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Jiongchi Yu

Singapore Management University

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#artificial intelligence Preprint Oct 2026

JANUS: Synthesizing Cross-Layer Defenses Against Web Deserialization Attacks

Unsafe deserialization turns untrusted data into attacker-controlled execution, and a single vulnerability can admit diverse exploit variants that evade defenses tailored to a known exploit. Existing defenses typically operate at a single enforcement point with limited visibility into the full attack. Combining control...

Ruo-Zhao Yang, Ming-Lang Li, Jiongchi Yu et al. · 0 citations
#artificial intelligence Preprint Oct 2026

When Messages Go Wrong: Understanding Communication Faults in LLM-Based Multi-Agent Systems

LLM-based multi-agent systems (LLM-MAS) use specialized agents that exchange messages to accomplish complex tasks. Their reliance on networked protocols, remote tools, and model endpoints exposes communication to message loss, delay, and context expiration. Because agents often exchange open-ended natural language, ano...

Jin-Hao Zhou, Xiao-Yue Zhang, Jiongchi Yu et al. · 0 citations
#software testing Book Open access Oct 2026

The Gene Is Not the Gate: Conceptualizing the Semantic Genome of Quantum Software

This work presents QGenome, a semantic foundation for quantum software genomics that establishes a falsifiable framework and a concrete research agenda for gene mining, lineage recovery, cross-layer regression testing and repair, and evidence-grounded quantum software agents.

Jiongchi Yu, Yue Duan, Zi-Ming Zhao et al. · 0 citations
#artificial intelligence Preprint Sep 2026

AdaRepair-Mem: Adaptive Experience Orchestration for Repository-Level Program Repair

The results show that the key to memory-augmented repair is not simply accumulating more experiences, but retrieving the right experiences for the right repair context, and that relevance, quality, and redundancy matter more than raw memory volume.

Zi-Chen Luo, Jia-Chen Guo, Wen-Jun He et al. · 0 citations
Preprint Aug 2026

Repair or Resample? Rethinking Failure Debugging in LLM Multi-Agent Systems

This study introduces SymTrace, a controlled evaluation framework that records the MAS execution trajectory and establishes intervention anchors and explores the effectiveness of MAS repair methods, revealing that existing unguided rerun methods are highly unreliable.

Zhong-Wen Luan, Xiaoyan Zhang, Ming Hu et al. · 2 citations

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