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Paper Citation Record · LEDGER

What Really Matters for Robust Multi-Sensor HD Map Construction?

As of 23 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.01484.

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

pith.paper-citation-record.v1
2507.01484 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:57:10.250611Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

38 of 38 outbound references displayed

  • verified exact2
  • verified fuzzy25
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18174ded-771e-4b93-a984-90b06a5f4f46 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Mapdistill: Boosting efficient camera-based hd map construction via camera-lidar fusion model distillation,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.579088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.147171Z digest=sha256:a1c45861958a0f5b178cf2b1e84512757c38d036a3b4c79b6771ce2ded41e679

Observation d866fb08-a132-4f57-8767-db33b21af6fe · outbound

This paper cites Stream query denoising for vectorized hd-map construction,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Stream query denoising for vectorized hd-map construction,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.570752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.150669Z digest=sha256:bb88a25b9f9091816b47df752d86a78a50ea797383a70ff46f72642166a60293

Observation 325baab9-f4bd-4666-8769-c2faf8ff004e · outbound

This paper cites Stvit+: improving self-supervised multi-camera depth estimation with spatial-temporal context and adversarial geometry regularization,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Stvit+: improving self-supervised multi-camera depth estimation with spatial-temporal context and adversarial geometry regularization,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.562737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.153683Z digest=sha256:4c6386ec22e248400f05c522bdac7061db232b07e4ab68dfaef0b741b2c3b244

Observation 5703ca53-8fac-458f-8c23-c4f36cafcd0b · outbound

This paper cites Diffmap: Enhancing map segmentation with map prior using diffusion model,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Diffmap: Enhancing map segmentation with map prior using diffusion model,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.554734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.156640Z digest=sha256:00ae20fb8139c8923cff7b854e1ed321655d346793b0879ddd3222bd541fc5c1

Observation 7867f199-2c26-4d6c-b724-af7653320dd0 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Maptr: Structured modeling and learning for online vectorized hd map construction,

Reference 5

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unresolved
no resolver link, observed 2026-08-06T20:57:10.159635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.159635Z digest=sha256:59f74aa3e17f397c625bc1eaa8ab78145a16eb8d41e00daa3f137d8993773fd2

Observation 8ab37a1f-184c-462a-892a-1acb975224d9 · outbound

This paper cites FastRSR: Efficient and Accurate Road Surface Reconstruction from Bird's Eye View.

What Really Matters for Robust Multi-Sensor HD Map Construction? FastRSR: Efficient and Accurate Road Surface Reconstruction from Bird's Eye View

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:57:10.334413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.162295Z digest=sha256:4ac8a9b92c9a874e13083a49e97893c63b5ef59e4fd1d324ea1c4191433d1944

Observation 5071798b-b597-45bf-9cde-6f3a96877bfc · outbound

This paper cites Mapfusion: A novel bev feature fusion network for multi-modal map construction,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Mapfusion: A novel bev feature fusion network for multi-modal map construction,

Reference 7

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raw_fallback, observed 2026-08-06T20:57:10.540558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.165345Z digest=sha256:849460909f4a98c07d2f285292d35778f7a291fcd62acf2c1047965986fae4e0

Observation 203583b6-1520-43c7-99e7-b82f299045cc · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Bevfusion: A simple and robust lidar-camera fusion framework,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.532584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.167790Z digest=sha256:d0a52d94b86e2a0e99cda57677173690aee284f07c90f0db01abb5a60fb554c3

Observation e2568ba9-3a9a-4329-9a04-3c4e011878c2 · outbound

This paper cites Deepfusionmot: A 3d multi- object tracking framework based on camera-lidar fusion with deep association,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Deepfusionmot: A 3d multi- object tracking framework based on camera-lidar fusion with deep association,

Reference 9

Resolution
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raw_fallback, observed 2026-08-06T20:57:10.523960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.170378Z digest=sha256:39d713650980bc0c93d367e3e12c395d8bc39d902432d1cb7eb0b1f3302c45cf

Observation e6860bb9-285b-42f5-85ee-a43ad1a5e119 · outbound

This paper cites Safemap: Robust hd map construction from incomplete observations,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Safemap: Robust hd map construction from incomplete observations,

Reference 10

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raw_fallback, observed 2026-08-06T20:57:10.516107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.172806Z digest=sha256:c39757fb2e417359cf469fdce7b6dce0869b810a7b9e976b29239eaebee36100

Observation dc3f73c0-27fe-4fab-aee6-f9a144e30adf · outbound

This paper cites Team Samsung-RAL: Technical Report for 2024 RoboDrive Challenge-Robust Map Segmentation Track.

What Really Matters for Robust Multi-Sensor HD Map Construction? Team Samsung-RAL: Technical Report for 2024 RoboDrive Challenge-Robust Map Segmentation Track

Reference 11

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verified exact
local_arxiv, observed 2026-08-06T20:57:10.319823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.175462Z digest=sha256:ec1cabd413de76b3e38119362aadc8aad3aec4e0b29cf3ea909d40b20965549b

Observation 817f9821-5b27-4e62-88ce-1993351d494e · outbound

This paper cites The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition.

What Really Matters for Robust Multi-Sensor HD Map Construction? The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition

Reference 12

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no resolver link, observed 2026-08-06T20:57:10.178891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.178891Z digest=sha256:cff2d6e34f2276989b34b3eb9f5e1761240ce8d08680e010a1df1cc5441f3352

Observation c31ccb24-28ef-4e93-8ac1-c2097c6d14c9 · outbound

This paper cites Using temporal information and mixing-based data augmentations for robust hd map construction.

What Really Matters for Robust Multi-Sensor HD Map Construction? Using temporal information and mixing-based data augmentations for robust hd map construction

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.508293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.181527Z digest=sha256:4db3a2064a913e17f0ebe39ff24056267e2ab993cfed5ed57973aa0f80417dc3

Observation d2a86827-0b81-451f-9a51-667a01cd1760 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions

Reference 14

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no resolver link, observed 2026-08-06T20:57:10.184089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.184089Z digest=sha256:d50203811392c99d878c6be848674b344dc4095dc013bed25bcc8018c9e30026

Observation 4e5ef0ee-b7eb-4678-a807-cca9cdd397f5 · outbound

This paper cites Robustness-aware 3d object detection in autonomous driving: A review and outlook,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Robustness-aware 3d object detection in autonomous driving: A review and outlook,

Reference 15

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no resolver link, observed 2026-08-06T20:57:10.186981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.186981Z digest=sha256:b856d08e4b0a071fb6a92d2b553a8f72fe3c42d533b2056217dffd4eae99c058

Observation 26a69806-ded2-45fb-a8ef-5021fe1400e6 · outbound

This paper cites The four most basic elements in machine cognition,.

What Really Matters for Robust Multi-Sensor HD Map Construction? The four most basic elements in machine cognition,

Reference 16

Resolution
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raw_fallback, observed 2026-08-06T20:57:10.494122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.189355Z digest=sha256:9847c5547e467d1a83b9ef7f0e0d24fa3a3f18a58e504c2a769fa0c67a333bab

Observation 372c455d-0011-4180-a832-e1d3d9ea6a74 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Robo3d: Towards robust and reliable 3d perception against corruptions,

Reference 17

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raw_fallback, observed 2026-08-06T20:57:10.486401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.191644Z digest=sha256:df550b3714fe08e9369d4a101b89b8148f16de191094034ee55570056a0ec4d9

Observation d197bb6e-60dc-4648-93f6-cd2dcfa86f24 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Understanding the robustness of 3d object detection with bird’s-eye-view representations in autonomous driving,

Reference 18

Resolution
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raw_fallback, observed 2026-08-06T20:57:10.478660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.194145Z digest=sha256:f22989ee6d8eef0070448c20be94d1e1428a1935630d5885195d743d70f72047

Observation 0cd3bdb7-cab7-4220-adc7-a5dcd3d94621 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Is your hd map constructor reliable under sensor corruptions?

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.470834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.197173Z digest=sha256:f14d907fac0d3dbbd33fcdd844db7335054201c42bdc9cc7ab6d0cdc9b4c5b67

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

This paper cites MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception.

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

Reference 20

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.199989Z digest=sha256:d2534c6abf42b770f43dbcc293f9ca9d3c9073f8de135b85be4bc6e2e3ea7dde

Observation 8f488452-b1c6-45af-91f3-1751c1b88ad0 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? nuscenes: A multimodal dataset for autonomous driving,

Reference 21

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raw_fallback, observed 2026-08-06T20:57:10.462789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.203008Z digest=sha256:f22d5a7e42d459a9c457a65b9a44421d2d1b6d15b31b7d0a6e17c7bd5c2030a1

Observation a8ac3345-c736-43bf-acd9-51bb7348b763 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Hdmapnet: An online hd map construction and evaluation framework,

Reference 22

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raw_fallback, observed 2026-08-06T20:57:10.454557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.205631Z digest=sha256:4e1f79f21fd559ab629d4600b32e1cf83551e93426f2624144b8bd42e2236883

Observation 195904dc-6206-4b8b-925d-11295c86d062 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Vectormapnet: End-to-end vectorized hd map learning,

Reference 23

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raw_fallback, observed 2026-08-06T20:57:10.446847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.208257Z digest=sha256:deed07e4fe7493cfd75dcaf64344e73b48106f692f659433322de8a078694b57

Observation 6a97b521-eb6c-42de-b186-54b3e026d882 · outbound

This paper cites Pivotnet: Vectorized pivot learning for end-to-end hd map construction,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Pivotnet: Vectorized pivot learning for end-to-end hd map construction,

Reference 24

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raw_fallback, observed 2026-08-06T20:57:10.438909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.210913Z digest=sha256:995b825567ed56b56807ca6b16ef7d64c4b96f929aa4639f23d13a3ea6bccec5

Observation f11eb449-2141-4ec8-be04-4996b0c72ac5 · outbound

This paper cites End-to-end vectorized hd- map construction with piecewise bezier curve,.

What Really Matters for Robust Multi-Sensor HD Map Construction? End-to-end vectorized hd- map construction with piecewise bezier curve,

Reference 25

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raw_fallback, observed 2026-08-06T20:57:10.430901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.213430Z digest=sha256:6802efa89e200da241a3c00e37caa1651255c7c0f194c234a45f8b37dfcf07df

Observation 44309925-9662-4aa0-8716-74caaac7b253 · outbound

This paper cites Maptrv2: An end-to-end framework for online vectorized hd map construction,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Maptrv2: An end-to-end framework for online vectorized hd map construction,

Reference 27

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no resolver link, observed 2026-08-06T20:57:10.218775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.218775Z digest=sha256:c169d672b560244c8cf313ecc476082f53f761424c0b5c83f87007a929c66c21

Observation a8464de3-5a79-4f18-9d54-35b8ba109265 · outbound

This paper cites Streammapnet: Streaming mapping network for vectorized online hd map construction,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Streammapnet: Streaming mapping network for vectorized online hd map construction,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.410157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.221355Z digest=sha256:30467243ec71ef0914064c39eab8553236bb08d6a08d1e6e1e68c06ef81ab536

Observation 16d5f542-52b9-46aa-8486-65e373f630c7 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Himap: Hybrid representation learning for end-to-end vectorized hd map construction,

Reference 29

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no resolver link, observed 2026-08-06T20:57:10.223809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.223809Z digest=sha256:8ba7df166e3df33b440bb429d76a9b90945fb14270d5922d4d7e30330bf5b1c7

Observation a119aeab-237f-4e5e-8692-1b3f2d4cf3cb · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Mbfusion: A new multi-modal bev feature fusion method for hd map construction,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.397064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.226199Z digest=sha256:e893adac7f122a2b62ca962279ca8ead333dbad8e0192800589f2f33e46c20ec

Observation 144bb1d6-d2c1-460d-8e4d-3a2418f82361 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Online vectorized hd map construction using geometry,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.422994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.228715Z digest=sha256:7f4226fcbae82e3778835226c27cb9c6f0833167f0200e4bead4e1e54994d3cc

Observation 5fc51011-b2ee-4866-95ac-5f5eb5682cb9 · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Mgmap: Mask-guided learning for online vectorized hd map construction,

Reference 32

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no resolver link, observed 2026-08-06T20:57:10.231115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.231115Z digest=sha256:049dab619ae30f0efe340adfa090713e75f73aeb2688b1f67be608628671dab5

Observation bc1280e0-afa2-4f7c-a3ec-ca37ab98ab13 · outbound

This paper cites A survey on image data augmentation for deep learning,.

What Really Matters for Robust Multi-Sensor HD Map Construction? A survey on image data augmentation for deep learning,

Reference 33

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no resolver link, observed 2026-08-06T20:57:10.233619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.233619Z digest=sha256:7df27efa24c16caa7902945fdb783c6b9eba8b5db369c42dae70ab0f4208b5b8

Observation 17c2070e-a0e0-4d39-988d-d17c5e88e8a5 · outbound

This paper cites Part-aware data augmentation for 3d object detection in point cloud,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Part-aware data augmentation for 3d object detection in point cloud,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.377552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-06T20:57:10.236152Z digest=sha256:1ab794a959b952cd09eef29858e1f39be542407afd644c582e714a54e8068668

Observation be8c2d62-948a-458f-b44a-bb071bf98976 · outbound

This paper cites Deep residual learning for image recognition,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Deep residual learning for image recognition,

Reference 35

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no resolver link, observed 2026-08-06T20:57:10.238768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fc5538a8-621c-4e01-b062-a73fc912a104 · outbound

This paper cites Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer.

What Really Matters for Robust Multi-Sensor HD Map Construction? Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer

Reference 36

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Observation ad762e7c-a576-4862-89e3-1df0527b981d · outbound

This paper cites SECOND: sparsely embedded convolutional detection,.

What Really Matters for Robust Multi-Sensor HD Map Construction? SECOND: sparsely embedded convolutional detection,

Reference 37

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation da424b7e-0dbb-4e80-9ee9-150a05df295d · outbound

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

What Really Matters for Robust Multi-Sensor HD Map Construction? Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation,

Reference 38

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verified fuzzy
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Source-reported events for the cited work

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Observation 2efbb81b-41d4-44bf-bce4-26770f18d60e · outbound

This paper cites Electronic device and method with birds-eye-view image processing,.

What Really Matters for Robust Multi-Sensor HD Map Construction? Electronic device and method with birds-eye-view image processing,

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-06T20:57:10.343977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Pith citing papers

No inbound Pith citation observations are available.