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Paper Citation Record · LEDGER

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets

As of 18 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2505.00584.

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

pith.paper-citation-record.v1
2505.00584 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:42:39.353305Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

19 of 19 outbound references displayed

  • verified exact1
  • verified fuzzy8
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a19371a3-f055-45ac-a138-ade81510490f · outbound

This paper cites Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Survey

Reference 1

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no resolver link, observed 2026-08-16T04:42:39.291010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b9ddc618-9b78-4243-b233-c88931a40183 · outbound

This paper cites DETRs with Collaborative Hybrid Assignments Training.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets DETRs with Collaborative Hybrid Assignments Training

Reference 2

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unresolved
no resolver link, observed 2026-08-16T04:42:39.295238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7ad743bd-f53b-447a-b35e-e886d2af59d0 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Microsoft COCO: Common Objects in Context

Reference 3

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no resolver link, observed 2026-08-16T04:42:39.298956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.298956Z digest=sha256:d8244a3c4ac58e5768c0ff1b4c4ec9d706cb350e19d7ae2ba0cf9ba7d2c2d65a

Observation 39f140c3-0c49-4bad-8132-9f8255b2f83c · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets nuscenes: A multimodal dataset for autonomous driving,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.608395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.302683Z digest=sha256:d1d58637d9fe5c92eca89117e59c888bd26ed3895d6de029922a2c4a3acb1442

Observation 201b73c4-0bc1-47fa-805d-89cdbd339485 · outbound

This paper cites Sparse4D v3: Advancing End-to-End 3D Detection and Tracking.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Sparse4D v3: Advancing End-to-End 3D Detection and Tracking

Reference 5

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unresolved
no resolver link, observed 2026-08-16T04:42:39.306484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.306484Z digest=sha256:5966a58a000b82f46e8a7d723043af5dfbfd089169fa42bf85a2d65bfe56defb

Observation 578e2cf0-8b60-43d4-8758-a7609a71b21f · outbound

This paper cites 3d multi-object tracking: A baseline and new evaluation metrics,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets 3d multi-object tracking: A baseline and new evaluation metrics,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.598425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.310031Z digest=sha256:ee58e467987c669d137887eb811361067bca1a5fab337a0941419d4c7026ce58

Observation 0f9dccaa-f086-4162-a5d0-62bd961e6d51 · outbound

This paper cites Center-based 3D Object Detection and Tracking.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Center-based 3D Object Detection and Tracking

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T04:42:39.313660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.313660Z digest=sha256:f00f96c6f371889aa14bbd067197dba789b8e592c8bd0b21425529206a4c1aeb

Observation f0cbc99e-e5b3-4b95-876a-c187ac8ed057 · outbound

This paper cites Rcbevdet++: Toward high-accuracy radar-camera fusion 3d perception network,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Rcbevdet++: Toward high-accuracy radar-camera fusion 3d perception network,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.588243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 798c235e-8d90-4bac-abd3-866abaf98894 · outbound

This paper cites A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-16T04:42:39.463448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.324001Z digest=sha256:8810156d7fcb488062173ae8b32d66a7fb008360752f9331cc694c8169b081f4

Observation 964dff9d-2afe-456d-815a-e165cacf91e0 · outbound

This paper cites an unresolved cited work.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Unresolved cited work

Reference 10

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unresolved
raw_fallback, observed 2026-08-16T04:42:39.578701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 56617ee2-e4b5-4ee1-92aa-c95766aaeffd · outbound

This paper cites Automotive radars: A review of signal processing techniques,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Automotive radars: A review of signal processing techniques,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.568773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.330810Z digest=sha256:64c99e8283f77fae7a85aa39840e0035ef165a4d5b963b7e56f26f8bd8169000

Observation 7ceafe2a-11d6-4af5-a9fc-7f8ef2dc3b05 · outbound

This paper cites Survey on lidar perception in adverse weather conditions,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Survey on lidar perception in adverse weather conditions,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.558759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.334132Z digest=sha256:9ac18605878beb935f9ca43f729cb3641d3b82e943b1fcc653b6a9bac1ddae50

Observation 16199c1b-c5b2-4571-a02f-4ea06ec912e0 · outbound

This paper cites Radiant: Radar-image association network for 3d object detection,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Radiant: Radar-image association network for 3d object detection,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.548965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c1d9ae03-28d1-4b63-9b7c-d1759b04da4c · outbound

This paper cites Crn: Camera radar net for accurate, robust, efficient 3d perception,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Crn: Camera radar net for accurate, robust, efficient 3d perception,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.538412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.340720Z digest=sha256:393ce4e17abacf60bb056dfe331d437b6befbf1cc8f6dfb205da27a1195d946f

Observation e28fe129-807e-4a14-b1f0-73344feb9a9c · outbound

This paper cites RadSegNet: A Reliable Approach to Radar Camera Fusion.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets RadSegNet: A Reliable Approach to Radar Camera Fusion

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T04:42:39.343837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.343837Z digest=sha256:3047ad295bc6d190efe52bed8b6caa06f386b51186050cd0167b3b42c54d43df

Observation b8fbd432-0568-4656-8c2d-03d700e2cf4e · outbound

This paper cites Immfusion: Robust mmwave-rgb fusion for 3d human body reconstruction in all weather conditions,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Immfusion: Robust mmwave-rgb fusion for 3d human body reconstruction in all weather conditions,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T04:42:39.347054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.347054Z digest=sha256:f24c50b262b8a525aff4520a20a90e7e304473365fc116c772055f35fff3cb8e

Observation 4668534f-4d7b-430a-9050-12b7b906310f · outbound

This paper cites Precision and accuracy in radar measurements,.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets Precision and accuracy in radar measurements,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:42:39.527169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T04:42:39.350243Z digest=sha256:7d2a906e77896b4d0c3d894685a3f636288a98d40e2a5dce71ee93f12436699c

Observation a9b0c08c-6e08-407e-960f-1603ce231da4 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-16T04:42:39.353305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.353305Z digest=sha256:247c681753cbf2de38adb8a0a72bb4bbd1ae3d8cc08a376f0755bd58a6f8f71e

Observation 85b60e16-a295-47e1-8740-c1593f9541d6 · outbound

This paper cites RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network.

Synthesizing and Identifying Noise Levels in Autonomous Vehicle Camera Radar Datasets RCBEVDet++: Toward High-accuracy Radar-Camera Fusion 3D Perception Network

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-16T04:42:39.320401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:39.320401Z digest=sha256:8c79eabbb575f6b76e43f860ff280c16263b8c1a5837dcbe6aa9f4b837dd8ecd

Pith citing papers

No inbound Pith citation observations are available.