Pith Number

pith:JPFAHTI7

pith:2025:JPFAHTI7MC2A72NR6ASU6UAQ5I

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Are Large Pre-trained Vision Language Models Effective Construction Safety Inspectors?

Xuezheng Chen, Zhengbo Zou

Pre-trained vision-language models generalize to construction safety tasks in zero- and few-shot settings but still require additional training for real sites.

arxiv:2508.11011 v2 · 2025-08-14 · cs.CV

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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

Our subsequent evaluation of current state-of-the-art large pre-trained VLMs shows notable generalization abilities in zero-shot and few-shot settings, while additional training is needed to make them applicable to actual construction sites.

C2weakest assumption

The three annotated tasks (captioning, safety-rule VQA, and element grounding) are sufficient to evaluate whether a VLM can function as an effective construction safety inspector (abstract, paragraph 3).

C3one line summary

Presents the ConstructionSite 10k dataset and evaluates pre-trained VLMs on zero-shot and few-shot construction safety inspection tasks.

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2 papers in Pith

General Hazard Detection

Integration of Object Detection and Small VLMs for Construction Safety Hazard Identification

Receipt and verification

First computed	2026-05-28T01:04:29.625881Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

4bca03cd1f60b40fe9b1f0254f5010ea0cce5202b38a758ebfa2cf97e6ddd121

Aliases

arxiv: 2508.11011 · arxiv_version: 2508.11011v2 · doi: 10.48550/arxiv.2508.11011 · pith_short_12: JPFAHTI7MC2A · pith_short_16: JPFAHTI7MC2A72NR · pith_short_8: JPFAHTI7

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/JPFAHTI7MC2A72NR6ASU6UAQ5I \
  | 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: 4bca03cd1f60b40fe9b1f0254f5010ea0cce5202b38a758ebfa2cf97e6ddd121

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "2cca751c1741b89e7e6a8c11d162350b36619dfa93848a5e64d250175df44965",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2025-08-14T18:23:09Z",
    "title_canon_sha256": "cd76d9e374b73fbc48c84652a0e6309c8acb83e4972e8c40d5a023fa9793350b"
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