Vaishnav Tadiparthi

A robot can learn its partner's hidden physical limitations simply by watching it collaborate, enabling seamless coordination on novel tasks without explicit communication.

This work proposes ARIA (autoencoder-gated inference-time unlearning), a test-time unlearning method that leaves model weights intact and gates access to unwanted knowledge only when generation enters a forget-related state and introduces three post-unlearning adversarial attacks targeting weight-space and decoding-space recovery.