Pith Number

pith:IZFSFNTT

pith:2026:IZFSFNTTXFMWHUD5PV35JHEMC5

not attested not anchored not stored refs resolved

DriveSafe: A Framework for Risk Detection and Safety Suggestions in Driving Scenarios

Avijit Dasgupta, C. V. Jawahar, Sainithin Artham, Shankar Gangisetty

DriveSafe improves driving risk assessment by conditioning it on explicit language-based scene representations.

arxiv:2605.16892 v1 · 2026-05-16 · cs.CV · cs.AI · cs.CL

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Claims

C1strongest claim

By conditioning risk assessment on explicit language-based scene representations, DriveSafe achieves significant gains over both zero-shot MLLMs and prior domain-specific baselines. Exhaustive experiments on the DRAMA benchmark demonstrate state-of-the-art performance.

C2weakest assumption

That generating spatially grounded captions enriched with multimodal context (motion, spatial, and depth cues) will provide sufficient and accurate information to enable superior risk assessment compared to direct zero-shot use of MLLMs, as stated in the abstract's motivation and method overview.

C3one line summary

DriveSafe improves driving risk detection by first creating detailed language-based scene descriptions enriched with motion, spatial, and depth information, then assessing risks and suggesting actions, with an adapter fine-tuned on caption-risk pairs to achieve SOTA results on the DRAMA benchmark.

References

44 extracted · 44 resolved · 0 Pith anchors

[1] Risk assessment, modelling and proactive safety manage- ment system in aviation: a literature review, 2015

[2] Risk management in the healthcare safety management system, 2021

[3] Safety assessment of collaborative robotics through automated formal verifi- cation, 2019

[4] Road traffic injuries fact sheet, 2024

[5] Fatality statistics: State-by- state, 2023

Receipt and verification

First computed	2026-05-20T00:03:28.660082Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

464b22b673b95963d07d7d77d49c8c17429dcd8252abeb2d5176e4a64ab3e539

Aliases

arxiv: 2605.16892 · arxiv_version: 2605.16892v1 · doi: 10.48550/arxiv.2605.16892 · pith_short_12: IZFSFNTTXFMW · pith_short_16: IZFSFNTTXFMWHUD5 · pith_short_8: IZFSFNTT

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/IZFSFNTTXFMWHUD5PV35JHEMC5 \
  | 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: 464b22b673b95963d07d7d77d49c8c17429dcd8252abeb2d5176e4a64ab3e539

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "002290cd30d81e67f8900e9929750d502e6f76ac4ede8fb8c0ffc93e3e75126f",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CL"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-16T09:07:14Z",
    "title_canon_sha256": "cdb9670a8b359ab628e91368eea59b9386204826c549ba7a92b2b29b7f926a29"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16892",
    "kind": "arxiv",
    "version": 1
  }
}