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context: no action conditioning;full: always-on action conditioning;drop25: complete action-sequence dropout on 25% of training examples;gated25: learned action-value gate plus 25% sequence dropout.model.pt, config.yaml, manifest.json, eval.json, and
eval_m3_endpoint.json.| Protocol | Key H4 result |
|---|---|
| EgoDex official test | context 0.117616 ± 0.000156; gate 0.024 ± 0.001 |
| DROID-held-out-v1 | full action 0.156419 ± 0.000301; 12.21% over context; gate 0.986 ± 0.001 |
| DROID success prediction | full forecast AUROC 0.9106 ± 0.0005 |
| DROID 16-way image-goal ranking | full forecast R@1 62.36% ± 0.16% |
DROID-held-out-v1 is the
fixed project split with 86,072 training and 9,564 held-out episodes.1import torch
2
3checkpoint = torch.load("model.pt", map_location="cpu", weights_only=False)
4print(checkpoint.keys())config.yaml before loading its state
dictionary. Training and evaluation code, exact downstream protocols, and
compiled CVPR/ECCV manuscripts are available in the
GitHub repository.