4 papers
Proximal State Nudging: Reducing Skill Atrophy from AI Assistance
Megha Srivastava, Jonathan Ouyang, Eric Zhou +6
Skill atrophy, the gradual decline of human capability under AI assistance, poses a safety risk in shared-control of semi-autonomous systems, where operators may be unable to disti…
Modeling Student Learning with 3.8 Million Program Traces
Alexis Ross, Megha Srivastava, Jeremiah Blanchard +1
As programmers write code, they often edit and retry multiple times, creating rich "interaction traces" that reveal how they approach coding tasks and provide clues about their lev…
Policy Learning with a Language Bottleneck
Megha Srivastava, Cedric Colas, Dorsa Sadigh +1
Modern AI systems such as self-driving cars and game-playing agents achieve superhuman performance, but often lack human-like generalization, interpretability, and inter-operabilit…
Shared Autonomy for Proximal Teaching
Megha Srivastava, Reihaneh Iranmanesh, Yuchen Cui +6
Motor skill learning often requires experienced professionals who can provide personalized instruction. Unfortunately, the availability of high-quality training can be limited for…