🧠 PlanGEN: Enhancing Planning with Adaptive Verification and Selection
published on February 22

The paper introduces PlanGEN, a new agent framework designed to tackle complex planning problems in machine learning. It combines three main components: constraint agents, verification agents, and selection agents, which work together to enhance the performance of inference-time algorithms. By using constraint-guided iterative verification, PlanGEN improves the effectiveness of algorithms like Best of N and Tree-of-Thought. The framework also adapts algorithm selection based on the complexity of the task, leading to significant performance gains across various benchmarks.