Gokul Swamy

“Co-author with prior work on steering VLAs (cited as "SayCan" successor work on steering VLAs via language). Active in the test-time steering and RL for robotics space.”

“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”

“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.”