Papers by Shengli Gan

1 papers
Synergizing Stylometrics with Semantics: Dual-Path Framework for LLM Detection and Attribution (2026.findings-acl)

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Challenge: Existing methods for identifying MGTs rely on statistical likelihood or deep embeddings.
Approach: They propose a framework that extracts model-specific stylistic fingerprints across lexical, syntactic, and structural dimensions.
Outcome: The proposed framework achieves a Macro-F1 score of 95.6% on the Wikipedia dataset.

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