Papers by Yunxiao Zhu

2 papers
iAgent: LLM Agent as a Shield between User and Recommender Systems (2025.findings-acl)

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Challenge: Traditional recommender systems focus on the user-platform paradigm, where users are directly exposed under the control of the platform's recommendation algorithms.
Approach: They propose a user-agent-platform paradigm where agent serves as the protective shield between user and recommender system that enables indirect exposure.
Outcome: The proposed model improves 16.6% over baselines on four datasets and mitigates echo chamber effects and reduces model bias in disadvantaged users.
DivScore: Zero-Shot Detection of LLM-Generated Text in Specialized Domains (2025.emnlp-main)

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Challenge: Existing zero-shot detectors fail when applied to specialized content due to domain shift . DivScore outperforms state-of-the-art detectors in specialized domains .
Approach: They propose a zero-shot detection framework that uses normalized entropy-based scoring and domain knowledge distillation to identify LLM-generated text in specialized domains.
Outcome: The proposed framework outperforms state-of-the-art detectors on medical and legal datasets with 14.4% higher AUROC and 64.0% higher recall.

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