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Paper Citation Record · LEDGER

Securing Multimodal AI through Internal Information Decomposition

As of 21 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.21600.

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

pith.paper-citation-record.v1
2607.21600 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T15:03:01.447793Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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  • verified fuzzy0
  • unresolved32
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

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Outbound references

Observation bfed0043-890a-426c-acdc-85bf21af107d · outbound

This paper cites Qwen2.5-VL Technical Report.

Securing Multimodal AI through Internal Information Decomposition Qwen2.5-VL Technical Report

Reference 2

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source=pdf_text observed=2026-08-02T15:02:57.997161Z digest=sha256:8325a0551bf5a12a4df7313a58c7eb18a44a43d8f3011dc32adc14d0dccc4d06

Observation cb55d4c7-79ef-447a-bbda-92082a225337 · outbound

This paper cites Jailbreaking Black Box Large Language Models in Twenty Queries.

Securing Multimodal AI through Internal Information Decomposition Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 4

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source=pdf_text observed=2026-08-02T15:02:58.279711Z digest=sha256:18b3094237d45b57e3439c3201d89fdd69805e1a7adcf423395f9efb9bd38209

Observation 5fae3157-4b5f-4e72-bb97-188145f8b5f4 · outbound

This paper cites DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback.

Securing Multimodal AI through Internal Information Decomposition DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback

Reference 5

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source=pdf_text observed=2026-08-02T15:02:58.424519Z digest=sha256:9e8497d185c3c2035e30efac7cabb5edadd5bef0d98ed7c1bf4142784b66764f

Observation 96fa12cc-2f83-4a58-8df5-53b3942d1379 · outbound

This paper cites The Llama 3 Herd of Models.

Securing Multimodal AI through Internal Information Decomposition The Llama 3 Herd of Models

Reference 7

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source=pdf_text observed=2026-08-02T15:02:58.674459Z digest=sha256:56cd7a5e73f96d895af2b1472054f86b186e1c81432ba2c121ce9de54d740e9c

Observation 4f8ff18d-7e5c-45ad-b0f2-054ff7dce504 · outbound

This paper cites MirrorCheck: Efficient Adversarial Defense for Vision-Language Models.

Securing Multimodal AI through Internal Information Decomposition MirrorCheck: Efficient Adversarial Defense for Vision-Language Models

Reference 8

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source=pdf_text observed=2026-08-02T15:02:58.880122Z digest=sha256:48c19ba1d802b72dd6f1a16a503ae72b8994cb27255516aeeefd866686eb6acb

Observation bfae213e-9029-4b58-954f-127a92ef4fd2 · outbound

This paper cites FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts.

Securing Multimodal AI through Internal Information Decomposition FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts

Reference 10

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source=pdf_text observed=2026-08-02T15:02:59.139372Z digest=sha256:622b2c4c2b697c27ab846b6800ac90401176da6c8766c9fc02a888d625641600

Observation f4e52eaa-f2ca-4f87-a83d-25ed95e7954b · outbound

This paper cites Baseline Defenses for Adversarial Attacks Against Aligned Language Models.

Securing Multimodal AI through Internal Information Decomposition Baseline Defenses for Adversarial Attacks Against Aligned Language Models

Reference 13

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source=pdf_text observed=2026-08-02T15:02:59.641888Z digest=sha256:7caa8b7505d68597a7ee26fdfc7bc0781b5c4a1380186f7dcc4d8c3f9ad446de

Observation 2444ea51-84c0-4ece-8723-71219482be7c · outbound

This paper cites AI Alignment: A Comprehensive Survey.

Securing Multimodal AI through Internal Information Decomposition AI Alignment: A Comprehensive Survey

Reference 14

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source=pdf_text observed=2026-08-02T15:02:59.770853Z digest=sha256:2e02e15e2ed248e07378435ea8ca1cf2155db2f7be9b6dc564ad9dbc11ae9440

Observation 2a60bd29-46b3-4948-80b1-9a2723b30304 · outbound

This paper cites ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs.

Securing Multimodal AI through Internal Information Decomposition ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs

Reference 15

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source=pdf_text observed=2026-08-02T15:02:59.892345Z digest=sha256:d8894d6e00f21874f17e07f4961f3a0d70e55ec50e1de2ed1a929dfe338f61b9

Observation af7ba74a-be5b-4a97-b870-8f56b06562df · outbound

This paper cites Gemma 3 Technical Report.

Securing Multimodal AI through Internal Information Decomposition Gemma 3 Technical Report

Reference 16

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source=pdf_text observed=2026-08-02T15:02:59.953206Z digest=sha256:d74fb211eaa9a9aa62384d5686400be59b36fff736be971dd14ea2ea40db93c0

Observation 61c847a2-bb09-4873-9bf1-2e5d82d57f48 · outbound

This paper cites MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries?.

Securing Multimodal AI through Internal Information Decomposition MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries?

Reference 18

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source=pdf_text observed=2026-08-02T15:03:00.136710Z digest=sha256:0788b228346292029b601c794e874ff391af14a6b2920ef70d1591023156cfd5

Observation 6cc2164e-9968-467e-affb-a0cd047c6307 · outbound

This paper cites MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models.

Securing Multimodal AI through Internal Information Decomposition MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models

Reference 21

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source=pdf_text observed=2026-08-02T15:03:00.273991Z digest=sha256:c92dc37091b91314c412100e5d290c66f8af7a796d5ace7efc677a1e4312947d

Observation ffa5c034-8062-4550-bd25-f6d4e4260c05 · outbound

This paper cites Jailbreaking Attack against Multimodal Large Language Model.

Securing Multimodal AI through Internal Information Decomposition Jailbreaking Attack against Multimodal Large Language Model

Reference 22

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source=pdf_text observed=2026-08-02T15:03:00.340843Z digest=sha256:17813371ecbd9346e7158e07842150b731b83df176b7416d0750a8ece7ebafcb

Observation 9d3eb570-0db1-450a-9faa-31f9349b4926 · outbound

This paper cites Qi, X., Huang, K., Panda, A., Henderson, P., Wang, M., and Mittal, P.

Securing Multimodal AI through Internal Information Decomposition Qi, X., Huang, K., Panda, A., Henderson, P., Wang, M., and Mittal, P

Reference 23

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source=pdf_text observed=2026-08-02T15:03:00.455003Z digest=sha256:171edafb0491a3f577941ab7069919b5c983aa5bd90e5d3851b525e1b5084a74

Observation ec5622d3-6877-43fe-9108-89fb88938cc3 · outbound

This paper cites Visual Adversarial Examples Jailbreak Aligned Large Language Models.

Securing Multimodal AI through Internal Information Decomposition Visual Adversarial Examples Jailbreak Aligned Large Language Models

Reference 24

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source=pdf_text observed=2026-08-02T15:03:00.459707Z digest=sha256:8757646180de955a8f3112daa530e5edc90995ea8b3ad48c41ed0548923d74a6

Observation 0637691e-9c18-48c5-b8f6-28cad3c7f5d0 · outbound

This paper cites Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack.

Securing Multimodal AI through Internal Information Decomposition Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack

Reference 25

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source=pdf_text observed=2026-08-02T15:03:00.463918Z digest=sha256:84e850a608c7f272c7d7e13966418422327b27730e23e5b82d2d02b0fb19d320

Observation 1fe2a1f3-7795-4fba-bf02-8caf1827bc63 · outbound

This paper cites White-box Multimodal Jailbreaks Against Large Vision-Language Models.

Securing Multimodal AI through Internal Information Decomposition White-box Multimodal Jailbreaks Against Large Vision-Language Models

Reference 27

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source=pdf_text observed=2026-08-02T15:03:00.706850Z digest=sha256:2024f01f5cc27bdf0c67c17361d67d807befe9eb46828b79e9e5d9bd4293dc06

Observation f94b3422-f9f0-4a29-9320-cfe54fc14c0a · outbound

This paper cites Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models.

Securing Multimodal AI through Internal Information Decomposition Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models

Reference 29

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source=pdf_text observed=2026-08-02T15:03:00.946530Z digest=sha256:4de6ade2b8c60587f91047aa795dbd74bc5c8f5b2d071ebb133dfccf7882f87f

Observation 6ad33a52-c565-4179-939f-d7dbe3f20c75 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Securing Multimodal AI through Internal Information Decomposition Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 30

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Observation e476ad4f-e8be-4651-acc9-85456b71fbec · outbound

This paper cites Sure, here is.

Securing Multimodal AI through Internal Information Decomposition Sure, here is

Reference 33

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source=pdf_text observed=2026-08-02T15:03:01.447793Z digest=sha256:eadcb19c02e21c70dfb17a699bacb0e830da3b6bf64e099cc7843bba2afc6c24

Observation 6062de3d-fc1a-4f6b-8fb0-c006037ee109 · outbound

This paper cites DO NOT include harmful content in your response.

Securing Multimodal AI through Internal Information Decomposition DO NOT include harmful content in your response

Reference 64

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source=pdf_text observed=2026-08-02T15:03:01.161001Z digest=sha256:2d862d13307ab821d9f96bf03faeb28ba88412d68a465200c99397c96a2bc1ac

Observation a9c94644-0f7a-4a88-a735-dae0811e211c · outbound

This paper cites Wang, R., Ma, X., Zhou, H., Ji, C., Ye, G., and Jiang, Y .-G.

Securing Multimodal AI through Internal Information Decomposition Wang, R., Ma, X., Zhou, H., Ji, C., Ye, G., and Jiang, Y .-G

Reference 1948

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source=pdf_text observed=2026-08-02T15:03:00.540725Z digest=sha256:74017ccca39a07cba35a2e0babfab04d031ea92a0902915b74a55b1d9c80c420

Observation ab658a34-554d-418a-bcf4-2c30d29b46f1 · outbound

This paper cites URL https: //doi.org/10.1214/aoms/1177729694.

Securing Multimodal AI through Internal Information Decomposition URL https: //doi.org/10.1214/aoms/1177729694

Reference 1951

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Observation fa6fd3a5-09c8-457f-a81c-a5cd20f99af6 · outbound

This paper cites an unresolved cited work.

Securing Multimodal AI through Internal Information Decomposition Unresolved cited work

Reference 1991

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source=pdf_text observed=2026-08-02T15:03:00.177513Z digest=sha256:f184bb12f3b1b210283d836f25457e86fdaac0f1dd24e2e8fe76bbb38eb615b3

Observation b8c1bf3a-9aed-4b8e-b11c-bec0be5d92af · outbound

This paper cites Liu, H., Li, C., Wu, Q., and Lee, Y.

Securing Multimodal AI through Internal Information Decomposition Liu, H., Li, C., Wu, Q., and Lee, Y

Reference 2008

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source=pdf_text observed=2026-08-02T15:03:00.218077Z digest=sha256:589cfa71e7b768b3f1aa7a9057dc817920f11babdc5a490a42b0913a13f834e2

Observation 8d5fac30-f0f0-4694-aa3b-0f859aca3f84 · outbound

This paper cites Nonnegative Decomposition of Multivariate Information.

Securing Multimodal AI through Internal Information Decomposition Nonnegative Decomposition of Multivariate Information

Reference 2010

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source=pdf_text observed=2026-08-02T15:03:00.847790Z digest=sha256:0643d7cc14dd9cd99167481e6bd50b62f1cbe3f53d4cd9882ee63e443301e12b

Observation 5bb3ef10-f102-4b69-a523-97760ede7fa3 · outbound

This paper cites Sure, here is.

Securing Multimodal AI through Internal Information Decomposition Sure, here is

Reference 2017

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source=pdf_text observed=2026-08-02T15:03:01.282759Z digest=sha256:f4833796872647933349ccfcf38383c50cab28efaff439b51e041bf70dd6acd0

Observation f34e6295-32c8-4142-9545-491416e1ed38 · outbound

This paper cites VizWiz Grand Challenge: Answering Visual Questions from Blind People.

Securing Multimodal AI through Internal Information Decomposition VizWiz Grand Challenge: Answering Visual Questions from Blind People

Reference 2018

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source=pdf_text observed=2026-08-02T15:02:59.292875Z digest=sha256:b2c9143763082391369d66f9cddfb2b47bc35d5069bc2012add25ed0976f898d

Observation de3c4701-412d-4acb-8dd5-e3329bb092c8 · outbound

This paper cites Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks.

Securing Multimodal AI through Internal Information Decomposition Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 2020

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source=pdf_text observed=2026-08-02T15:02:58.558426Z digest=sha256:734c564c7f9434fe6942b295583b51247ab2f94b3ef34209f85a35346101ddf7

Observation 1e855e13-e178-4aaf-b694-1148474964e4 · outbound

This paper cites doi: 10.18653/v1/2021.acl-long.133.

Securing Multimodal AI through Internal Information Decomposition doi: 10.18653/v1/2021.acl-long.133

Reference 2021

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source=pdf_text observed=2026-08-02T15:02:59.013034Z digest=sha256:072d5ea7fedfbcd532fad277605a0202054a3e7896c1354b5fe5f2fcf6cee73c

Observation cab09187-d374-4a72-a880-d9f0b90a66df · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

Securing Multimodal AI through Internal Information Decomposition Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 2023

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source=pdf_text observed=2026-08-02T15:02:59.499483Z digest=sha256:fbb4434ee6c09c62081a99d523d9ddb049fa1c92be10cadd0dc90a8f1da41c08

Observation bac76bc1-07cc-4137-a403-25d788855de2 · outbound

This paper cites Discovering Latent Knowledge in Language Models Without Supervision.

Securing Multimodal AI through Internal Information Decomposition Discovering Latent Knowledge in Language Models Without Supervision

Reference 2024

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Observation 0bcf0487-a5b7-4e05-b895-f080ab07ecd6 · outbound

This paper cites an unresolved cited work.

Securing Multimodal AI through Internal Information Decomposition Unresolved cited work

Reference 2025

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source=pdf_text observed=2026-08-02T15:02:57.887684Z digest=sha256:bd5ee52a02961eefaa6aa7b6d1e26707417c35cadf53aad87329fa9f7540f50b

Pith citing papers

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