Rhombus: Incentivizing Coordination in Parallel Thinking through Reinforcement Learning
Rhombus uses reinforcement learning to incentivize coordination in parallel thinking frameworks.
Published 2026Paper ↗
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Rhombus reframes parallel reasoning as RL-driven inter-agent coordination rather than solo logic, though missing MMLU, HumanEval, and MATH ablations leave its gains unmoored and its reward design unverified.
Abstract
Ziyuan Nan, Qi Yi, Di Huang, Yutong Wu, Guanhua Huang, Xue Gong, Kejiao Li, Yuhao Jiang, Chenchen Zhang, Zenan Xu, Xing Hu, Bo Zhou. Findings of the Association for Computational Linguistics: ACL 2026. 2026.