Before revision:  Experimental results show that the proposed method consistently boosts the performance of previous trajectory forecasting, behavioral cloning , and reinforcement learning algorithms in various settings .
After revision:  Experimental results show that the proposed method consistently boosts the performance of previous trajectory forecasting, behavioral cloning , and reinforcement learning algorithms , outperforming current state-of-the-art models on several benchmarks .