3 papers
cs.AI2026
RODS: Reward-Driven Online Data Synthesis for Multi-Turn Tool-Use Agents
Ruishan Fang, Siyuan Lu, Chenyi Zhuang +1
Multi-turn tool-use RL is bottlenecked by the rapid depletion of informative samples in static datasets. We observe that the gradient signal in GRPO concentrates on tasks with the…
cs.AI2026
Do More Agents Help? Controlled and Protocol-Aligned Evaluation of LLM Agent Workflows
Yuhang Fu, Ruishan Fang, Jiaqi Shao +4
Does adding more agents help an LLM workflow once compared systems share the same benchmark loader, tool access, answer contract, usage accounting, and trajectory logging? We intro…
cs.MA2026
Stop Wasting Your Tokens: Towards Efficient Runtime Multi-Agent Systems
Fulin Lin, Shaowen Chen, Ruishan Fang +2
While Multi-Agent Systems (MAS) excel at complex tasks, their growing autonomy with operational complexity often leads to critical inefficiencies, such as excessive token consumpti…