Paper Citation Record · LEDGER

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2412.10765.

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

pith.paper-citation-record.v1
2412.10765 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:40:08.243328Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

35 of 35 outbound references displayed

verified exact11
verified fuzzy7
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ca2cc25-e458-4e3e-839b-a07c3a5c3172 · outbound

This paper cites Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.598598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 177cd8ca-8633-4c2b-843b-ab0e476e52f6 · outbound

This paper cites Pixel-wise Anomaly Detection in Complex Driving Scenes.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Pixel-wise Anomaly Detection in Complex Driving Scenes

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T15:40:08.581038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6d298dda-c247-4dc6-bd79-c0a58506e83e · outbound

This paper cites The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.087059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03e41c81-3877-4e73-91ec-90705526718c · outbound

This paper cites Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.550925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32d27dba-bdfa-4ecb-80c6-80c397378cc9 · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.790042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 52a5615a-2458-42f2-b044-e3ad76755c0b · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.775860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 58ea5883-4978-4213-a44c-547c362c4160 · outbound

This paper cites Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.108501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57ac706b-a517-432b-8a9e-3e4347dcc784 · outbound

This paper cites G., Kirillov, A., and Gird- har, R.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation G., Kirillov, A., and Gird- har, R

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.761326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 10d23e7c-4325-4986-81c0-0e82a724f0e7 · outbound

This paper cites G., and Kirillov, A.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation G., and Kirillov, A

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.747332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0190eb2d-c39c-471d-baed-7cb4d3e58824 · outbound

This paper cites The Cityscapes Dataset for Semantic Urban Scene Understanding.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation The Cityscapes Dataset for Semantic Urban Scene Understanding

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.125116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70aa4591-a38b-49ad-9c2b-0cec8eb80d07 · outbound

This paper cites Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Improving Reconstruction Autoencoder Out-of-distribution Detection with Mahalanobis Distance

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.130172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1500a7c-b24a-46fa-afd8-fb4e780a1ab1 · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.735005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1f92a0f1-d3cb-4a15-93c7-cb9eb61099ca · outbound

This paper cites Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.492221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 12a3efd4-d15e-45b2-ad01-5d9d85b02a01 · outbound

This paper cites and Gimpel, K.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation and Gimpel, K

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.723041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d29f68cb-005d-4d13-942b-a6c66d587e00 · outbound

This paper cites OpenReview.net.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation OpenReview.net

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.710113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 938b4e95-1edd-4a2e-a36b-3bd88cf99054 · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.696024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 91584aa9-41e1-4314-a98f-25c71e178c96 · outbound

This paper cites Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.161418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63254c9f-3398-4745-870a-25a59231b971 · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.165627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51ec1ab8-f3d0-4171-8dd0-46d37de12bb8 · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.675507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1e2239fe-86db-4038-a4a3-0a066a778d4c · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.663033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c84419b-d53a-4296-988b-10c64cbe7c8b · outbound

This paper cites Uncertainty Aware Proposal Segmentation for Unknown Object Detection.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Uncertainty Aware Proposal Segmentation for Unknown Object Detection

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.461133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 246e0ff8-fc02-4fe8-afdf-42b3af7ebdde · outbound

This paper cites an unresolved cited work.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-11T15:40:08.649710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 78d52f19-4123-40a0-be2d-f188f0d0cda0 · outbound

This paper cites OpenReview.net.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation OpenReview.net

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.636303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 62fd5722-2b15-4a9a-b7ea-96533646fb89 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Microsoft COCO: Common Objects in Context

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.193373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a9a90dd-8027-47c9-a70f-07d4c0b358e1 · outbound

This paper cites Detecting the Unexpected via Image Resynthesis.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Detecting the Unexpected via Image Resynthesis

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T15:40:08.428569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c20ee0ee-be61-4cc1-b9be-333c4ac1cf2a · outbound

This paper cites F., and Güney, F.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation F., and Güney, F

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.624075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 361a4ae2-439e-44e3-8622-2714a573f0a8 · outbound

This paper cites Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.408715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1acd7731-3d03-48ae-859f-84cd98e26516 · outbound

This paper cites Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.388844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f12d6ee2-0226-41c3-a2df-719c2b25228f · outbound

This paper cites N., Cermelli, F., Fontanel, D., Masone, C., and Ca- puto, B.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation N., Cermelli, F., Fontanel, D., Masone, C., and Ca- puto, B

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:40:08.612115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d4518248-13f1-47a7-a382-3773acd3e5b2 · outbound

This paper cites Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.372208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d2893111-498a-4441-94c7-e583741d661b · outbound

This paper cites Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.355979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 76be2522-865e-45d3-a4c6-0fb4e8965ba6 · outbound

This paper cites Identifying Unknown Instances for Autonomous Driving.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Identifying Unknown Instances for Autonomous Driving

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.337498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d56eed99-b1e9-4c3e-b893-8c537827f609 · outbound

This paper cites Wider or Deeper: Revisiting the ResNet Model for Visual Recognition.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Wider or Deeper: Revisiting the ResNet Model for Visual Recognition

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T15:40:08.234490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd09d63-82c1-4b80-bf7e-bc169cc7cc4c · outbound

This paper cites Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.306527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 79248c7f-3ec7-47bc-9497-500cf6484246 · outbound

This paper cites Improving Semantic Segmentation via Video Propagation and Label Relaxation.

Neural Network Meta Classifier: Improving the Reliability of Anomaly Segmentation Improving Semantic Segmentation via Video Propagation and Label Relaxation

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:40:08.284680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.