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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:13:25.940793Z

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

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  • 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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-17T10:58:53.215887Z digest=sha256:ec9119a7a55e326f35f08d97002773b8be5c2d336fe5a31a26c81bf48397dbcd

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T00:05:03.547664Z digest=sha256:ef88430fa2f226eca84b8d87be65b71226b137bce67493af41bda1a81f31880e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-17T07:51:12.953777Z digest=sha256:c81fb18c0e2a71cd91728a2964786229891daa2367b61f491443784ecb6497e4

Observation a058e217-c823-40c3-8f3d-92fbd41a2206 · inbound

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations cites this paper.

A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T19:45:18.754300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:45:18.754300Z digest=sha256:e20f7d689a0e0d47b43c4c24a61a2e8e650ea7f8061608a54c4c5fb310d90209

Observation f3ba0300-05e8-43ea-a7e6-2f2c36a0b7ca · inbound

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models cites this paper.

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T13:57:07.419635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:57:07.419635Z digest=sha256:030c47b4f99fde8e8a7819db4f8e0844b6a6e6ea2b8aea789863f7b6df87e144

Observation cf22a302-1e01-4e57-b838-dfdc96986a09 · inbound

Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment cites this paper.

Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:35:55.414755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:35:55.414755Z digest=sha256:e793557fa7ab9fed2f0a9c802aebb9cafcf91e7bddf0b8d97f3f39cdca444c53

Observation 1567cb64-eba7-4cfd-a546-41f62aa51bc2 · inbound

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples cites this paper.

D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:11.230813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:23:11.230813Z digest=sha256:5fe1acaa969fca458147abef3bcb8be21ee2b940c7550b99c58bc47de3093073

Observation 448ccc0f-a26a-4c91-ab4a-9b4750d221e9 · inbound

MLA-Trust: Benchmarking Trustworthiness of Multimodal LLM Agents in GUI Environments cites this paper.

MLA-Trust: Benchmarking Trustworthiness of Multimodal LLM Agents in GUI Environments How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T11:42:33.433505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:42:33.433505Z digest=sha256:8a77cf14c7cb5fdb925da33aa0fc5dae1f8fac56973b9e7a3704d82d22ad3879

Observation 92032bf7-2422-4d67-8b64-828035486beb · inbound

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs cites this paper.

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 210

Resolution
unresolved
no resolver link, observed 2026-08-07T10:17:27.240375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:17:27.240375Z digest=sha256:5da5d69470e709ffb450a5fef28cb698a548971541fb0a67eef7bc87f80c2395

Observation ed55307c-ca35-43ce-8faf-54be1420f9b4 · inbound

One Object, Multiple Lies: A Benchmark for Cross-task Adversarial Attack on Unified Vision-Language Models cites this paper.

One Object, Multiple Lies: A Benchmark for Cross-task Adversarial Attack on Unified Vision-Language Models How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T18:40:55.324196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:40:55.324196Z digest=sha256:89d532bdc6a02246839a8771e204651807a9f21c4f80d4c4b7b49887f624f68a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T22:29:36.960961Z digest=sha256:251c907d5bc783dc4d0b6756589916dc3b5dde6258e5185c2837c87da1cc3835

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:a36230128607bb7bed80a997bafc2020e9c565ea5ab938cda7b87baaa21191a1

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:dde400f5d158ede8233955fd175dc9647a2f1183a69ac29d1254d268850597a6

Observation 2cc8404a-8f16-4ec7-8f39-8bc631564e22 · inbound

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis cites this paper.

PRISM: Priority-aware Rubric Internalization via Structured Multimodal Data Synthesis How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-08T17:13:25.940793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:13:25.940793Z digest=sha256:20fd38e0ed06d755b80d1f33beb9b312864df125cf5d7c0fb240db74d454a180