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cs.AI2026
Multi-Paradigm Agent Interaction in Practice:A Systematic Analysis of Generator-Evaluator, ReAct Loop,and Adversarial Evaluation in the buddyMe Framework
Xiaohua Wang, Chao Han, Kai Yu +2
The rapid evolution of Large Language Model (LLM) agents has produced diverse interaction paradigms, yet few production systems integrate multiple paradigms within a unified archit…
cs.AI2026
Good to Go: The LOOP Skill Engine That Hits 99% Success and Slashes Token Usage by 99% via One-Shot Recording and Deterministic Replay
Xiaohua Wang, Kai Yu, XuXiao Liang +2
Deploying AI agents for repetitive periodic tasks exposes a critical tension: Large Language Models (LLMs) offer unmatched flexibility in tool orchestration, yet their inherent sto…
cs.AI2026
No Action Without a NOD: A Heterogeneous Multi-Agent Architecture for Reliable Service Agents
Zixu Yang, Hang Zheng, Nan Jiang +5
Large language model (LLM) agents have increasingly advanced service applications, such as booking flight tickets. However, these service agents suffer from unreliability in long-h…