Papers by Dominik Meier

2 papers
TrojanStego: Your Language Model Can Secretly Be A Steganographic Privacy Leaking Agent (2025.emnlp-main)

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Challenge: Existing work has focused on the (un)intended leakage of sensitive information through LLM outputs.
Approach: They propose a threat model that embeds context information into natural-looking outputs via linguistic steganography without requiring explicit control over inference inputs.
Outcome: The proposed model transmits 32-bit secrets with 87% accuracy on held-out prompts and can reach over 97% accuracy using majority voting across three generations.
Towards Human Understanding of Paraphrase Types in Large Language Models (2025.coling-main)

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Challenge: Current paraphrase evaluations of language models use binary approaches, offering limited interpretability of specific text changes.
Approach: They introduce a dataset of 800 sentence-level and word-level annotations by 15 annotators and a human preference ranking of paraphrases with different types.
Outcome: The proposed model can generate simple APTs, but struggle with complex structures (e.g., subordination changes).

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