Papers by Zhuangdi Zhu

2 papers
Dialogue is Better Than Monologue: Instructing Meidcal LLMs via Strategic Conversations (2026.findings-eacl)

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Challenge: Existing tuning methods for medical AI models are monologue-based . existing benchmarks are based on licensing exams or research articles .
Approach: They propose a benchmark to expose limitations of monologue-based tuning for medical AI models . they use a large dialogue dataset to capture stepwise diagnostic reasoning .
Outcome: The proposed model outperforms monologue-tuned models on a medical question answering task and improves accuracy on standard medical QA benchmarks.
Web Intellectual Property at Risk: Preventing Unauthorized Real-Time Retrieval by Large Language Models (2025.emnlp-main)

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Challenge: a new framework protects web content from unauthorized LLM real-time extraction and redistribution . multiple AI companies have been accused of scraping digital IP for proprietary benefit .
Approach: They propose a defense framework that empowers web content creators to safeguard their web-based IP from unauthorized LLM real-time extraction and redistribution by leveraging the semantic understanding capability of LLMs themselves.
Outcome: The proposed defense outperforms traditional defenses on LLMs and improves on black-box optimization problems.

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