Pith Number

pith:CLO7UEVM

pith:2026:CLO7UEVMNPCYTTAASUPFEHCEQQ

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Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling

Jinkyu Kim, Joon Seo, Jungbeom Lee, Minseung Lee, Seokha Moon

CaAD models causal dependencies between the ego vehicle and surrounding agents inside a shared latent scene representation to produce more consistent closed-loop trajectories.

arxiv:2605.13646 v1 · 2026-05-13 · cs.RO · cs.AI

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Claims

C1strongest claim

we propose CaAD, a Causality-aware end-to-end Autonomous Driving framework that captures these dependencies within a shared latent scene representation. On the Bench2Drive and NAVSIM benchmarks, CaAD demonstrates strong closed-loop planning performance, achieving a Driving Score of 87.53 and Success Rate of 71.81 on Bench2Drive, and a PDMS of 91.1 on NAVSIM.

C2weakest assumption

That the ego-centric joint-causal modeling module actually learns genuine causal dependencies (rather than correlations) between the ego vehicle and interaction-relevant agents, and that aligning the stochastic ego policy via joint-mode embeddings will produce more consistent and reliable closed-loop trajectories in interaction-critical scenarios.

C3one line summary

CaAD adds ego-centric joint-causal modeling and causality-aware policy alignment to end-to-end driving, reporting Driving Score 87.53 and Success Rate 71.81 on Bench2Drive plus PDMS 91.1 on NAVSIM.

References

66 extracted · 66 resolved · 13 Pith anchors

[1] nuscenes: A multimodal dataset for autonomous driving 2020

[2] NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles 2021 · arXiv:2106.11810

[3] Gri: General reinforced imitation and its application to vision-based autonomous driving.Robotics, 12(5):127, 2023 2023

[4] End-to-end autonomous driving: Challenges and frontiers.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):10164–10183, 2024 2024

[5] VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning 2024 · arXiv:2402.13243

Receipt and verification

First computed	2026-05-18T02:44:17.544725Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

12ddfa12ac6bc589cc00951e521c44840df7c614a6246353c7cb210daa53519f

Aliases

arxiv: 2605.13646 · arxiv_version: 2605.13646v1 · doi: 10.48550/arxiv.2605.13646 · pith_short_12: CLO7UEVMNPCY · pith_short_16: CLO7UEVMNPCYTTAA · pith_short_8: CLO7UEVM

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/CLO7UEVMNPCYTTAASUPFEHCEQQ \
  | 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: 12ddfa12ac6bc589cc00951e521c44840df7c614a6246353c7cb210daa53519f

Canonical record JSON

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  "metadata": {
    "abstract_canon_sha256": "0653d12c00ec3f88e8db227396548f8d9f0106e43ac3886a88fa69227d404d21",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-13T15:06:22Z",
    "title_canon_sha256": "9cf9fe41498a53b657f836c7f3baeaef66f7d25cf512f5a1868a220f4cc1f775"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13646",
    "kind": "arxiv",
    "version": 1
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}