In this episode, we discuss
PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving by Mihir Parmar, Xin Liu, Palash Goyal, Yanfei Chen, Long Le, Swaroop Mishra, Hossein Mobahi, Jindong Gu, Zifeng Wang, Hootan Nakhost, Chitta Baral, Chen-Yu Lee, Tomas Pfister, Hamid Palangi. The paper introduces **PlanGEN**, a versatile agent framework designed to tackle complex planning problems by incorporating constraint, verification, and selection agents. PlanGEN enhances existing inference-time algorithms through constraint-guided iterative verification and dynamically selects the optimal algorithm based on the complexity of each instance. Experimental results show that PlanGEN significantly outperforms leading baselines across multiple benchmarks, achieving state-of-the-art performance by effectively improving verification processes and adaptive algorithm selection.
AI Breakdown