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Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space
We address this research gap and propose the embedding space attack, which directly attacks the continuous embedding representation of input tokens.
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning
To facilitate reliable deployments of autonomous robots in the real world, Out-of-Distribution (OOD) detection capabilities are often required.
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection
To combine these 2 approaches, we formulate our Bayesian Inference for Rating Data (BIRD) model, a flexible Bayesian model of user rating behavior.
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