pith:SYPTGEY7
Rule-VLN: Bridging Perception and Compliance via Semantic Reasoning and Geometric Rectification
Rule-VLN adds 177 regulatory categories to a 29k-node urban graph to test whether navigation agents can obey semantic rules instead of only reaching goals.
arxiv:2604.16993 v2 · 2026-04-18 · cs.AI · cs.CV · cs.RO
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\pithnumber{SYPTGEY7KHAND4KL56ZOEJPGSZ}
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Record completeness
Claims
Experiments demonstrate that while Rule-VLN challenges state-of-the-art models, SNRM significantly restores navigation capabilities, reducing CVR by 19.26% and boosting TC by 5.97%.
That the 177 injected regulatory categories and the coarse-to-fine VLM perception in SNRM accurately capture and interpret real-world semantic and behavioral constraints in a zero-shot manner without domain-specific fine-tuning or additional supervision.
Rule-VLN is the first large-scale benchmark injecting 177 regulatory categories into an urban environment, and the proposed SNRM module equips pre-trained VLN agents with zero-shot semantic reasoning and detour planning to reduce constraint violations by 19.26% and improve task completion.
Receipt and verification
| First computed | 2026-07-02T01:17:31.317449Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
961f33131f51c0d1f14befb2e225e696577e14fb03d8983811b195e1ec8ff322
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SYPTGEY7KHAND4KL56ZOEJPGSZ \
| 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: 961f33131f51c0d1f14befb2e225e696577e14fb03d8983811b195e1ec8ff322
Canonical record JSON
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"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
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