pith:E3T33RED
What Matters in Building Vision-Language-Action Models for Generalist Robots
Specific choices in backbones, architectures, and data timing let simple Vision-Language-Action models set new robot manipulation records.
arxiv:2412.14058 v4 · 2024-12-18 · cs.RO · cs.CV
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Claims
Through extensive experiments which include over 8 VLM backbones, 4 policy architectures, and over 600 distinct designed experiments, we provide a detailed guidebook for the future design of VLAs... RoboVLMs... achieve a new state-of-the-art performance in three simulation tasks and real-world experiments.
That the chosen simulation tasks and real-world experiments are representative enough of generalist robot manipulation that the observed ranking of design choices will transfer to new tasks, embodiments, and environments not tested in the 600+ runs.
Systematic tests of VLM backbones, policy architectures, and cross-embodiment data yield RoboVLMs that set new SOTA on robot manipulation benchmarks while requiring few manual designs.
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| First computed | 2026-05-17T23:38:13.006948Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
26e7bdc4830515fd12a9ccf81a88b0304845d02a7ee8022d7163fbd4f8dbd609
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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/E3T33REDAUK72EVJZT4BVCFQGB \
| 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: 26e7bdc4830515fd12a9ccf81a88b0304845d02a7ee8022d7163fbd4f8dbd609
Canonical record JSON
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