Pith Number

pith:LCSULM4L

pith:2023:LCSULM4LHXNXJLCWZHGHOT73K2

not attested not anchored not stored refs pending

MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models

Chao Yang, Jindong Gu, Xin Liu, Yichen Zhu, Yunshi Lan, Yu Qiao

arxiv:2311.17600 v5 · 2023-11-29 · cs.CV

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{LCSULM4LHXNXJLCWZHGHOT73K2}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

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.

Cited by

9 papers in Pith

PolicyShiftGuard: Benchmarking and Improving Policy-Adaptive Image Guardrails

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges

Robust and Generalizable Safety Steering for Text-to-Image Diffusion Transformers

Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion

Receipt and verification

First computed	2026-07-05T08:34:08.628981Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

58a545b38b3ddb74ac56c9cc774ffb56980c44e5e446f7604c92b4d8c9d88c51

Aliases

arxiv: 2311.17600 · arxiv_version: 2311.17600v5 · doi: 10.48550/arxiv.2311.17600 · pith_short_12: LCSULM4LHXNX · pith_short_16: LCSULM4LHXNXJLCW · pith_short_8: LCSULM4L

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/LCSULM4LHXNXJLCWZHGHOT73K2 \
  | 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: 58a545b38b3ddb74ac56c9cc774ffb56980c44e5e446f7604c92b4d8c9d88c51

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "8a52c3194928bcb0b7ed9090d72fef4b5cbac51857ac5741e7d5802a5947754b",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2023-11-29T12:49:45Z",
    "title_canon_sha256": "51cf67ce4d23fb915863f9e2fa77d24ae53eef7d059939d085561eb7b0094792"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2311.17600",
    "kind": "arxiv",
    "version": 5
  }
}