Paper Citation Record · LEDGER

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving

As of 14 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2411.18860.

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

pith.paper-citation-record.v1
2411.18860 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:54:44.722646Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T14:36:18.415384Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T06:19:38.199121Z

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy18
unresolved15
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e9e5146-b70b-4d8c-8d4b-e699fd04faec · outbound

This paper cites Revisiting batch normalization for improving cor- ruption robustness.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Revisiting batch normalization for improving cor- ruption robustness

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.226359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e1ade9c9-1a9d-4cd0-92d5-7ec1c523d8a9 · outbound

This paper cites End to End Learning for Self-Driving Cars.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving End to End Learning for Self-Driving Cars

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.576007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a06102d2-f965-4a9b-b293-3306f7b6eb48 · outbound

This paper cites Parameter-free online test-time adaptation.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Parameter-free online test-time adaptation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.580880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfd13fc2-abc4-4b15-a0e5-0f85aebc1c6a · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving nuscenes: A multi- modal dataset for autonomous driving

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.585327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8f1ba14-82ef-485b-8675-1cc614a617ef · outbound

This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Improved Regularization of Convolutional Neural Networks with Cutout

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.589820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d35ce8b-cb5a-4865-a9da-d49447aef5b4 · outbound

This paper cites Learning depth-guided con- volutions for monocular 3d object detection.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Learning depth-guided con- volutions for monocular 3d object detection

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.594630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d4da47e-ce93-4c6a-b374-723d4ce19b58 · outbound

This paper cites Test time adaptation through perturba- tion robustness.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Test time adaptation through perturba- tion robustness

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.185240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0a330d2c-943c-4c32-940c-d2e3e59a793e · outbound

This paper cites Vision meets robotics: The kitti dataset.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Vision meets robotics: The kitti dataset

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.603976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40fb55c5-b873-4121-bca8-03312f74de64 · outbound

This paper cites Test-time classifier adjustment module for model-agnostic domain generaliza- tion.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Test-time classifier adjustment module for model-agnostic domain generaliza- tion

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.160421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bea94ac6-8838-43fc-b23d-5ae92eb1b606 · outbound

This paper cites Groomed-nms: Grouped mathematically differentiable nms for monocular 3d object detection.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Groomed-nms: Grouped mathematically differentiable nms for monocular 3d object detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.144465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2919a386-08a3-47c6-b0e0-49e77b5b8472 · outbound

This paper cites Adaptive batch normalization for practical do- main adaptation.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Adaptive batch normalization for practical do- main adaptation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.129920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 25f599c9-8614-447f-9ccb-df44ced93bcc · outbound

This paper cites On the robust- ness of open-world test-time training: Self-training with dy- namic prototype expansion.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving On the robust- ness of open-world test-time training: Self-training with dy- namic prototype expansion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.115356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6950e78b-f215-47b6-9689-68b84c419efe · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.100553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1096f127-460e-4784-a636-35880e815edc · outbound

This paper cites A comprehensive sur- vey on test-time adaptation under distribution shifts.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving A comprehensive sur- vey on test-time adaptation under distribution shifts

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.630474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22ddcc83-43e5-4c68-b247-a7bfb2316319 · outbound

This paper cites Fully Test-Time Adaptation for Monocular 3D Object Detection.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Fully Test-Time Adaptation for Monocular 3D Object Detection

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-12T10:54:44.821791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation adf7b985-9788-41d9-a5d2-7fa716a237c5 · outbound

This paper cites Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.639315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ed2a64f-ec46-4be5-9b44-55a4e7d8ba7f · outbound

This paper cites Ttt++: When does self-supervised test-time training fail or thrive? Advances in Neural Information Processing Systems , 34: 21808–21820, 2021.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Ttt++: When does self-supervised test-time training fail or thrive? Advances in Neural Information Processing Systems , 34: 21808–21820, 2021

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.076278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fde786b8-e309-4283-ad70-6cf6fd8fd9b2 · outbound

This paper cites Efficient test-time model adaptation without forgetting.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Efficient test-time model adaptation without forgetting

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.061685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fdf9e728-1af1-4aa9-ba04-65006c896aa4 · outbound

This paper cites Towards Stable Test-Time Adaptation in Dynamic Wild World.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Towards Stable Test-Time Adaptation in Dynamic Wild World

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.652528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55047989-5dcf-4f7c-a598-ec392de78ec7 · outbound

This paper cites Improving robustness against common corruptions by covariate shift adaptation.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Improving robustness against common corruptions by covariate shift adaptation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.047179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a0bebc70-c918-4326-bb26-86345cce49b0 · outbound

This paper cites Test-time training with self- supervision for generalization under distribution shifts.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Test-time training with self- supervision for generalization under distribution shifts

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.660911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fd6cd30-6120-4dba-8825-d663023ce55b · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.665384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c5833e4-7627-4217-9bfe-e2ff6f180bff · outbound

This paper cites Detr3d: 3d object detection from multi-view images via 3d-to-2d queries.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Detr3d: 3d object detection from multi-view images via 3d-to-2d queries

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.023541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0ae3b00b-70bd-455e-9c8f-7346c5fc0f86 · outbound

This paper cites Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective su- pervision.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective su- pervision

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:45.008690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2ae54165-541d-408a-8bfa-0b2d75d4fab9 · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.678537Z

Source-reported events for the cited work

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Observation c203fbf9-f5d0-422f-91ac-d55d91dc5d85 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving mixup: Beyond Empirical Risk Minimization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T10:54:44.682672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8443685b-ef2e-40c4-9d28-bc97b982e421 · outbound

This paper cites Do- mainadaptor: A novel approach to test-time adaptation.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Do- mainadaptor: A novel approach to test-time adaptation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:44.984486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6b921feb-6e7e-41bc-86c6-cfdebbb3f7cb · outbound

This paper cites Adaptive risk min- imization: Learning to adapt to domain shift.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Adaptive risk min- imization: Learning to adapt to domain shift

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:44.969415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 197fcb57-1020-4d74-8d60-a2dc44bbbe9e · outbound

This paper cites Objects are differ- ent: Flexible monocular 3d object detection.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Objects are differ- ent: Flexible monocular 3d object detection

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:44.955228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b024a492-669f-43af-99ab-134f2e8b91f9 · outbound

This paper cites Adanpc: Exploring non-parametric classifier for test-time adaptation.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Adanpc: Exploring non-parametric classifier for test-time adaptation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:44.939899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d8d7b882-0386-406e-a56b-838a167201a5 · outbound

This paper cites Un- derstanding the robustness of 3d object detection with bird’s- eye-view representations in autonomous driving.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Un- derstanding the robustness of 3d object detection with bird’s- eye-view representations in autonomous driving

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:44.924798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4b3533ee-2d4c-45df-80a7-e65ecf44e7e9 · outbound

This paper cites The devil is in the task: Exploiting reciprocal appearance-localization features for monocular 3d object de- tection.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving The devil is in the task: Exploiting reciprocal appearance-localization features for monocular 3d object de- tection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T10:54:44.910020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 738c2a6e-a2d2-4e75-9a57-be761b52d3e7 · outbound

This paper cites an unresolved cited work.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-12T10:54:44.895135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5f68b58e-0fd2-49b7-939f-bd2f29768d1a · outbound

This paper cites an unresolved cited work.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-12T10:54:44.880803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ce088890-8894-48a3-985c-320e82ba1478 · outbound

This paper cites Severity setting details The three Severity settings for each corruption are consis- tent with the severity settings used in Nuscenes-C, as shown in the Table 5.

Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving Severity setting details The three Severity settings for each corruption are consis- tent with the severity settings used in Nuscenes-C, as shown in the Table 5

Reference 35

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T10:54:44.865815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation 60373ac6-549a-4018-a158-c5b76086a804 · inbound

A DVDrive Approach for doScenes Instructed Driving Challenge cites this paper.

A DVDrive Approach for doScenes Instructed Driving Challenge Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:19:38.200758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.