pith:7T3FOS2R
Ctrl-World: A Controllable Generative World Model for Robot Manipulation
A controllable world model ranks robot policies and improves them by 44.7 percent through imagined trajectories alone.
arxiv:2510.10125 v3 · 2025-10-11 · cs.RO · cs.AI
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Claims
By synthesizing successful trajectories in imagination and using them for supervised fine-tuning, our approach can improve policy success by 44.7%.
The generated trajectories are sufficiently accurate proxies for real-world dynamics on novel objects, instructions, and camera placements to enable reliable policy ranking and effective fine-tuning.
A controllable world model trained on the DROID dataset generates consistent multi-view robot trajectories for over 20 seconds and improves generalist policy success rates by 44.7% via imagined trajectory fine-tuning.
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| First computed | 2026-05-17T23:38:49.505782Z |
|---|---|
| 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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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7T3FOS2RQBBK6QUVHWCRVMNFMP \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: fcf6574b518042af42953d851ab1a563c626870a90cde4bf3aee4770022a874b
Canonical record JSON
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