Yeah, at first I read that as it using 26.8% of the original steps, but reducing the number of steps by 26.8% is not that impressive. I wonder whether it actually reduces total search time as there is added overhead of running the neural network.
I publish in this area and this is a common thing for reviewers to bring up when authors don't report wall clock time. And then for papers to be rejected. What's the value in making an algorithm that's drastically slower? Not much.
Perhaps as an important stepping stone? Deferred optimization and all that.
Some people call the flag planting. You publish something that doesn't work with keywords you suspect will be important in the future. Then hope others will cite you.