I am a researcher at Stanford University working with Prof. Maneesh Agrawala. I work at the intersection of AI and media integrity. In a world that is becoming increasingly AI-mediated, my goal is to build AI systems and networks that are inherently trustworthy and interpretable, resulting in productive, democratic discourse.
Jonas Dolezal, Sawood Alam, Mark Graham, Maty Bohacek
Measures the prevalence of AI-generated text on the web and finds reduced semantic diversity and increased positive sentiment, but no statistical support for decreased factual accuracy or stylistic homogenization.
Maty Bohacek, Nino Scherrer, Nick Dufour, Thomas Leung, Christoph Bregler, Stephanie CY Chan
Surfacing actionable insights for improved evals and models through a comprehensive analysis of LLM competency gaps.
Maty Bohacek, Thomas Fel, Maneesh Agrawala, Ekdeep Singh Lubana
Method for identifying blindspots in text-to-image models: concepts the model was trained on but cannot generate.
Maty Bohacek, Rishub Jain, Nicholas Dufour, Thomas Leung, Christoph Bregler, Roma Patel
More effective and interpretable alternative to contrastive features for detecting and controlling LM behavior.
Raina Panda, Daniel Fein, Arpita Singhal, Mark Fiore, Maneesh Agrawala, Maty Bohacek
Interpretable style in vision models using sparse autoencoders for controllable style transfer.
Sarah Barrington, Maty Bohacek, Hany Farid
Large-scale dataset of real and deepfake footage for detecting face-swap and lip-sync deepfakes.
No upcoming events.
Whether you are a researcher exploring collaboration ideas, a journalist writing about AI, a policymaker seeking insight, or an educator looking to apply AI in new ways — I would love to hear from you at maty@stanford.edu.