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arXiv Machine Learning By Takanori Yoshimoto, Yang Hu, Naruya Kondo, Tatsuya Matsushima

FlexLAM: Resolving the Bottleneck Trade-off in Latent Action Learning

Read the original on arXiv Machine Learning →

arXiv:2606. 19408v1 Announce Type: new Abstract: Latent actions provide a compact interface between action-free video and downstream decision-making, yet existing Latent Action Models (LAMs) force every transition through a fixed-capacity bottleneck.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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