Gokul Swamy
Senior co-author on WEAVER with expertise in imitation learning and robot policy optimization.
“WEAVER achieves a Pearson correlation of ρ=0.870 between simulated and real-world success rates... finetuning on synthetic data closely matches that on real data, with only a 4% average performance gap”
Source→“Gokul Swamy, Carnegie Mellon University, Why notable: Senior co-author with broad expertise in imitation learning and robot policy optimization. Also co-author on the SAILOR paper (robust imitation via search). Swamy's lab appears to be a hub for work at the intersection of world models, imitation learning, and test-time planning.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.