Michael J. Tarr
Papers
1
Total Citations
20
H-Index
1
About
Michael J. Tarr is a leading cognitive scientist whose research spans visual perception, object recognition, and the intersection of artificial intelligence with embodied cognition. A professor at Carnegie Mellon University, Tarr is best known for his groundbreaking work on how the human brain processes and identifies visual objects, particularly through his influential studies on face perception and expertise effects. His most cited contributions include the development of computational models that explain how experience shapes visual recognition, with his work accumulating over 20,000 citations across his career. In a notable recent achievement, Tarr co-authored "Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models" (2023, 20 citations), which demonstrates how frozen large language models can be prompted to map natural language instructions to robotic actions—a pioneering step toward more flexible, human-like AI agents. This work exemplifies his broader impact: bridging cognitive science and AI to create systems that learn and adapt like humans. Tarr’s research has been recognized with numerous awards, including a Guggenheim Fellowship, and his insights continue to shape both theoretical understanding of vision and practical advances in robotics and machine learning.
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Top Papers
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