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Yu-Quan Lin

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#artificial intelligence Preprint Oct 2026

RITE: Evaluating End-to-End Resilience to Silent Tool Errors in E-Commerce Agentic Systems

This work forms Silent-error Resilience Task, an interactive task that evaluates whether agents complete the original query after a silent error corrupts an intermediate state, and introduces RITE, a benchmark built from human-authored industrial workflows and production-log-derived inputs.

Wen-Shuo Zhang, Yu-Quan Lin, Yu-Shi Sun et al. · 0 citations
2026

Rethinking Fake Adversarial Examples for Single-Step Adversarial Training

Adversarial training (AT) is a widely adopted defense against adversarial attacks, but its multi-step optimization process for generating adversarial examples leads to substantial computational overhead. To mitigate this, various single-step adversarial training methods have been proposed. However, these models often s...

Lifeng Huang, Yuquan Lin, Chen Wan et al. · 0 citations

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