Paper Citation Record · LEDGER

Out-of-Distribution Detection Using Neural Rendering Generative Models

As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:1907.04572.

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

pith.paper-citation-record.v1
1907.04572 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T23:35:45.607156Z

measured 17 of 17 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

17 of 17 outbound references displayed

verified exact5
verified fuzzy3
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfa547a1-0c24-4ed3-88d4-30d78ce2db3b · outbound

This paper cites and Cho, S.

Out-of-Distribution Detection Using Neural Rendering Generative Models and Cho, S

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:36:27.835365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 254cab17-528b-4cef-b3c2-404990d3c119 · outbound

This paper cites WAIC, but Why? Generative Ensembles for Robust Anomaly Detection.

Out-of-Distribution Detection Using Neural Rendering Generative Models WAIC, but Why? Generative Ensembles for Robust Anomaly Detection

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:36:27.602197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bfa947e5-5ebd-4661-8d62-9ddb4e0772b4 · outbound

This paper cites an unresolved cited work.

Out-of-Distribution Detection Using Neural Rendering Generative Models Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-05-24T23:36:27.842418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f53720b9-e248-43e9-815e-68027c7f37c0 · outbound

This paper cites an unresolved cited work.

Out-of-Distribution Detection Using Neural Rendering Generative Models Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-05-24T23:36:27.826108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 13b0bc9e-7920-41b0-b3b0-354f622c1b12 · outbound

This paper cites Deep Anomaly Detection with Outlier Exposure.

Out-of-Distribution Detection Using Neural Rendering Generative Models Deep Anomaly Detection with Outlier Exposure

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:36:27.612213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 42672e72-dbfa-432d-8613-d84a6a15902e · outbound

This paper cites A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model.

Out-of-Distribution Detection Using Neural Rendering Generative Models A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-24T23:36:27.616850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fbb7fa75-031a-47fe-93c8-7d474e5da962 · outbound

This paper cites an unresolved cited work.

Out-of-Distribution Detection Using Neural Rendering Generative Models Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-05-24T23:36:27.822862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 32fee60f-17a1-45d5-b2f6-cede5d33dec4 · outbound

This paper cites and Hinton, G.

Out-of-Distribution Detection Using Neural Rendering Generative Models and Hinton, G

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:36:27.819525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d93117e9-b73e-4eb4-9365-aadd9496bda1 · outbound

This paper cites Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series.

Out-of-Distribution Detection Using Neural Rendering Generative Models Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:36:27.597620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e6294ffd-7f66-45f3-9289-1d9a37559da6 · outbound

This paper cites an unresolved cited work.

Out-of-Distribution Detection Using Neural Rendering Generative Models Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-05-24T23:36:27.829122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8a07a820-e564-4880-8f5e-e07e30e52246 · outbound

This paper cites Do Deep Generative Models Know What They Don't Know?.

Out-of-Distribution Detection Using Neural Rendering Generative Models Do Deep Generative Models Know What They Don't Know?

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-05-24T23:36:27.592530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f57f6b68-5d60-44a3-a8d4-6727c7674b42 · outbound

This paper cites Hybrid Models with Deep and Invertible Features.

Out-of-Distribution Detection Using Neural Rendering Generative Models Hybrid Models with Deep and Invertible Features

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-05-24T23:36:27.603430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a5193bcb-3803-4f11-9f44-46a49979f07b · outbound

This paper cites an unresolved cited work.

Out-of-Distribution Detection Using Neural Rendering Generative Models Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-05-24T23:36:27.832224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f723d2fc-5a08-4590-89f7-fc5e4e38b16a · outbound

This paper cites Striving for Simplicity: The All Convolutional Net.

Out-of-Distribution Detection Using Neural Rendering Generative Models Striving for Simplicity: The All Convolutional Net

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-05-24T23:36:27.576473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 77d0c706-b913-4efe-a41a-d1bfcd9fa06c · outbound

This paper cites Visualizing and Understanding Convolutional Networks.

Out-of-Distribution Detection Using Neural Rendering Generative Models Visualizing and Understanding Convolutional Networks

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:36:27.622942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e875e52e-c21d-40f9-bf3f-264b3b94e6b0 · outbound

This paper cites Efficient GAN-Based Anomaly Detection.

Out-of-Distribution Detection Using Neural Rendering Generative Models Efficient GAN-Based Anomaly Detection

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-05-24T23:36:27.611454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0f2abc27-181f-4ca9-8afc-fb413b7f464d · outbound

This paper cites cat" and reconstruction of cat from false label.

Out-of-Distribution Detection Using Neural Rendering Generative Models cat" and reconstruction of cat from false label

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:36:27.839110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.