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cs.AI2026
DuMateBench: Evaluating Autonomous Agents in Complex Real-World Workflows
Zechun Niu, Yukun Zhao, Jiaxin Zhang +12
Autonomous agents are increasingly adopted to complete complex, multi-tool workflows in real-world settings. However, existing benchmarks typically separate tasks by application or…
cs.AI2026
UnityMAS-O: A General RL Optimization Framework for LLM-Based Multi-Agent Systems
Yiqun Chen, Wei Yang, Erhan Zhang +14
LLM-based multi-agent systems decompose complex tasks into interacting roles, but most remain manually orchestrated by prompts, tools, and control rules, while agents are rarely op…
cs.AI2026
OASES: Outcome-Aligned Search-Evaluation Co-Training for Agentic Search
Erhan Zhang, Yiqun Chen, Zechun Niu +6
Agentic search enables language models to solve knowledge-intensive tasks by adaptively acquiring external evidence over multiple steps. Reinforcement learning with verifiable rewa…