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Paper Citation Record · LEDGER

Multimodal HD Mapping for Intersections by Intelligent Roadside Units

As of 17 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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:26.056454Z digest=sha256:e6d872e2610ba5452934e00e1a2e4fc8b67bb77b4cbcff9ff3fc759b120a3e58

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.

source=pdf_text observed=2026-08-06T18:24:26.077528Z digest=sha256:469267a044d376d2167ee423c78370d9402d2c40e19692205da49dac87d50a2d

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.

source=pdf_text observed=2026-08-06T18:24:26.206822Z digest=sha256:6d1c94cd1f62e8000a0e31b31795c79236657366098a44adb7ce26fab9afbb4e

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:26.297230Z digest=sha256:9938d93c883875801239f165b22b1c263abf53dd2a53b6fc915d61c72808d835

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:26.443079Z digest=sha256:2490a7392deb5ae65e0443fd46fb727fb18762acb34ba9729919fdb406732a29

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:26.520688Z digest=sha256:1000661b4294b80e1625cef58a5854508a2211eece5cb5df455f7ccf040a6fd7

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:26.583333Z digest=sha256:be0e8a2b1205436b00bf60bbc62e1a0cbf21b48997557f0617310926b8861563

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.359477Z digest=sha256:e7bb700cb58309ba9a24eb2526936e461a3bab7a02991f6e18d3ca397f9ffe0c

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.

source=pdf_text observed=2026-08-06T18:24:50.456597Z digest=sha256:14969d1b0c4f18e2e2eb660ad471a0d5d1838369dc5054c9b13c699e1747313a

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.498116Z digest=sha256:723ad9f19553d7d81b48e8c708474bf45321fb2d465f17c674287744f55616e3

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.641296Z digest=sha256:bc9a753851444cf705460572ef73e20595f2fba2372fa2c394b8a67182da5781

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.721459Z digest=sha256:7ea8635a21162708791eee13d8deb0008742fea12c6331a32c29ce9352ab25e4

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.780576Z digest=sha256:e23c5b4ebb531a83663f46004174b7b0920e0d70c49404327b53b7d1432b1da3

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.875455Z digest=sha256:88fa813b96744f03826de6bcc10903869709a7a2ffc5f4ba881c841ad99bab42

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:50.966862Z digest=sha256:1d7f96391f071cff5a232332726b3a20522f20360dd3359936518ec72a10ac90

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.

source=pdf_text observed=2026-08-06T18:24:51.055662Z digest=sha256:93e58daf9670ba030da33f7adb6936f804f7484973384609fcb0750956df4936

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:51.097534Z digest=sha256:b5f3278d9b4b9e0d7e0f0e7f68d1dc4706b5daff29a6213658bd46a8f00589f9

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:51.180532Z digest=sha256:76ed53e9bce1850253a3cd50d8bef24fd3b38447e4a08af0472a0e7f50513511

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:51.254048Z digest=sha256:782b12ef9dec4fa1d2ff827b5b31e0cc728576b43716a1a5878e3b8d623155ef

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.

source=pdf_text observed=2026-08-06T18:24:51.328844Z digest=sha256:45a0905efa64d1bc340ec56a31e9ed1f165278c60b72170cd4892a89d7d08d9b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:51.399138Z digest=sha256:39708eea9a0963f271f9198b04cd9c5abae64b20a83d8ebcd80c7a8d6662fce6

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-06T18:24:51.445863Z digest=sha256:14b19c57656a869654f66262a2d7697004901aee62f5ba88d4a81e1a869f44c5

Pith citing papers

No inbound Pith citation observations are available.