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Found 6 papers, 1 papers with code
Robust Eavesdropping in the Presence of Adversarial Communications for RF Fingerprinting
Deep learning is an effective approach for performing radio frequency (RF) fingerprinting, which aims to identify the transmitter corresponding to received RF signals.
FameBias: Embedding Manipulation Bias Attack in Text-to-Image Models
Building on this concept, we introduce FameBias, a T2I biasing attack that manipulates the embeddings of input prompts to generate images featuring specific public figures.
CTRQNets & LQNets: Continuous Time Recurrent and Liquid Quantum Neural Networks
Neural networks have continued to gain prevalence in the modern era for their ability to model complex data through pattern recognition and behavior remodeling.
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State
More concretely, in this paper we ask: Given a hidden (internal) representation of a single token at position $t$ in an input, can we reliably anticipate the tokens that will appear at positions $\geq t + 2$?
Dropout Attacks
DROPOUTATTACK attacks the dropout operator by manipulating the selection of neurons to drop instead of selecting them uniformly at random.
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
We develop the first non-trivial lower bound on the worst-case error of the best map from attributes to classes for this setting, even with perfect attribute detectors.
