Paper Citation Record · LEDGER

An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline

As of 16 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 2026-08-16T06:30:59.297886+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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.