Paper Citation Record · LEDGER

Quantifying Cross-Modality Memorization in Vision-Language Models

As of 20 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 1 inbound Pith citation observation for arXiv:2506.05198.

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

pith.paper-citation-record.v1
2506.05198 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:27:49.753134Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-07T17:58:11.469707Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T23:11:18.189304Z

Reference resolution

19 of 19 outbound references displayed

verified exact0
verified fuzzy1
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f57a6b85-dfd0-4eed-80f8-080d04ad8f25 · outbound

This paper cites Physics of Language Models: Part 3.2, Knowledge Manipulation.

Quantifying Cross-Modality Memorization in Vision-Language Models Physics of Language Models: Part 3.2, Knowledge Manipulation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.299716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aafb8524-eb26-4d8a-a1bc-bc867eb3b7aa · outbound

This paper cites Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?.

Quantifying Cross-Modality Memorization in Vision-Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.584237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42a76126-2361-49a8-8ddf-f2b2256c0f6f · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Quantifying Cross-Modality Memorization in Vision-Language Models Measuring Massive Multitask Language Understanding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.692794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9dfc881-582b-45ce-a82e-62168f112854 · outbound

This paper cites Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick.

Quantifying Cross-Modality Memorization in Vision-Language Models Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:27:50.466596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b5cd2a40-f0c0-4b9c-bc4a-34f1a8a42fb9 · outbound

This paper cites Scalable Extraction of Training Data from (Production) Language Models.

Quantifying Cross-Modality Memorization in Vision-Language Models Scalable Extraction of Training Data from (Production) Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.155819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51609f8b-3d48-4062-b23c-5cd2169d5732 · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

Quantifying Cross-Modality Memorization in Vision-Language Models GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.223478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aad3d495-db8d-4758-bb98-00dd1e0ed42d · outbound

This paper cites Measuring Style Similarity in Diffusion Models.

Quantifying Cross-Modality Memorization in Vision-Language Models Measuring Style Similarity in Diffusion Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.301075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb20fe76-8122-4f4f-8618-bbf24535a16f · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Quantifying Cross-Modality Memorization in Vision-Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.389145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cba103c-ab3c-4040-ba27-2fefc0378a5f · outbound

This paper cites Gemma 3 Technical Report.

Quantifying Cross-Modality Memorization in Vision-Language Models Gemma 3 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.493850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0e4bb2c-45b7-4e5d-8659-41979ecf42d5 · outbound

This paper cites Measuring short-form factuality in large language models.

Quantifying Cross-Modality Memorization in Vision-Language Models Measuring short-form factuality in large language models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.586262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc4530e6-94f6-4ced-878f-07503ae1f9d4 · outbound

This paper cites Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models.

Quantifying Cross-Modality Memorization in Vision-Language Models Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.683237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f4f4cc9-899a-41e1-8089-17635ccbe180 · outbound

This paper cites Large Language Models Are Not Robust Multiple Choice Selectors.

Quantifying Cross-Modality Memorization in Vision-Language Models Large Language Models Are Not Robust Multiple Choice Selectors

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.753134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9919505c-1bbb-47e4-b8db-1f85e8d4cefa · outbound

This paper cites Decoupled Weight Decay Regularization.

Quantifying Cross-Modality Memorization in Vision-Language Models Decoupled Weight Decay Regularization

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.013233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44fcc08c-757c-4119-8e82-0c1ba43040ec · outbound

This paper cites TOFU: A Task of Fictitious Unlearning for LLMs.

Quantifying Cross-Modality Memorization in Vision-Language Models TOFU: A Task of Fictitious Unlearning for LLMs

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:49.098394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2824d38a-4f12-4b92-a6ec-e990b3ef09a6 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Quantifying Cross-Modality Memorization in Vision-Language Models LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.851135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff8c600c-0673-41e4-918d-fdc6bb831460 · outbound

This paper cites Training Data Leakage Analysis in Language Models.

Quantifying Cross-Modality Memorization in Vision-Language Models Training Data Leakage Analysis in Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.763185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 447ab3df-50fd-4c0f-9dba-199a1ba88968 · outbound

This paper cites Imagen 3.arXiv preprint arXiv:2408.07009,.

Quantifying Cross-Modality Memorization in Vision-Language Models Imagen 3.arXiv preprint arXiv:2408.07009,

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.402343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90cedb31-bfa6-44d4-9360-8724dd32b562 · outbound

This paper cites Fantastic Copyrighted Beasts and How (Not) to Generate Them.

Quantifying Cross-Modality Memorization in Vision-Language Models Fantastic Copyrighted Beasts and How (Not) to Generate Them

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.630517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83fed1bc-4803-45cd-ae98-ff2c68d4f35e · outbound

This paper cites The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A".

Quantifying Cross-Modality Memorization in Vision-Language Models The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T10:27:48.477387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 67bde97d-8577-4dcc-ae3d-5d98f920875f · inbound

Before Forgetting, Learn to Remember: Revisiting Foundational Learning Failures in LVLM Unlearning Benchmarks cites this paper.

Before Forgetting, Learn to Remember: Revisiting Foundational Learning Failures in LVLM Unlearning Benchmarks Quantifying Cross-Modality Memorization in Vision-Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:11:18.193547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.