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Found 3 papers, 3 papers with code
Neural Linguistic Steganography
Whereas traditional cryptography encrypts a secret message into an unintelligible form, steganography conceals that communication is taking place by encoding a secret message into a cover signal.
Encoder-Agnostic Adaptation for Conditional Language Generation
Large pretrained language models have changed the way researchers approach discriminative natural language understanding tasks, leading to the dominance of approaches that adapt a pretrained model for arbitrary downstream tasks.
Latent Normalizing Flows for Discrete Sequences
Normalizing flows are a powerful class of generative models for continuous random variables, showing both strong model flexibility and the potential for non-autoregressive generation.
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