Physical Words: A Vocabulary for Structuring Latent Reasoning in Robot Manipulation
Pairs action-word predictions with hidden-state predictions of future visual and tactile observations. Uses these intermediate representations to guide robot manipulation, with separate supervision for action labels and future sensory information.
First public: · Added to this list: October 22, 2026
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Continuous-state reasoning — Use vectors—lists of numbers—to carry intermediate reasoning from one step to the next, instead of selecting a text token at every step. Some methods use the model's hidden states; others combine several candidate token representations.
Thinking tokens — Give a model extra tokens for computation, such as pauses, filler symbols, or learned planning tokens. These tokens need not spell out the solution.