Papers by Peizhuo Lv

2 papers
PROMPRINT: Prompt Fingerprinting via First-Token Response for LLM App Cloning Detection (2026.acl-long)

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Challenge: Large Language Model apps are increasingly regarded as intellectual property . cloned apps pose risks of copyright infringement and malicious misuse .
Approach: They propose a fingerprinting approach that optimizes queries that induce the LLM to generate a specific first token associated with the given system prompt.
Outcome: The proposed fingerprinting approach is robust to partial system prompt modifications and effective under injection of adversarial instructions.
ReasMark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation Attacks (2026.acl-long)

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Challenge: Existing reasoning-enhanced large language models fail to provide reliable attribution of reasoning behavior once it is transferred through knowledge distillation.
Approach: They propose to embed a reasoning-length gap in a model by querying a target domain and training a local student to imitate its outputs.
Outcome: et al. show that ReasMark outperforms baselines while preserving task utility.

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