Chitta Baral Research Group

Arizona State University (Tempe)

How can knowledge and reasoning be combined with statistical models to improve language and vision understanding? The laboratory of Cognition and Intelligence develops neuro-symbolic and knowledge-based approaches to natural language understanding, vision-language question answering, and multi-modal document understanding. Projects investigate prompting and programming large language models, bias origins in NLP, efficient low-data methods, and knowledge assimilation for inference. Researchers apply methods spanning symbolic knowledge representation, reasoning frameworks, and machine learning to develop robust, generalizable models for tasks in cybersecurity, robotics, and biological and health sciences. The group maintains publications and a public lab website documenting tools and project outputs.