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Paper Citation Record · LEDGER

How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2311.16101.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2311.16101 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T13:51:18.171740Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-17T22:30:23.249867Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 827bad60-ca14-4a9e-ad10-4911386eaf80 · inbound

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning cites this paper.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 176

Resolution
verified exact
arxiv_id, observed 2026-05-17T10:58:53.471175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-17T10:58:53.215887Z digest=sha256:6830c1fc683bda74c812ff8ec641483f65a8813d2bf3c95618f1f11c7b5967a1

Observation 94f13af7-92c4-41cb-a373-51555c9858d8 · inbound

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs cites this paper.

Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 130

Resolution
verified exact
arxiv_id, observed 2026-05-17T00:05:03.754666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-17T00:05:03.547664Z digest=sha256:5f6bf9663b9a86646c863c0af9bee7d041e0603ae3f3c0e9a394d06af5d966dd

Observation d1611879-a4cb-4d9c-8bf9-d70238c93b76 · inbound

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning cites this paper.

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 95

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T07:51:13.080598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-17T07:51:12.953777Z digest=sha256:26e39699edb575180f1882bb6e9efa1db3bba92c95fef422e12f0d1911827b16

Observation b049805a-607b-4e8f-b383-367b4963bad0 · inbound

OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models cites this paper.

OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:30:23.252260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-17T22:29:36.960961Z digest=sha256:8d4a286250ec77193b1b5849b4528e73712808e7cee5099d3252ec8202cc5e62

Observation bdf9c0a4-a820-4468-9c70-e0f4b29403ba · inbound

Twins: Learn to Predict Unified Representations with Focal Loss cites this paper.

Twins: Learn to Predict Unified Representations with Focal Loss How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 289

Resolution
unresolved
no resolver link, observed 2026-08-01T04:30:12.171419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:30:12.171419Z digest=sha256:cfeb1f22d61980484b547d93cfb932c9e1198e682650297bc4c2e3084701446b

Observation af48c296-9a76-4654-be1d-b1b0e5752f51 · inbound

Two Sides of the Same Coin: Co-Evolving Search for Cross-Task Attacks on Vision-Language Models cites this paper.

Two Sides of the Same Coin: Co-Evolving Search for Cross-Task Attacks on Vision-Language Models How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-04T13:51:18.171740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T13:51:18.171740Z digest=sha256:5cdb8d2b993dd31e8d8343501c9a9c8405e2f08d377780b660a3b3c378e5eca1