Papers by Zachary Ziegler

2 papers
Neural Linguistic Steganography (D19-1)

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Challenge: linguistic steganography encrypts a secret message into a cover signal . language is a pragmatic cover signal due to its benign occurrence and independence from any one medium.
Approach: They propose a technique that encrypts a secret message into a cover signal . language is a particularly pragmatic cover signal due to its benign occurrence .
Outcome: The proposed technique generates realistic looking cover sentences as evaluated by humans while preserving security by matching the cover message distribution with the language model distribution.
A Generative Approach for Mitigating Structural Biases in Natural Language Inference (2022.starsem-1)

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Challenge: Natural language inference datasets contain artifacts and biases that allow models to perform poorly by using a biased subset of the input without considering the remainder features.
Approach: They reformulate a natural language inference task as a generative task . they find that this approach is highly robust to large amounts of bias .
Outcome: The proposed model is highly robust to large amounts of bias.

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