Pith Number

pith:QIWSSMM3

pith:2026:QIWSSMM3UF4CRTSAZCYHFZSAQL

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What Limits Vision-and-Language Navigation ?

Jiaxi Zhang, Junzhe Xu, Kun Liu, Lusong Li, Renjing Xu, Taowen Wang, Wei Lu, Yixiao Feng, Yuetong Fang, Yunheng Wang, Zecui Zeng, Zizhao Yuan

StereoNav uses target-location priors and stereo vision to achieve robust real-world vision-and-language navigation with fewer parameters and less data.

arxiv:2605.13328 v1 · 2026-05-13 · cs.RO · cs.AI · cs.CL · cs.CV

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\usepackage{pith}
\pithnumber{QIWSSMM3UF4CRTSAZCYHFZSAQL}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

StereoNav achieves state-of-the-art egocentric RGB performance, with SR and SPL scores of 81.1% and 68.3%, and 67.5% and 52.0%, respectively, while using significantly fewer parameters and less training data than prior scaling-based approaches. More importantly, real-world robotic deployments confirm that StereoNav substantially improves navigation reliability in complex, unstructured environments.

C2weakest assumption

That the introduced Target-Location Priors remain invariant and useful across simulation-to-real domain shifts and that stereo vision reliably supplies depth cues that overcome motion blur and illumination changes without additional calibration or post-processing.

C3one line summary

StereoNav reaches new benchmark highs on R2R-CE and RxR-CE and improves real-robot reliability by supplying persistent target-location priors and stereo-derived geometry that stay stable under lighting changes and blur.

References

59 extracted · 59 resolved · 9 Pith anchors

[1] Vision-and-language navigation: A survey of tasks, methods, and future directions 2022

[2] arXiv preprint arXiv:2407.07035 , year= 2024

[3] HomeRobot: Open-vocabulary mobile manipulation 2024

[4] Navila: Legged robot vision-language-action model for navigation 2025

[5] Navid: Video-based vlm plans the next step for vision-and-language navigation 2024

Receipt and verification

First computed	2026-05-18T02:44:48.590477Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

822d29319ba17828ce40c8b072e64082e1c0f3ddfe5483683d12be7640f3fee3

Aliases

arxiv: 2605.13328 · arxiv_version: 2605.13328v1 · doi: 10.48550/arxiv.2605.13328 · pith_short_12: QIWSSMM3UF4C · pith_short_16: QIWSSMM3UF4CRTSA · pith_short_8: QIWSSMM3

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/QIWSSMM3UF4CRTSAZCYHFZSAQL \
  | 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: 822d29319ba17828ce40c8b072e64082e1c0f3ddfe5483683d12be7640f3fee3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6d926be6e47a166eb417ceaf37a090f2d36bc628b3a6683386eb044e6963ccbf",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CL",
      "cs.CV"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-13T10:41:24Z",
    "title_canon_sha256": "ee0b99c94fee81331fa8b475bc09421d04906f0460a087bfdc634a7f9ebbd079"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13328",
    "kind": "arxiv",
    "version": 1
  }
}