Paper Citation Record · LEDGER

Multimodal HD Mapping for Intersections by Intelligent Roadside Units

As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2507.08903.

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

pith.paper-citation-record.v1
2507.08903 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:24:51.445863Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

22 of 22 outbound references displayed

verified exact0
verified fuzzy17
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57b81c6b-8f6d-4a12-9af1-ce951bc61551 · outbound

This paper cites Hdmapnet: An online hd map construction and evaluation framework,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Hdmapnet: An online hd map construction and evaluation framework,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:53.657719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a9a67dac-b691-4ee8-8aae-8267e8b2f11a · outbound

This paper cites MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:26.077528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41d3311b-95c3-4434-8693-e22acc97dfd1 · outbound

This paper cites Mgmap: Mask-guided learning for online vectorized hd map construction,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Mgmap: Mask-guided learning for online vectorized hd map construction,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:26.206822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0269ce6-13ad-4dce-84e1-fb7642107ba7 · outbound

This paper cites V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:53.557738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 896fccc8-332a-4772-8634-f7cdbbdc50aa · outbound

This paper cites Design and implementation of edge-fog-cloud system through hd map generation from lidar data of autonomous vehicles,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Design and implementation of edge-fog-cloud system through hd map generation from lidar data of autonomous vehicles,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:53.463787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b55f5481-86c2-4ca5-a393-c22aac6fc126 · outbound

This paper cites Pointpillars: Fast encoders for object detection from point clouds,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Pointpillars: Fast encoders for object detection from point clouds,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:53.364306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7806bf7-a876-4b67-af7e-d5a5872e2d9d · outbound

This paper cites Bevfusion: A simple and robust lidar-camera fusion framework,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Bevfusion: A simple and robust lidar-camera fusion framework,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:53.167091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 674819aa-0ab0-4d30-8da0-4627cd898ece · outbound

This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:53.041741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6d1df1da-06ab-44cd-9133-f6bcf0325db0 · outbound

This paper cites Second: Sparsely embedded convolutional detection,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Second: Sparsely embedded convolutional detection,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:50.456597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e25fdb6a-2037-4161-9947-febdccd5b2fb · outbound

This paper cites Superfusion: Multilevel lidar-camera fusion for long- range hd map generation,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Superfusion: Multilevel lidar-camera fusion for long- range hd map generation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.963299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f350c49-57b5-4c9d-a4ba-7a988f3c23cc · outbound

This paper cites V2x-vit: Vehicle-to-everything cooperative perception with vision transformer,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units V2x-vit: Vehicle-to-everything cooperative perception with vision transformer,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.873023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 87e0189b-6f62-4634-9f94-ac4e33a02456 · outbound

This paper cites Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.770414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 045c4b44-7f48-4cc4-94be-35680bdbe648 · outbound

This paper cites Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.652573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c837b143-21f0-4305-8c65-a3ee1959c8ef · outbound

This paper cites Tumtraf v2x cooperative perception dataset,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Tumtraf v2x cooperative perception dataset,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.520925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b246d3e9-9e32-42ce-aaec-021f269f21f8 · outbound

This paper cites Vi-map: Infrastructure-assisted real-time hd mapping for autonomous driving,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Vi-map: Infrastructure-assisted real-time hd mapping for autonomous driving,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.339850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 77c874ee-b547-4173-bc96-2ed542be0af7 · outbound

This paper cites Carla: An open urban driving simulator,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Carla: An open urban driving simulator,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:51.055662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12a86c65-1201-4a2f-9579-59ae405a4d46 · outbound

This paper cites Denoising of a multi- station point cloud and 3d modeling accuracy for substation equipment based on statistical outlier removal,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Denoising of a multi- station point cloud and 3d modeling accuracy for substation equipment based on statistical outlier removal,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:52.065409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ff42cde6-160b-4dba-b54e-039f0988ed64 · outbound

This paper cites Three-dimensional alpha shapes,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Three-dimensional alpha shapes,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:51.914753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5ad0f6bb-566b-43c4-b9d4-f2d98ddd634b · outbound

This paper cites Least-squares fitting of a straight line,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Least-squares fitting of a straight line,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:51.825713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b91af7e-3044-4633-a8bc-6d79fdd2dc21 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units U-net: Convolutional networks for biomedical image segmentation,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:51.328844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f26aeba6-f6b8-4a64-a31c-69b7c1313734 · outbound

This paper cites Pidnet: A real-time semantic segmentation network inspired by pid controllers,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Pidnet: A real-time semantic segmentation network inspired by pid controllers,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:51.712347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a6c48d3-ffa3-4088-b46b-8b6a9aedeaa5 · outbound

This paper cites Vision transformer adapter for dense predictions,.

Multimodal HD Mapping for Intersections by Intelligent Roadside Units Vision transformer adapter for dense predictions,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:24:51.594130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.