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cs.LG2025
Value from Observations: Towards Large-Scale Imitation Learning via Self-Improvement
Michael Bloesch, Markus Wulfmeier, Philemon Brakel +8
Imitation Learning from Observation (IfO) offers a powerful way to learn behaviors at large-scale: Unlike behavior cloning or offline reinforcement learning, IfO can leverage actio…
cs.LG2025
Learning-Order Autoregressive Models with Application to Molecular Graph Generation
Zhe Wang, Jiaxin Shi, Nicolas Heess +2
Autoregressive models (ARMs) have become the workhorse for sequence generation tasks, since many problems can be modeled as next-token prediction. While there appears to be a natur…