Papers by Minjia Mao

1 papers
Watermarking Large Language Models: An Unbiased and Low-risk Method (2025.acl-long)

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Challenge: Recent advances in large language models (LLMs) have highlighted the risk of misusing them, raising the need for accurate detection of LLM-generated content.
Approach: They propose a method to inject imperceptible identifiers into large language models (LLMs) this method is unbiased and preserves the original token distribution in expectation .
Outcome: The proposed method preserves the original token distribution in expectation and has lower risk of producing unsatisfactory outputs in low-entropy scenarios compared to existing unbiased watermarks.

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