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An inverse dynamics model compresses what changed into a small latent; a forward model must predict the next frame from the past frame plus that latent, so the latent has to carry the action-like change. LAPO (2023, v2 pinned) fixed this template; Genie (2024) used it with 8 discrete codes so a person could pick one per step; AdaWorld (2025) used a continuous latent. LAPO tested on synthetic game data with known actions; web video was the stated motivation, not the tested case.\n\nCurator qualifications: All excerpts located in the work texts. Genie's codebook of 8 is a stated design choice; the discrete-vs-continuous disagreement is preserved.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2312.10812v2","note":"method; conclusion; Sec. on decoders"},{"url":"https://arxiv.org/abs/2402.15391v1","note":"method; conclusion; Sec. on decoders"},{"url":"https://arxiv.org/abs/2503.18938v4","note":"method; conclusion; Sec. on decoders"}]},"categories":["T06","T15","T18"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://arxiv.org/abs/2312.10812v2","claim":"A latent action model (LAM) is trained on pairs of consecutive frames with no action labels. 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An inverse dynamics model compresses what changed into a small latent; a forward model must predict the next frame from the past frame plus that latent, so the latent has to carry the action-like change. LAPO (2023, v2 pinned) fixed this template; Genie (2024) used it with 8 discrete codes so a person could pick one per step; AdaWorld (2025) used a continuous latent. LAPO tested on synthetic game data with known actions; web video was the stated motivation, not the tested case.\n\nCurator qualifications: All excerpts located in the work texts. Genie's codebook of 8 is a stated design choice; the discrete-vs-continuous disagreement is preserved.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2312.10812v2","note":"method; conclusion; Sec. on decoders"},{"url":"https://arxiv.org/abs/2402.15391v1","note":"method; conclusion; Sec. on decoders"},{"url":"https://arxiv.org/abs/2503.18938v4","note":"method; conclusion; Sec. on decoders"}]},"tags":[],"type":"article","links":[],"title":"What is a latent action model, and how is one trained from video that has no action labels?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"A latent action model (LAM) is trained on pairs of consecutive frames with no action labels. 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