Namyeong So
2026
Superficial Success vs. Internal Breakdown: An Empirical Study of Generalization in Adaptive Multi-Agent Systems
Namyeong So | Seokgyu Jang | Taeuk Kim
Findings of the Association for Computational Linguistics: ACL 2026
Namyeong So | Seokgyu Jang | Taeuk Kim
Findings of the Association for Computational Linguistics: ACL 2026
Adaptive multi-agent systems (MAS) are increasingly adopted as solutions to complex problems. However, their optimization for narrow task ranges leaves it unclear whether they can function as general-purpose systems. To fill this gap, we conduct an extensive empirical study on adaptive MAS, revealing two key findings: (1) they are prone to topological overfitting, defined as failures in domain transfer; and (2) they exhibit illusory coordination, where surface-level accuracy is high but underlying agent coordination deviates from ideal MAS behavior, raising concerns about their practical effectiveness. These observations highlight the urgent need to prioritize generalization in MAS development and motivate more thorough evaluation beyond correctness of the final answer.