Paper Citation Record · LEDGER

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

As of 21 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 6 inbound Pith citation observations for arXiv:2501.01037.

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

pith.paper-citation-record.v1
2501.01037 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:41:52.633165Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:10:34.482336Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:02:27.168768Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy21
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b44c168b-cad5-405c-b1a4-279986ae7399 · outbound

This paper cites Bevfusion: Multi-task multi-sensor fusion with unified bird’s eye view representation,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Bevfusion: Multi-task multi-sensor fusion with unified bird’s eye view representation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.999162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2aec310d-cacc-4975-be74-b0138a30d0ca · outbound

This paper cites Deepinteraction: 3d object detection via modality interaction,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Deepinteraction: 3d object detection via modality interaction,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.985042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f782af66-bc9e-4fb2-9f00-8a01dd33982d · outbound

This paper cites Transfusion: Robust lidar-camera fusion for 3d object detection with transformers,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Transfusion: Robust lidar-camera fusion for 3d object detection with transformers,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.969785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5526a46e-c7e1-4662-9231-257238c27c23 · outbound

This paper cites Sparsefusion: Fusing multi-modal sparse representations for multi-sensor 3d object detection,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Sparsefusion: Fusing multi-modal sparse representations for multi-sensor 3d object detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.954376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation daa926cd-5dd0-4453-b649-c0ea5583b675 · outbound

This paper cites Cross Modal Transformer: Towards Fast and Robust 3D Object Detection.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:41:52.554692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b3ee8a8-57d5-40f5-91e9-4c92e0b4c38e · outbound

This paper cites Is-fusion: Instance-scene collaborative fusion for multimodal 3d object detection,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Is-fusion: Instance-scene collaborative fusion for multimodal 3d object detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.939125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6e9fae03-b460-454a-a833-30524a6474c7 · outbound

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

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Hdmapnet: An online hd map construction and evaluation framework,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.923481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0eb789f-045d-4e66-b596-577247377087 · outbound

This paper cites Mapdistill: Boosting efficient camera- based hd map construction via camera-lidar fusion model distillation,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Mapdistill: Boosting efficient camera- based hd map construction via camera-lidar fusion model distillation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.908471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9fdc95e3-5cec-4602-8a23-9ccfcf448d05 · outbound

This paper cites Vectormapnet: End-to-end vectorized hd map learning,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Vectormapnet: End-to-end vectorized hd map learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.893326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 233082ed-c2af-4c02-b973-b4e6747da706 · outbound

This paper cites Maptr: Structured modeling and learning for online vectorized hd map construction,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Maptr: Structured modeling and learning for online vectorized hd map construction,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.879075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5297c8ee-2a2e-4124-9839-f3a9ab24c0d6 · outbound

This paper cites RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:41:52.582210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d1bf74d-dbe0-4e5f-b6fe-87423e7f9229 · outbound

This paper cites Robo3d: Towards robust and reliable 3d perception against corruptions,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Robo3d: Towards robust and reliable 3d perception against corruptions,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.864750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3e889c17-380e-429a-b7d5-aed57aa2e7cc · outbound

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

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Understanding the robustness of 3d object detection with bird’s-eye-view representations in autonomous driving,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.849987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation daa2bbb7-b653-4c12-8372-68c9e7ce6712 · outbound

This paper cites 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.836062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69e19323-6a1a-486b-93a5-f73ff7f71828 · outbound

This paper cites Unimix: Towards domain adaptive and generalizable lidar semantic segmentation in adverse weather,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Unimix: Towards domain adaptive and generalizable lidar semantic segmentation in adverse weather,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.822010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dc63b6fb-3e32-4cf7-b532-bcd991314d85 · outbound

This paper cites Is your hd map constructor reliable under sensor corruptions?,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Is your hd map constructor reliable under sensor corruptions?,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.807234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5a38bff2-c21b-456f-975d-7a037b33746e · outbound

This paper cites Multicorrupt: A multi-modal robustness dataset and benchmark of lidar-camera fusion for 3d object detection,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Multicorrupt: A multi-modal robustness dataset and benchmark of lidar-camera fusion for 3d object detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.792278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e925892b-010b-4637-9c83-3704036e36f8 · outbound

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

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception nuscenes: A multimodal dataset for autonomous driving,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.776313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cbefc0a0-dde5-4459-893e-62ca0c70cb25 · outbound

This paper cites Fog simulation on real lidar point clouds for 3d object detection in adverse weather,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Fog simulation on real lidar point clouds for 3d object detection in adverse weather,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.759682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9f243756-2c7c-42f6-a520-b219bdcb29c4 · outbound

This paper cites Lidar snowfall simulation for robust 3d object detection,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Lidar snowfall simulation for robust 3d object detection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.744487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f4bb457-83bf-4a9b-93ff-378ba052310e · outbound

This paper cites Mbfusion: A new multi-modal bev feature fusion method for hd map construction,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Mbfusion: A new multi-modal bev feature fusion method for hd map construction,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.729317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 86e5e48d-2354-4e92-9125-474931d0aac0 · outbound

This paper cites Online vectorized hd map construction using geometry,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Online vectorized hd map construction using geometry,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.714375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 934b6f31-68bd-49bc-bb5f-55fb026d480f · outbound

This paper cites Himap: Hybrid representation learning for end-to-end vectorized hd map construction,.

MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception Himap: Hybrid representation learning for end-to-end vectorized hd map construction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:41:52.699097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 4ba1c3ba-3214-422d-9368-541b6a93de32 · inbound

MapFusion: A Novel BEV Feature Fusion Network for Multi-modal Map Construction cites this paper.

MapFusion: A Novel BEV Feature Fusion Network for Multi-modal Map Construction MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T05:10:34.482336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73496278-b98b-4a8f-9c02-c8af690521c9 · inbound

MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation cites this paper.

MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:02:27.171682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f558849e-060e-4223-83dc-76de7155752f · inbound

SafeMap: Robust HD Map Construction from Incomplete Observations cites this paper.

SafeMap: Robust HD Map Construction from Incomplete Observations MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T21:13:14.742632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef72986c-12ce-4fcc-9d4b-1045f0fca717 · inbound

What Really Matters for Robust Multi-Sensor HD Map Construction? cites this paper.

What Really Matters for Robust Multi-Sensor HD Map Construction? MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T20:57:10.199989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a5d53fd-2616-4d4f-957c-04b6fc62779e · inbound

Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities cites this paper.

Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Reference 125

Resolution: unresolved; no resolver link, observed 2026-08-04T20:52:06.712221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05bfb893-70e5-4d92-a28a-8132f3166d83 · inbound

Multi-Sensor Alignment for Weather Simulations cites this paper.

Multi-Sensor Alignment for Weather Simulations MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T01:59:52.832255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.