pith:NCQ4Y6O6
DiscreteRTC: Discrete Diffusion Policies are Natural Asynchronous Executors
Discrete diffusion policies act as natural asynchronous executors because iterative unmasking makes inpainting native to them.
arxiv:2604.25050 v2 · 2026-04-27 · cs.RO
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Claims
discrete diffusion policies, which generate actions by iteratively unmasking, are natural asynchronous executors that resolve all limitations at once: they are fine-tuning free since inpainting is their native operation, while early stopping further provides adaptive guidance and reduces inference cost.
That a discrete diffusion policy trained on standard offline data will produce consistent, high-quality inpainted continuations for committed action chunks in dynamic environments without quality degradation or the need for task-specific adaptations.
Discrete diffusion policies support native asynchronous execution via unmasking for real-time chunking, delivering higher success rates and 0.7x inference cost versus flow-matching RTC on dynamic robotics benchmarks and real pick tasks.
Receipt and verification
| First computed | 2026-06-03T02:05:47.825243Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
68a1cc79de8c7d14824630cc9f2363499e82b1df5e2a7786b861eafdfbcae370
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NCQ4Y6O6RR6RJASGGDGJ6I3DJG \
| 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: 68a1cc79de8c7d14824630cc9f2363499e82b1df5e2a7786b861eafdfbcae370
Canonical record JSON
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