This paper reminds me of the Neural Network Diffusion paper which was on the front page of HN yesterday in the sense that we are training another model to bypass a number of iterative steps (in the previous paper, those were SGD steps, in this one, it is A* exploration steps).

On a different note, they choose such a bad heuristic for the A* for Sokoban. The heuristic they choose is "A∗ first matches every box to the closest dock and then computes the sum of all Manhattan distances between each box and dock pair". I played Sokoban for 20 minutes while reading the paper and I feel like this is a very poor exploration heuristic (you often need to move boxes away from goal state to make progress).