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Ziqi Miao

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#natural language process... Preprint Oct 2026

OPRD: On-Policy Reminder Distillation for Long-Horizon Coding Agents

Reliable repository-level coding requires agents not only to generate correct code but also to preserve constraints and respond to tool feedback across long interactions. However, our diagnostic analysis shows that agents often fail to act on relevant information already available in context, while final Pass/Fail outc...

Yu-Jia Luo, Zhi-Yi Lai, Zi-Qi Miao et al. · 0 citations
Preprint Sep 2026

Defense-as-Skill: Evolving Runtime Guard Skill for Skill-Augmented Agents

Skill-augmented agents load reusable skills as persistent runtime context, improving task performance but also giving malicious skills a durable channel for steering future actions. Such skills may leak secrets, corrupt code, bypass approvals, or stage data for exfiltration only after a concrete user task and workspace...

Xiao-Fan Yang, Ziqi Miao, Chen Qian et al. · 0 citations

TabSieve: Explicit In-Table Evidence Selection for Tabular Prediction

TabSieve, a select-then-predict framework that makes evidence usage explicit and auditable, and introduces TAB-GRPO, a reinforcement learning recipe that jointly optimizes evidence selection and prediction correctness with separate rewards, and stabilizes mixed regression and classification training via dynamic task-ad...

Yong-Yao Wang, Ziqi Miao, Lu Yang et al. · 5 citations
#artificial intelligence Preprint Sep 2026

Defense-as-Skill: Evolving Runtime Guard Skill for Skill-Augmented Agents

This work proposes Defense-as-Skill, a defense paradigm that implements the runtime guard itself as an installable, inspectable, and editable skill, and demonstrates transfer across victim models, held-out risk families, and external benchmarks, as well as retained protection against adaptive attackers.

Xiao-Fan Yang, Ziqi Miao, Dian-Bo Sui et al. · 0 citations
Preprint Aug 2026

Tracing the Cascade: A Topology-Aware Evaluation Framework for Scientific Agent Hallucinations

SCHEMA reveals that hallucinations concentrate at a small set of highly connected knowledge hubs, and that final-answer accuracy decouples from trajectory honesty; models often reach correct conclusions through structurally flawed reasoning.

Xinshun Feng, Ziqi Miao, Li-Jun Li et al. · 0 citations

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