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#machine learning Conference Open access Sep 2025

What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs

DUALLM, a dual-method pipeline that integrates two approaches based on a Large Language Model (LLM) and a fine-tuned small language model, achieves 87.4% accuracy and an F1-score of 0.875, significantly outperforming prior solutions.

Xing-Yu Li, Jue-Fei Pu, Yifan Wu et al. · 1 citation

Melting the Flesh of PHP’s Memory Hardening

It is found that although the new protection measures aimed at stopping popular heap exploit techniques or restricting the exploit strategy space can effectively defend against the exploitation of most vulnerabilities, the attack strategies proposed by this work can still make these vulnerabilities exploitable again.

Yifan Wu, Xiao-Chuan Yu, Zhiyun Qian · 0 citations
#human-computer interacti... Preprint Jun 2026

When Chatbots Accommodate: Auditing the Response Policies of AI Companions in Vulnerable Conversations

The AI Companion Vulnerability-Response Taxonomy is introduced, a grounded, paired taxonomy of user vulnerability and chatbot response designed for analyzing extended companion chatbot interactions and reveals distinct response profiles of AI companions in conversations with vulnerable users.

Minh Duc Chu, Yifan Wu, Zhiyi Chen et al. · 0 citations

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