Paper Citation Record · LEDGER

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic

As of 9 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2606.07626.

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

pith.paper-citation-record.v1
2606.07626 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T19:14:49.785091Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

48 of 48 outbound references displayed

verified exact5
verified fuzzy0
unresolved42
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b3a562b6-28d2-4fb0-8b81-cf26873db616 · outbound

This paper cites arXiv preprint arXiv:2410.07701 (2024).

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic arXiv preprint arXiv:2410.07701 (2024)

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:34.783406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 02ea56e5-917c-41c2-92bb-340d7a2a98e2 · outbound

This paper cites and Dong, Y.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Dong, Y

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 728ef5bf-1ad9-44d6-9b3e-9f34933ca88b · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c7f8058-763c-4028-bc0a-8eeed6360bd7 · outbound

This paper cites and Song, R.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Song, R

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71bc5368-62a3-40ea-9800-4e2358f735c2 · outbound

This paper cites Solving Scene Understanding for Autonomous Navigation in Unstructured Environments.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Solving Scene Understanding for Autonomous Navigation in Unstructured Environments

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:34.781878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9eb99ac1-52f2-4db1-a252-52481293feb4 · outbound

This paper cites Hybrid Human-Machine Perception via Adaptive LiDAR for Advanced Driver Assistance Systems.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Hybrid Human-Machine Perception via Adaptive LiDAR for Advanced Driver Assistance Systems

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:34.780846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 847b6d02-fd82-432d-917a-93107995de5e · outbound

This paper cites and Trivedi, M.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Trivedi, M

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1eeea1e8-beea-4ee3-9e61-998d9c73a296 · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 629d2ed3-5299-40c8-aa4c-cce8759fe154 · outbound

This paper cites and Lenz, P.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Lenz, P

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1a2bd2b-2e1c-403c-99b9-b066a28dd6af · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6b3663e-48d4-4848-b2a2-bcc6ad018375 · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f94bb06-b5eb-452f-a7e9-43eb60e02432 · outbound

This paper cites and Subramanian, A.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Subramanian, A

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

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Observation e0600ef4-2a9b-40d2-baa3-dbf2d1d25467 · outbound

This paper cites and Hafez, A.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Hafez, A

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab9461e1-f46c-4a4b-af57-100b0cde6901 · outbound

This paper cites DriveIndia: An Object Detection Dataset for Diverse Indian Traffic Scenes.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic DriveIndia: An Object Detection Dataset for Diverse Indian Traffic Scenes

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:34.792409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f312ca89-be72-4b99-9d3f-299a49c97f50 · outbound

This paper cites and Wen, C.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Wen, C

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9defae9-44b4-4123-b52b-9932001a4f2b · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8900e88-66bb-4873-a305-525c0c1aba17 · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae2063c8-8f0b-4f4f-928c-d07f5ff78c5f · outbound

This paper cites and Sun, Y.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Sun, Y

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76067ce6-fc3d-44a1-895f-f7ae12b088f6 · outbound

This paper cites and Qi, C.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Qi, C

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70712a84-df32-4548-be7a-6ff4cb12dfaf · outbound

This paper cites and Tang, H.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Tang, H

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96ec6ddb-3926-4905-af17-574985a3c83f · outbound

This paper cites and Gong, B.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Gong, B

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aadb9116-54e1-4bad-969d-b24894e50d6e · outbound

This paper cites and Tuzel, O.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Tuzel, O

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 006afd24-b62f-47f0-89f4-b084f71864a0 · outbound

This paper cites and Mao, Y.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Mao, Y

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de9b92a3-b880-4943-aa38-a8a45a550f4e · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3b229ea-7fd4-4a8f-b536-33396805909e · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 830ab4cc-a215-4c39-a323-6314fa90a064 · outbound

This paper cites and Zhou, X.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Zhou, X

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea8541c3-c184-42e5-b5ce-f6c202712e7a · outbound

This paper cites and Gwak, J.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Gwak, J

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3403668-c1af-4e36-8ab1-5d28f596e6c4 · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b62869c7-f64b-4d36-84b8-b80f4780eafd · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3594ed90-31f9-46c2-b8e8-e6b39804b13d · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

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Observation 2b861d21-b28b-4f5f-af1f-3e9b7fbbaed7 · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 360ae5af-56af-4bca-a95e-77d5d002012a · outbound

This paper cites A2D2: Audi Autonomous Driving Dataset.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic A2D2: Audi Autonomous Driving Dataset

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-07-29T00:24:28.889631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d6865de-2265-4e4d-8a74-9d99b0722430 · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cacb006-321f-4dd9-bfc7-b624590082d7 · outbound

This paper cites and Hamprecht, F.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Hamprecht, F

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7af1f71-7d5c-4b60-863d-f0a6cbb39fa3 · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 830cd902-3721-4a30-aab2-d91d2a7e4915 · outbound

This paper cites and Hu, Q.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Hu, Q

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b21641a-544a-4604-890e-996b87d5f2a9 · outbound

This paper cites and Stanton, S.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Stanton, S

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c7e41fd-a5b8-4a38-b86d-2fd75cd4902d · outbound

This paper cites and Hou, Z.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Hou, Z

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69a393b5-e3d0-4cbc-af18-8166fca72692 · outbound

This paper cites Towards autonomous driving: A multi-modal.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Towards autonomous driving: A multi-modal

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34966e6d-c6d9-485a-b5de-4457faba3baf · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 673b1d44-654f-402f-905f-da8cb44364bd · outbound

This paper cites and Liang, M.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Liang, M

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8a9e622-87f5-458a-8b7a-a5f21ddf5a2e · outbound

This paper cites and Fidler, S.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Fidler, S

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a99c6a4b-19d3-47a6-a899-5e2e1a09492b · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1da5503c-8335-4abe-80ee-70928fb255dc · outbound

This paper cites and others , title =.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and others , title =

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fd8dbd2-1cdb-424b-834f-fd4b5bcddcba · outbound

This paper cites SWA-SOP: Spatially-aware Window Attention for Semantic Occupancy Prediction in Autonomous Driving.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic SWA-SOP: Spatially-aware Window Attention for Semantic Occupancy Prediction in Autonomous Driving

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:22:34.791084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f479bb6f-cbaf-4f8d-a480-17d6096a94a9 · outbound

This paper cites and Wang, L.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Wang, L

Reference 46

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56256a25-2b0e-4f83-b314-9f5b251085b6 · outbound

This paper cites an unresolved cited work.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic Unresolved cited work

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f9c9d7b-d74b-4dd7-a0c9-5392d43603f5 · outbound

This paper cites and Liang, D.

Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic and Liang, D

Reference 48

Resolution: unresolved; no resolver link, observed 2026-06-28T19:14:49.785091Z

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Pith citing papers

No inbound Pith citation observations are available.