pith:ZARD27V7
MVP-LAM: Learning Action-Centric Latent Action via Cross-Viewpoint Reconstruction
Cross-viewpoint reconstruction trains latent actions to capture underlying robot actions rather than camera-specific details.
arxiv:2602.03668 v3 · 2026-02-03 · cs.RO · cs.CV
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Claims
MVP-LAM produces more action-centric latent actions, achieving higher mutual information with ground-truth actions and improved action prediction, including under out-of-distribution evaluation. Finally, pretraining VLAs with MVP-LAM latent actions improves downstream manipulation performance on various benchmarks.
That forcing a latent action from one viewpoint to explain the future in another viewpoint will make the latent action contain information about the underlying ground-truth actions rather than viewpoint-specific cues.
MVP-LAM learns action-centric latent actions from multi-view videos via cross-viewpoint reconstruction, yielding higher mutual information with ground-truth actions and improved downstream VLA manipulation performance.
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| First computed | 2026-05-28T01:04:36.264068Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZARD27V76RNBZ5IFD7F5FHBUYV \
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# expect: c8223d7ebff45a1cf5051fcbd29c34c55f934fd57294adb660f11ef5352b8c3b
Canonical record JSON
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