Paper Citation Record · LEDGER

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording

As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2507.04529.

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

pith.paper-citation-record.v1
2507.04529 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:50:41.293252Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T11:45:32.281685Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T11:49:58.943969Z

Reference resolution

31 of 31 outbound references displayed

verified exact9
verified fuzzy18
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a1a788ab-e3e7-409a-b5f6-c6b303f415cc · outbound

This paper cites CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Research.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Research

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:50:41.527340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 418144a5-b243-4a66-af01-6783faf7102f · outbound

This paper cites Curse of rarity for autonomous vehicles,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Curse of rarity for autonomous vehicles,

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T19:50:41.343059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b85cccfb-2e7c-4b4d-8e37-d730e65a3cd1 · outbound

This paper cites Iso/pas 8800:2024 road vehicles — safety and artificial intel- ligence,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Iso/pas 8800:2024 road vehicles — safety and artificial intel- ligence,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.687119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 733a0033-40af-459e-8c99-6a5d311a5f85 · outbound

This paper cites Statistical consideration of the representativeness of open road tests for the validation of automated driving systems,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Statistical consideration of the representativeness of open road tests for the validation of automated driving systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.678386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 08c7064b-e8df-460b-81cd-a51d7dd403fa · outbound

This paper cites Towards a data engineering process in data-driven systems engineering,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Towards a data engineering process in data-driven systems engineering,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.669048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a4ccdda-e1a9-4a74-84d4-475f29b4a33b · outbound

This paper cites Systematization of corner cases for visual perception in automated driving,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Systematization of corner cases for visual perception in automated driving,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.660751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f5302a7f-3516-4b29-bb3b-cd9612381a69 · outbound

This paper cites The fishyscapes benchmark: Measuring blind spots in semantic segmentation,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording The fishyscapes benchmark: Measuring blind spots in semantic segmentation,

Reference 7

Resolution: verified exact; doi, observed 2026-08-06T19:50:41.332174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7ff18d80-3d61-449b-86cd-53a3c1ab5e8b · outbound

This paper cites Segmentmeifyoucan: A benchmark for anomaly segmentation,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Segmentmeifyoucan: A benchmark for anomaly segmentation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.652316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a45c9f20-5d4b-4eca-87be-fceb89545274 · outbound

This paper cites Scaling out-of-distribution detection for real-world settings,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Scaling out-of-distribution detection for real-world settings,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.643280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c18ef2e5-8e22-4472-86d2-d7c815d295ae · outbound

This paper cites AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:50:41.321208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a76804e-8fe3-4d31-b35a-e713bad8141a · outbound

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

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:50:41.228184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 151f983e-84f8-4753-8ea9-eeaedc286176 · outbound

This paper cites Densely connected normalizing flows.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Densely connected normalizing flows

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:50:41.507890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5661dad1-1b1c-4712-b424-05735e25b2f2 · outbound

This paper cites Predictive Uncertainty Estimation via Prior Networks.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Predictive Uncertainty Estimation via Prior Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T19:50:41.235633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83b90f13-38a1-4739-989d-8e6ba1f3e23b · outbound

This paper cites Fast and scalable outlier detection with approximate nearest neighbor ensembles,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Fast and scalable outlier detection with approximate nearest neighbor ensembles,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.634610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bbd951b5-af89-4ba5-8e6b-d79cecff9ff9 · outbound

This paper cites Algorithms for mining distance-based outliers in large datasets,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Algorithms for mining distance-based outliers in large datasets,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.625767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 529092ad-860f-4874-a9f2-099f6c41aabc · outbound

This paper cites Deep Transfer Learning for Multiple Class Novelty Detection ,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Deep Transfer Learning for Multiple Class Novelty Detection ,

Reference 16

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:50:41.488736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a3bb991-7dc1-4b36-a6cf-a2b1728822fe · outbound

This paper cites Unsupervised anomaly detection with generative adver- sarial networks to guide marker discovery,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Unsupervised anomaly detection with generative adver- sarial networks to guide marker discovery,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.616715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4ceb90b4-a8c8-4987-8ff5-2bf68c978f8a · outbound

This paper cites Isolation forest for anomaly detection in raw vehicle sensor data,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Isolation forest for anomaly detection in raw vehicle sensor data,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.607429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3682acbd-5c8f-4eb3-ba62-7a88fe013f27 · outbound

This paper cites f-anogan: Fast unsupervised anomaly detection with generative adversarial networks,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording f-anogan: Fast unsupervised anomaly detection with generative adversarial networks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.598009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f95e6dc4-9cda-4f4b-9e40-d49f02b93601 · outbound

This paper cites CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:50:41.392761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation aaf0bb0b-b37d-4643-9885-8372846c0a66 · outbound

This paper cites Submodularity in data subset selection and active learning,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Submodularity in data subset selection and active learning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.588726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0ce63cc7-0f7a-469e-8f13-0fd30b8fb896 · outbound

This paper cites Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:50:41.381095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0c6efdfe-51d6-49a1-9844-400f4c73c225 · outbound

This paper cites Semantic Redundancies in Image-Classification Datasets: The 10% You Don't Need.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Semantic Redundancies in Image-Classification Datasets: The 10% You Don't Need

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T19:50:41.269090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cec222c9-384f-4322-85d8-861e299975c1 · outbound

This paper cites Making stochastic neural networks from deterministic ones,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Making stochastic neural networks from deterministic ones,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.580605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7638c286-675d-4873-9937-57886a595c6e · outbound

This paper cites Deepcore: A comprehensive library for coreset selection in deep learning,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Deepcore: A comprehensive library for coreset selection in deep learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.572124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3251465a-e7e4-4de5-a8fe-d35286d1f139 · outbound

This paper cites Coresets for data- efficient training of machine learning models,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Coresets for data- efficient training of machine learning models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.562847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9a518858-a07e-4d6f-b6c0-8a188b7794c5 · outbound

This paper cites GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T19:50:41.280850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b222f16d-cac2-4fb5-ae13-e81f446aa154 · outbound

This paper cites Behavior Forests: Real-Time Discovery of Dynamic Behavior for Data Selection.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Behavior Forests: Real-Time Discovery of Dynamic Behavior for Data Selection

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:50:41.354908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9a0223de-bd51-4560-a973-decae5b47c1d · outbound

This paper cites Fast and efficient image novelty detection based on mean- shifts,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Fast and efficient image novelty detection based on mean- shifts,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.554091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 66a92eb8-ddac-45c2-a988-87dd018147a9 · outbound

This paper cites Honey, i shrunk the sample covariance matrix,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording Honey, i shrunk the sample covariance matrix,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.544771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 03e235ff-e0f0-44a2-85aa-4894f4e215fe · outbound

This paper cites The German Traffic Sign Recognition Benchmark: A multi-class classification com- petition,.

A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording The German Traffic Sign Recognition Benchmark: A multi-class classification com- petition,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:50:41.535856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation d01c6444-4e5b-47c8-884f-ad9423e43d61 · inbound

A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection cites this paper.

A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection A Data-Driven Novelty Score for Diverse In-Vehicle Data Recording

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:49:58.946852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.