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Chenchen Gu

2 accepted papers

2025

Auditing Prompt Caching in Language Model APIs

ICML 2025poster

Prompt caching in large language models (LLMs) results in data-dependent timing variations: cached prompts are processed faster than non-cached prompts. These timing differences introduce the risk of side-channel timing attacks. For example, if the cache is shared across users, an attacker could ide…

2024

On the Learnability of Watermarks for Language Models

ICLR 2024poster

Watermarking of language model outputs enables statistical detection of model-generated text, which can mitigate harms and misuses of language models. Existing watermarking strategies operate by altering the decoder of an existing language model. In this paper, we ask whether language models can dir…