How do the driving and robot world-model sources measure multi-view, temporal, physics and control-following consistency, and which of those measurements are numbers versus figures or company claims?
The sources use five families of checks: distribution distances (FID, FVD, FDD, FVMD), epipolar Sampson error within a view over time (TSE) and between views (CSE), pose re-estimation from the generated clip to check commanded paths (Cosmos TAE/TFE and camera-path errors, Vista IDM trajectory difference), detector/segmentation agreement with the conditioning boxes (GAIA-2), and human preference tests (Vista, Cosmos instruction tests). GAIA-2 provides no multi-camera metric in its text; Cosmos does (TSE/CSE, Table 24 and Predict2.5 Table 14) and notes the real-video reference values. Wayve's GAIA-3/4 pages describe LiDAR alignment, a three-level fidelity scheme and unpublished correlation claims; these are company statements without a linked report. Numbers from different reports are not comparable even for similar model names.
Structured fields
{
"citations": [
{
"url": "https://arxiv.org/abs/2503.20523v1",
"note": "candidate evidence excerpts"
},
{
"url": "https://arxiv.org/abs/2501.03575v3",
"note": "candidate evidence excerpts"
},
{
"url": "https://arxiv.org/abs/2511.00062v2",
"note": "candidate evidence excerpts"
},
{
"url": "https://arxiv.org/abs/2405.17398v5",
"note": "candidate evidence excerpts"
},
{
"url": "https://arxiv.org/abs/2403.06845v2",
"note": "candidate evidence excerpts"
},
{
"url": "https://wayve.ai/thinking/gaia-3/",
"note": "candidate evidence excerpts"
},
{
"url": "https://wayve.ai/thinking/gaia-4/",
"note": "candidate evidence excerpts"
},
{
"url": "https://www.1x.tech/discover/redwood-ai-world-model",
"note": "candidate evidence excerpts"
}
]
}Evidence claims
- [sourced_fact] The sources use five families of checks: distribution distances (FID, FVD, FDD, FVMD), epipolar Sampson error within a view over time (TSE) and between views (CSE), pose re-estimation from the generated clip to check commanded paths (Cosmos TAE/TFE and camera-path errors, Vista IDM trajectory difference), detector/segmentation agreement with the conditioning boxes (GAIA-2), and human preference tests (Vista, Cosmos instruction tests). GAIA-2 provides no multi-camera metric in its text; Cosmos does (TSE/CSE, Table 24 and Predict2.5 Table 14) and notes the real-video reference values. Wayve's GAIA-3/4 pages describe LiDAR alignment, a three-level fidelity scheme and unpublished correlation claims; these are company statements without a linked report. Numbers from different reports are not comparable even for similar model names. · locator: candidate evidence excerpts source
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |
Linked records
- cites → https://arxiv.org/abs/2403.06845v2
- cites → https://arxiv.org/abs/2405.17398v5
- cites → https://arxiv.org/abs/2501.03575v3
- cites → https://arxiv.org/abs/2503.20523v1
- cites → https://arxiv.org/abs/2511.00062v2
- cites → https://wayve.ai/thinking/gaia-3
- cites → https://wayve.ai/thinking/gaia-4
- cites → https://www.1x.tech/discover/redwood-ai-world-model