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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-09T06:31:02.800959+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

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.147171Z digest=sha256:892eb19c99af4c02475b4b64dfb5f5014bd323b6391e5b5d4e030b42f38723c9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.150669Z digest=sha256:613065043513f1ec832fe7695a7ba659b3801cd09bb33cd4fc32d01030dcbec6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.153683Z digest=sha256:00699c7f701ca75b4742d62d16053cf082ae02c0a3d5ce3a083026de3ab0edf5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.156640Z digest=sha256:81d82a8791d074281e521c159a91389ddf22491cba6a78210363dad998cc7070

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:f5f62c839342f1ffe4cf249fa180a050482515732207797a68cfb8c59c70498d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.162295Z digest=sha256:b13d862ca8d3f0171ebe13b3ebf3dc93e64d4cf55c52a5aeee9c0ea0f05d126c

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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verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.165345Z digest=sha256:dddf67fa05c038acdb5efadfd9062cdac0afe57a7133307e17fd5b8a87780af7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.167790Z digest=sha256:40d50dd0c2b7e393528765882c004169aea343eafb10634f263aee9e544b4637

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

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verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.170378Z digest=sha256:19848b38102e0067027a207ed257797fd603b42089f3a21ba2f6669a948401a5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.172806Z digest=sha256:72dd885ffa87dac8ca2d3df66050dd651f3b13f9a20b657ac22d4acc6fa4cbc0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.175462Z digest=sha256:73d1777bf81aca9ddddfb51cccea2a7fad9010133d2abf1fe1843f1313cc66db

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:e5d6432616d0b1e2a93bfef46e7cae5087bd2c330c7d587d743361e6275f20d9

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.181527Z digest=sha256:75f61cb04fa1056ee92ac7d7a999efc447a51378ee52497d9f4a37dfa0eda9b9

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=sha256:8da1c88f12d21b02611b8bd2a6c918d9611e7b37918c50cd0c63fcd728acf250

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=sha256:412376ea67ecaf606dc72ab6a2bccb75501524e7766e10d8b4e6d3570db91ee7

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.189355Z digest=sha256:10b1de18d976f584e402ffb5539661b82bd980c3d5761f816189648f9e26019b

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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verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.191644Z digest=sha256:c1d8347c5386835fef46dbaec8b4e4833afcc4eb9b39e103f932cf4c93d492cb

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.194145Z digest=sha256:633d7d8bfc666a9abfb963c3fbf9d9a60ab60c7c5843a8abfe9ff9f43cfcd84b

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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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.197173Z digest=sha256:1d3d4e5de8a1a0d172c07c35913b0739b7b071b671230e8098de246e1d55c378

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:57:10.199989Z digest=sha256:881eebf736682fa3f420c4a30d589fe32f925b0f644a76cb406b0f25738d1e50

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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verified fuzzy
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.203008Z digest=sha256:20c237649cd5aad590ac0f3fda2f9184bb2d93813fbc6be6da1d6ab8d80b8f48

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.205631Z digest=sha256:309bdf06199a90e5cd9dbd6197067bf33382ecf33b28dcbc2a6f5788ff7de505

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.208257Z digest=sha256:293c6c9f900b25271596b488d7a53ad4a4d9737e65746aca4d1787481fb01192

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.210913Z digest=sha256:81bbf0cca6c7a59d30a4a6b60f55680835d01e5b2d19888f00f79977587e1c2c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.213430Z digest=sha256:34bd734a43d7d9ae508cd5315b5a398aa9cbf3b85f1835896c0a01534db3b191

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=sha256:5ec203b5bf55c744b33ab0cb6c4c1348afdb7b54766348aace25fa9783f93bab

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.221355Z digest=sha256:68263fee18e10bcaa387a1d2164c19f88b9631a6aa953c95732fa1a576b542eb

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=sha256:845e41ec81ee46e00f994f6d9890a7a1203c78576af74d56a3e7e71923e1d50d

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.226199Z digest=sha256:fa7ff327d305dcadf5a995b21804351184aaf4982b29ad7ea99b5f1cd05890e5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.228715Z digest=sha256:ea9b5861b6acb27902bc481d0d68e8c21a4541a8a9225e1583f331c3a9649cb8

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:d1aa0b7db92daf57fe790a0096d5c2bb20d5a8d9f2e169c2336b1940d819cd00

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=sha256:215ee11eade213881b11dabb823c5bd9261f0d1a2b4ead3784289c290d580245

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T20:57:10.236152Z digest=sha256:52912a91ba51f60915dfc42cf4e6309ace8ba0ba4343100a77e235a59a3ecbd6

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.

source=pdf_text observed=2026-08-06T20:57:10.238768Z digest=sha256:d39812400b6c7691bdd3eabe59b809149c9dd2eaf4ba4c25fb593bca87a2c9c3

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 2026-08-09T06:31:02.800959+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

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

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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 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

No inbound Pith citation observations are available.