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Paper Citation Record · LEDGER

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving

As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2608.11790.

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

pith.paper-citation-record.v1
2608.11790 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:31:11.537865Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

35 of 35 outbound references displayed

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  • verified fuzzy21
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5a974a0-13fd-48b4-b5d9-e7dac63a4c80 · outbound

This paper cites Early estimates of motor vehicle traffic fatalities and fatality rate by sub-categories in 2021,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Early estimates of motor vehicle traffic fatalities and fatality rate by sub-categories in 2021,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-16T00:31:12.267770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.331201Z digest=sha256:ade7ba14cd72beccb5d807e824c03c402d6623cfa6889de05c1e52faddef47d5

Observation 796a99f2-ba65-4842-91a6-3d16b34ccbfa · outbound

This paper cites Spoofing and anti- spoofing technologies of global navigation satellite system: A survey,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Spoofing and anti- spoofing technologies of global navigation satellite system: A survey,

Reference 2

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source=pdf_text observed=2026-08-16T00:31:11.337090Z digest=sha256:a11cfc11f9b73af3d612c462f3bcc7203642d3f3382dbb7df17393f7302dd756

Observation a314a8d0-ca87-4e0a-b184-b038ea92e0d7 · outbound

This paper cites GPS-IDS: An Anomaly-based GPS Spoofing Attack Detection Framework for Autonomous Vehicles.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving GPS-IDS: An Anomaly-based GPS Spoofing Attack Detection Framework for Autonomous Vehicles

Reference 3

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source=pdf_text observed=2026-08-16T00:31:11.344548Z digest=sha256:9e035fabe4fb6ffd5367ca7b0a8739682158191f3e147a08478afde19ab4891f

Observation 7c012352-7c3a-44db-a85d-3c605001cc0f · outbound

This paper cites A sensor fusion-based gnss spoofing attack detection framework for autonomous vehicles,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving A sensor fusion-based gnss spoofing attack detection framework for autonomous vehicles,

Reference 4

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source=pdf_text observed=2026-08-16T00:31:11.350190Z digest=sha256:7d2a348129d4150b1800b55c4f04866ecec0043c724b992063380ca6c6706979

Observation 9d1a353e-c571-4f6c-b36f-f9fab847820d · outbound

This paper cites Prediction-Based GNSS Spoofing Attack Detection for Autonomous Vehicles.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Prediction-Based GNSS Spoofing Attack Detection for Autonomous Vehicles

Reference 5

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local_arxiv, observed 2026-08-16T00:31:11.644383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.355769Z digest=sha256:af129c167844418c8abda59dc52fdad134c1648aa07d095c5a5bb9ed2be5ab89

Observation 2894cbd3-296e-44d8-8599-66bc2fd984da · outbound

This paper cites Carrier-phase and imu based gnss spoofing detection for ground vehicles,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Carrier-phase and imu based gnss spoofing detection for ground vehicles,

Reference 6

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raw_fallback, observed 2026-08-16T00:31:12.224471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.362292Z digest=sha256:59565e7127376f3d2a7e2d825b1abd0e1fd5849f3dbd523261df8e5a69c85ed1

Observation 6ab949d9-ea6a-440e-a4fe-5d68ab5e7e6a · outbound

This paper cites A gps spoofing detection and classification correlator-based technique using the lasso,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving A gps spoofing detection and classification correlator-based technique using the lasso,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.367774Z digest=sha256:0eada65f382a49f65a24c455eab22de6b0828df4f0c65a5acb2aef047d48160d

Observation 8b009208-5195-4436-bde1-72a3a7e16762 · outbound

This paper cites Gps spoofing detection via crowd-sourced information for connected vehi- cles,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Gps spoofing detection via crowd-sourced information for connected vehi- cles,

Reference 8

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.373648Z digest=sha256:ebc275584f594f92b920e71baca2661cfe517153c6206adcfe57548173801d7e

Observation 4ee921e2-6b39-4590-9302-6d9c6769890c · outbound

This paper cites Recent advances on jamming and spoofing detection in gnss,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Recent advances on jamming and spoofing detection in gnss,

Reference 9

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raw_fallback, observed 2026-08-16T00:31:12.156469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.378490Z digest=sha256:0d945d26486eafc052538e3172dab874e65f85595ae8338334bbd1831a907980

Observation 868bb117-25e4-4e78-a777-812cb5d3928a · outbound

This paper cites Detecting signal spoofing attack in uavs using machine learning models,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Detecting signal spoofing attack in uavs using machine learning models,

Reference 10

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raw_fallback, observed 2026-08-16T00:31:12.130657Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.384356Z digest=sha256:4119e906cdf39ba5006f0f938bd72945d332f5eeef8debb042ff62d924644da5

Observation 8b2f4dc4-97e2-412e-898a-5d9348d8591c · outbound

This paper cites Ma- chine learning-based gps spoofing detection and mitigation for uavs,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Ma- chine learning-based gps spoofing detection and mitigation for uavs,

Reference 11

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raw_fallback, observed 2026-08-16T00:31:12.109314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.389143Z digest=sha256:d4ab8e2b9894ea6e1c4ad220cdcd10063e2cfcbc74c51129a11fc1caa0fbb8d5

Observation 2051df76-c38c-40cd-a4cd-19e55c30a533 · outbound

This paper cites Tree-based supervised machine learning models for detecting gps spoofing attacks on uas,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Tree-based supervised machine learning models for detecting gps spoofing attacks on uas,

Reference 12

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raw_fallback, observed 2026-08-16T00:31:12.089222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.394189Z digest=sha256:a5b301e9569e3b67d5b8b9397bcb7e44102302e7089efa1910811955eaa25aed

Observation 267db420-3aff-4344-8e49-5ca12609c38b · outbound

This paper cites Anomaly detection against gps spoofing attacks on connected and autonomous vehicles using learning from demonstration,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Anomaly detection against gps spoofing attacks on connected and autonomous vehicles using learning from demonstration,

Reference 13

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source=pdf_text observed=2026-08-16T00:31:11.399696Z digest=sha256:ed34960945f87780205e735ec8075efe1a9fded80c5b984dce1df110686418ef

Observation 47f3ecd8-aa5d-443b-8d34-2623ef506f4a · outbound

This paper cites Infrastructure-enabled gps spoofing de- tection and correction,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Infrastructure-enabled gps spoofing de- tection and correction,

Reference 14

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raw_fallback, observed 2026-08-16T00:31:12.058084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.406204Z digest=sha256:058e8009816e489f1a8e4f54054be7b59b91f98096c62931c359896c2250fa94

Observation 5db7f6c9-450b-4852-83f2-dc0a5d68f10c · outbound

This paper cites Secure pose estimation for autonomous vehicles under cyber attacks,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Secure pose estimation for autonomous vehicles under cyber attacks,

Reference 15

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raw_fallback, observed 2026-08-16T00:31:12.036801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.412725Z digest=sha256:5bfb6ed6aef6b62340c9d2082111c7b2bf737ea6f4ed7d772d99e11970373c74

Observation ce0a8b70-bd02-4320-9d80-0f5b710c92ba · outbound

This paper cites Security of gps/ins based on-road location tracking systems,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Security of gps/ins based on-road location tracking systems,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.418255Z digest=sha256:9badeb088b394b83dea8be9128018996adff4b35f8432cfa3d61f1f010b17c6e

Observation d23d9ce2-d350-4d42-86a8-cd99d2552424 · outbound

This paper cites Drift with devil: Security of{Multi-Sensor}fusion based localization in{High-Level} autonomous driving under{GPS}spoofing,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Drift with devil: Security of{Multi-Sensor}fusion based localization in{High-Level} autonomous driving under{GPS}spoofing,

Reference 17

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source=pdf_text observed=2026-08-16T00:31:11.423690Z digest=sha256:a6779550fb8f0d12f586b85df9fb4410f2f55cb20453de0a02d3a356b3d76c92

Observation 4f217c7b-dcb4-47fd-b346-a709a1209a6a · outbound

This paper cites Effect of gnss spoofing on gnss-imu data fusion-based vehicle pose estimation,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Effect of gnss spoofing on gnss-imu data fusion-based vehicle pose estimation,

Reference 18

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raw_fallback, observed 2026-08-16T00:31:11.979088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.429710Z digest=sha256:50e61a9cb5770f5c065f5647b8bee532e5537383e267b2469ab79cf74b7e9eb0

Observation bef2408b-2e2d-48e7-8cc6-8b6f390e7aa6 · outbound

This paper cites A reinforcement learning approach for global navigation satellite system spoofing attack detection in autonomous vehicles,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving A reinforcement learning approach for global navigation satellite system spoofing attack detection in autonomous vehicles,

Reference 19

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raw_fallback, observed 2026-08-16T00:31:11.957330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.442382Z digest=sha256:390693e3d92b3e1281df0a6762356a093c31c35d13d6c0546d4804cf0fe74616

Observation 37ab9139-1e16-451e-a4ac-1ecc8747ec88 · outbound

This paper cites Securing au- tonomous vehicles against gps spoofing attacks: A deep learning ap- proach,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Securing au- tonomous vehicles against gps spoofing attacks: A deep learning ap- proach,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.447714Z digest=sha256:85b016b3d4ee242ca4f3d96483319bca643b8fd9cef66610e01800d4d4fd18a3

Observation c6aba9c7-6bb4-4ecf-8ba2-33eed1bce3b5 · outbound

This paper cites Lstm-based gnss spoofing detection using low-cost spectrum sensors,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Lstm-based gnss spoofing detection using low-cost spectrum sensors,

Reference 21

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.453290Z digest=sha256:e80c9c9cadb22e55edf2a14f52cca11a24e4901e00a3cf22be699efc9f80808c

Observation fd17a140-3b0a-47fb-906b-5b43ec8675c1 · outbound

This paper cites Deeppose: Detecting gps spoofing attack via deep recurrent neural network,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Deeppose: Detecting gps spoofing attack via deep recurrent neural network,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.463046Z digest=sha256:10158ac81dd2ee3c9a9df73a5d82fc95cb7ecd7a73d068aaebd16fb38727c9f1

Observation 027377a3-5b6a-4083-975a-bdcf2945d625 · outbound

This paper cites Ai-based gnss spoofing attack detection for autonomous vehicles using satellite characteristics data,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Ai-based gnss spoofing attack detection for autonomous vehicles using satellite characteristics data,

Reference 23

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raw_fallback, observed 2026-08-16T00:31:11.855290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.468468Z digest=sha256:78e8c9b341d2952003e95438aea95114a325f1e3579bed40eec1d6a44b8e0402

Observation 08fa2c56-d2ee-4ae9-8da5-2e102d911ea3 · outbound

This paper cites Lstm-based gnss spoofing detection for drone formation flights,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Lstm-based gnss spoofing detection for drone formation flights,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-16T00:31:11.835592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.474429Z digest=sha256:09a133ef61367e0090d3f8da6801ec980a3066f8ea9ea3247fd1ff503da0e65d

Observation 455d0dea-09cd-4112-b15a-fa7ec88d442f · outbound

This paper cites Robust anomaly detection for multivariate time series through stochastic recurrent neural network,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Robust anomaly detection for multivariate time series through stochastic recurrent neural network,

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.481205Z digest=sha256:baca102e943f4b0e7d4d9d278132f90eda9e80818b6b373dac29c798299ff63c

Observation ca7c5d4d-a9c7-49b5-82cd-961aede05f08 · outbound

This paper cites Usad: Unsupervised anomaly detection on multivariate time series,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Usad: Unsupervised anomaly detection on multivariate time series,

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.486933Z digest=sha256:ef93c589c3e4256c8e36f5545fe54f53f25b5bed8e27f4ad081bf57d54627845

Observation efe905ac-48e7-4d55-96cd-2f4379de71eb · outbound

This paper cites Learning graph structures with transformer for multivariate time-series anomaly detection in iot,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Learning graph structures with transformer for multivariate time-series anomaly detection in iot,

Reference 27

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raw_fallback, observed 2026-08-16T00:31:11.781565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.492965Z digest=sha256:6bc8d9e89d3feeac94029bbc4b25f48ede8dae505a3006342414515b4725d624

Observation 15f693ec-89f7-4e39-a482-09233c4712f6 · outbound

This paper cites Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.500802Z digest=sha256:dd1a2492cee233f1a7361930c5dfd694a435431ae813a64c4ba954ab22f302f9

Observation 523d7d3c-5122-487a-a4b0-d86f421ab09b · outbound

This paper cites TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.506367Z digest=sha256:991c9fe26969913226e52709460eea1d04243001bf2252b3e7ed84097c5dd890

Observation 9f75ee28-ccdf-46c7-b8c9-735c8446337f · outbound

This paper cites Temporal convolutional networks for anomaly detection in time series,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Temporal convolutional networks for anomaly detection in time series,

Reference 30

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raw_fallback, observed 2026-08-16T00:31:11.752741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.511961Z digest=sha256:1800dacad89334138ea4fdf83fb76f0d3a736ffa8f060d234acb6bdffbff0270

Observation b5da1b40-15c4-4705-baa1-17247f68f0d4 · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.516841Z digest=sha256:4f956b1ad5e456b4a9d33dded38c8b9f8c26e3f65cbe4b118d6aa4c7d6a50ed6

Observation abe528aa-1707-4dc4-9903-5e6266e7d517 · outbound

This paper cites Neural ordinary differential equations,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Neural ordinary differential equations,

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.522397Z digest=sha256:e40d811aa974d027c0125b8c679763abb59f50bc27e7458fec62dbc375977fb7

Observation 0a1af086-1b7d-4e09-ad02-8b234a73456b · outbound

This paper cites Latent ordinary differential equations for irregularly-sampled time series,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Latent ordinary differential equations for irregularly-sampled time series,

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.527862Z digest=sha256:cae68d8ab78307b2ba96e8e319eb1e9edc55311e3e5fe7eab84ab43a6576dd1d

Observation 68d4772b-21fe-44b7-8e41-fedfe7290fcc · outbound

This paper cites Liquid time- constant networks,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Liquid time- constant networks,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:31:11.694601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T00:31:11.533070Z digest=sha256:81704b002b54199875d04a783c0e3a7d4b88d4171e6c7b670f849f04e592b289

Observation 63779abc-47d9-4517-b61a-b3a83b29fef2 · outbound

This paper cites Closed-form continuous-time neural networks,.

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving Closed-form continuous-time neural networks,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T00:31:11.537865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:11.537865Z digest=sha256:4143b7b2a8e6bf6ad0b6d99daf4d2b472f6d708076a3d1ea7c0fc07056065931

Pith citing papers

No inbound Pith citation observations are available.