ConTraIRL: Factorized Contrastive Abstractions for Transferable IRL.

arXiv:2606.03017v2 Announce Type: replace-cross Abstract: Reward transfer in Inverse Reinforcement Learning (IRL) is unreliable when policies must generalize to unseen combinations of environment dynamics and task goals. We propose Factorized Contrastive Abstr