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Peiyang Wang

2 accepted papers

2026

Dual-Branch Asymmetric Discrepancy Learning Based on Fake Image Pattern-Coexistence for AI-Generated Image Detection

AAAI 2026technical

With the rapid advancement of generative models, high-fidelity AI-generated images have become increasingly indistinguishable from real images, posing significant challenges to traditional detection methods that rely on explicit artifacts or uniform feature learning. We hypothesize that detection am

Cited by 0SourcePDFScholar
2025

Exploring the Hidden Reasoning Process of Large Language Models by Misleading Them

EMNLP 2025

Large language models (LLMs) have been able to perform various forms of reasoning tasks ina wide range of scenarios, but are they truly engaging in task abstraction and rule-based reasoning beyond mere memorization? To answer this question, we propose a novel experimentalapproach, Misleading Fine-Tu

Cited by 0SourcePDFScholar