Extensive experiments on various datasets show that our approach outperforms state-of-the-art methods, enhancing the model's

Given a previously generated plan, how do we effectively regenerate a new plan?

PlanBench seeks to cover a broad range of tasks related to planning and reasoning.

An important goal of modern scheduling systems is to efficiently manage power usage. In energy-efficient scheduling, the operating system controls the speed at which a machine is processing jobs with the dual objective of minimizing energy consumption and optimizing the quality of service cost of the resulting schedule. Since machine-learned predictions about future requests can often be learned from historical data, a recent line of work on learning-augmented algorithms aims to achieve improved performance guarantees by leveraging predictions.