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Paper Citation Record · LEDGER

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline

As of 12 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2509.04214.

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

pith.paper-citation-record.v1
2509.04214 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:22:04.654983Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

22 of 22 outbound references displayed

  • verified exact2
  • verified fuzzy10
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dee8f82e-d1ac-4324-8e9c-e18aa4cde941 · outbound

This paper cites Model inversion attacks that exploit confidence information and basic countermeasures,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Model inversion attacks that exploit confidence information and basic countermeasures,

Reference 1

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unresolved
no resolver link, observed 2026-08-05T10:22:04.546361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.546361Z digest=sha256:77bb72b8e5eda308ea528d16b003d7926991bd0e36bb299be145a16310daa795

Observation dfd22304-5831-47bf-9cde-f56d41ec539f · outbound

This paper cites Response Wide Shut: Surprising Observations in Basic Vision Language Model Capabilities.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Response Wide Shut: Surprising Observations in Basic Vision Language Model Capabilities

Reference 2

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verified exact
local_arxiv, observed 2026-08-05T10:22:05.138364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.552395Z digest=sha256:c9d737eb038e698f851566db12db84c37fa64ee98047e5d94c304f2e16a802c1

Observation 27d54235-2105-4d19-8a70-444feacee751 · outbound

This paper cites An Attack-Based Evaluation Method for Differentially Private Learning Against Model Inversion Attack,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline An Attack-Based Evaluation Method for Differentially Private Learning Against Model Inversion Attack,

Reference 3

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metadata mismatch
raw_fallback, observed 2026-08-05T10:22:05.116325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.558430Z digest=sha256:be57a2446955366e6e1b8e72ab5fb2664b9feac857c3dc090a44edb68e583dea

Observation a011ff36-f718-4cee-8f32-d3992992c6c5 · outbound

This paper cites Checkpoint for bart-large after being trained on the MultiNLI (MNLI) dataset.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Checkpoint for bart-large after being trained on the MultiNLI (MNLI) dataset

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.365498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.563049Z digest=sha256:81766393e9de1ebfb482fc8c4e3bf55da39f6f5d4e26bf5bb78ac95616bf8a29

Observation 4474a841-3519-4b9c-9f96-1f890d6ac544 · outbound

This paper cites Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield But Also a Catalyst for Model Inversion Attacks,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield But Also a Catalyst for Model Inversion Attacks,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.349362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.567953Z digest=sha256:b83f314e5b7d30fdfd1ccb90f78be115e917a49a6c605ba0ea612ffc054370e1

Observation 38aa8414-4486-469c-b624-2f71df08566b · outbound

This paper cites Rethinking the inception architecture for computer vision,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Rethinking the inception architecture for computer vision,

Reference 6

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unresolved
no resolver link, observed 2026-08-05T10:22:04.572589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.572589Z digest=sha256:a9f2caeb467987db035d77c9e89ddeb803341daae73b675c3c8f7f59b2280673

Observation 92e63ea8-3138-47da-8570-ab7902a4de74 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 7

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unresolved
no resolver link, observed 2026-08-05T10:22:04.577919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.577919Z digest=sha256:a87cda254565e75802db541433659bf77cca30b1040f823ef72396677e74cf38

Observation bf784742-208e-4baf-9f60-1894ee7cabf9 · outbound

This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 9

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unresolved
no resolver link, observed 2026-08-05T10:22:04.587059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.587059Z digest=sha256:65e608f481f4968e053b32a3b1935f18c823a43f4802b5f4c9d16c6c30f99ac6

Observation 10f53a16-4ada-496a-8f15-9c994589501d · outbound

This paper cites Visualizing and understanding convolu- tional networks,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Visualizing and understanding convolu- tional networks,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.333944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.591364Z digest=sha256:7c2e426a823339a901a07165795215dec7e014dd5c43db514e6fed596e8d627a

Observation 49b5e3c2-6287-41ba-acf5-0cc9fe047eb4 · outbound

This paper cites The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.317967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.596412Z digest=sha256:a99af3b9ed4bf5a68e73bd27385dee23efb1a2e411936df49cc0bee0fa5e08a0

Observation 303366d1-df3b-4f2f-bab7-bfd0f377342a · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Learning Transferable Visual Models From Natural Language Supervision

Reference 12

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unresolved
no resolver link, observed 2026-08-05T10:22:04.601265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.601265Z digest=sha256:eef51f5e4e53c9ed35197de473d01a4f3ffca60e6d8ca88cd8e3f7be93e4dd4a

Observation d1017104-3edf-43a1-91e9-5949eb23e962 · outbound

This paper cites BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models,

Reference 13

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metadata mismatch
raw_fallback, observed 2026-08-05T10:22:04.999648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.606265Z digest=sha256:2594dfe42107de3b2509747ad1eebde0a7e0578f8d28051ad2776be9110c9963

Observation 8be9f290-1d57-4ba1-89bd-98610f7cb82a · outbound

This paper cites InstructBLIP: towards general- purpose vision-language models with instruction tuning,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline InstructBLIP: towards general- purpose vision-language models with instruction tuning,

Reference 14

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metadata mismatch
raw_fallback, observed 2026-08-05T10:22:04.912481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.610773Z digest=sha256:0072611a8b6e5564b2dc9c6826bb8473bf928b8ed50d5699306ec539c708d593

Observation be0e850c-1257-4598-8665-be5e0a9ffab8 · outbound

This paper cites An analysis of single-layer networks in unsupervised feature learning,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline An analysis of single-layer networks in unsupervised feature learning,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.302066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.615456Z digest=sha256:2cb1c84e70155f5c280513109f76103a0305477b548dcdaf14418cdd03da0331

Observation 3c7fe559-8bb3-4261-b636-88d446e43db2 · outbound

This paper cites ImageNet: A Large-Scale Hierarchical Image Database,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline ImageNet: A Large-Scale Hierarchical Image Database,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.284683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.620061Z digest=sha256:a8ec905e20b98707ac0687b5445dc18cb22f8dc5cb38f7dbb978ba13f6383a05

Observation 9780af76-3f6e-44aa-a15e-71b91a7416d5 · outbound

This paper cites Military Vehicles Dataset,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Military Vehicles Dataset,

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.268694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.625275Z digest=sha256:8a66c173e566676bde2e8dc6c20a42aa9357452a71b249642216890c8a03165b

Observation 05525132-8f0a-4d4c-b81c-73e0a3276eb7 · outbound

This paper cites Lucid library adapted for PyTorch,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Lucid library adapted for PyTorch,

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.252021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.629691Z digest=sha256:fd433b1c41ee4845a24ab29d904f45e7df9dfc784e17248922f48e2f40e7a060

Observation dd7ad561-4a66-4246-aa62-6049cdfbcefc · outbound

This paper cites Error detection and constraint recovery in hierarchical multi-label classification without prior knowledge,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Error detection and constraint recovery in hierarchical multi-label classification without prior knowledge,

Reference 19

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unresolved
no resolver link, observed 2026-08-05T10:22:04.634061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.634061Z digest=sha256:f63755c994e54a898f86fa031e3305b01fb4b1d417037e2cba668ee9c7e72deb

Observation 597d34da-2f91-4abb-b3c4-0e33e1436208 · outbound

This paper cites kNN Approach to Unbalanced Data Distributions: A Case Study involving Information Extraction,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline kNN Approach to Unbalanced Data Distributions: A Case Study involving Information Extraction,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.236987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.638779Z digest=sha256:925b44ff60b5e9b0765c4531bd1983131a14ec5e7860534d8f0331c38aee19fd

Observation e6adde99-1718-4fea-b410-af030537c131 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 21

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unresolved
no resolver link, observed 2026-08-05T10:22:04.644522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:22:04.644522Z digest=sha256:46c0e4485bfd43f87387c836db876292e9af3cd48e28400b1c057e66aacc0f2c

Observation c6012169-eb45-4798-ae80-ad87d796567b · outbound

This paper cites Revisiting Model Inversion Evaluation: From Misleading Standards to Reliable Privacy Assessment.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline Revisiting Model Inversion Evaluation: From Misleading Standards to Reliable Privacy Assessment

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-05T10:22:04.714348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.649869Z digest=sha256:b0dcb9d72ba75fe60f23d075039aba8bb86db24017d8f6a80b781b52311f184e

Observation 51f33b01-8c00-40df-8534-4995a923c24f · outbound

This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation,.

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T10:22:05.221261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-05T10:22:04.654983Z digest=sha256:3dff9d143f16109ed78f76f98e41ca43c9d27470db31600cbb234ee0bf0d84eb

Pith citing papers

No inbound Pith citation observations are available.