These advancements enable more rigorous testing of cognitive hypotheses and improve the efficiency of tasks like design verification, ultimately advancing our understanding of human perception and cognition.