2 papers
cs.CL2026
Can LLMs Truly Forget? Revealing Unlearning Gaps Through Adversarial Evaluation
Ayush Gupta, Hima Varshini Surisetty, Sreevidya Bollineni +5
Machine unlearning aims to remove the influence of targeted training data from a model while preserving its remaining capabilities, but evaluating whether such information has trul…
cs.DC2026
Collaborative Processing for Multi-Tenant Inference on Memory-Constrained Edge TPUs
Nathan Ng, Walid A. Hanafy, Prashanthi Kadambi +5
IoT applications increasingly rely on on-device AI accelerators to ensure high performance, especially in low-connectivity and safety-critical scenarios. However, the limited on-ch…