pith:XRXESRUL
ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation
ORION reports 77.74 Driving Score and 54.62% Success Rate on Bench2Drive, outperforming prior end-to-end methods by 14.28 DS and 19.61% SR through unified VQA and planning optimization.
arxiv:2503.19755 v1 · 2025-03-25 · cs.CV
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Our method achieves an impressive closed-loop performance of 77.74 Driving Score (DS) and 54.62% Success Rate (SR) on the challenge Bench2Drive datasets, which outperforms state-of-the-art (SOTA) methods by a large margin of 14.28 DS and 19.61% SR.
The assumption that aligning the reasoning space of the LLM with the numerical action space through unified E2E optimization will reliably improve closed-loop causal reasoning and trajectory quality without introducing new failure modes.
ORION reports 77.74 Driving Score and 54.62% Success Rate on Bench2Drive, outperforming prior end-to-end methods by 14.28 DS and 19.61% SR through unified VQA and planning optimization.
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| First computed | 2026-05-17T23:38:14.609345Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
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| Schema | pith-number/v1.0 |
Canonical hash
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XRXESRULOKATW7KFSUUF36GC4G \
| jq -c '.canonical_record' \
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# expect: bc6e49468b72813b7d4595285df8c2e1b90a7d8aabb0b50e716e5b121db8db68
Canonical record JSON
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