Paper Citation Record · LEDGER

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning

As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2608.01201.

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

pith.paper-citation-record.v1
2608.01201 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:31:56.486263Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

36 of 36 outbound references displayed

verified exact1
verified fuzzy27
unresolved8
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c10dd003-9784-4e70-bd84-e6c19a1cca31 · outbound

This paper cites Critical reasons for crashes investigated in the national motor vehicle crash causation survey,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Critical reasons for crashes investigated in the national motor vehicle crash causation survey,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:02.841449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 777afb0a-6365-4bf8-b466-013978483b25 · outbound

This paper cites Optimizing autonomous transfer hub networks: Quantifying the potential impact of self-driving trucks,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Optimizing autonomous transfer hub networks: Quantifying the potential impact of self-driving trucks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:02.599199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 220eecc0-d2ae-44e1-8848-16d305e05f96 · outbound

This paper cites Challenges of autonomous driving trucks and the impact on logistics,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Challenges of autonomous driving trucks and the impact on logistics,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:02.343669Z

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Observation f36986d0-bbcc-4023-90d8-82deb0f1c83e · outbound

This paper cites Autonomous high speed road vehicle guidance by computer vision,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Autonomous high speed road vehicle guidance by computer vision,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:02.109047Z

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Observation 43b4a7ad-eb6b-43e2-98f2-e57cab2a95c0 · outbound

This paper cites Autonomous driving in urban environments: Boss and the urban challenge,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Autonomous driving in urban environments: Boss and the urban challenge,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:01.947435Z

Source-reported events for the cited work

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Observation 6d4f38cf-5376-4d4e-9d01-d2a0b71ae8a5 · outbound

This paper cites A survey of autonomous driving: Common practices and emerging technologies,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning A survey of autonomous driving: Common practices and emerging technologies,

Reference 6

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Source-reported events for the cited work

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Observation 8c776bb5-abf4-4623-8bc4-496d003c63e2 · outbound

This paper cites ALVINN: an autonomous land vehicle in a neural network,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning ALVINN: an autonomous land vehicle in a neural network,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:01.673668Z

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Observation 48db5c05-33c6-499e-9826-cb29c5342712 · outbound

This paper cites Planning-oriented autonomous driving,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Planning-oriented autonomous driving,

Reference 8

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Source-reported events for the cited work

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Observation ee9f19a9-4ea3-41ca-899c-998d890da208 · outbound

This paper cites V AD: vectorized scene representation for efficient autonomous driving,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning V AD: vectorized scene representation for efficient autonomous driving,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:01.270835Z

Source-reported events for the cited work

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Observation da811eb4-13ae-462c-99ca-a99ca5466c7a · outbound

This paper cites SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation

Reference 10

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Source-reported events for the cited work

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Observation 0e22f280-fd70-4909-a7a5-c1d30b1d40e4 · outbound

This paper cites The NVIDIA PilotNet Experiments.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning The NVIDIA PilotNet Experiments

Reference 11

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Source-reported events for the cited work

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Observation 3c402901-214a-4070-9f10-96151238df9a · outbound

This paper cites Learning Accurate, Comfortable and Human-like Driving.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Learning Accurate, Comfortable and Human-like Driving

Reference 12

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Source-reported events for the cited work

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Observation acd79b95-49fc-41a4-a3d8-3919f2a1b77c · outbound

This paper cites End-to-end learning of driving models from large-scale video datasets,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning End-to-end learning of driving models from large-scale video datasets,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:01.002559Z

Source-reported events for the cited work

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Observation 91d0aa65-8bd4-4126-89d5-2138ccb426e2 · outbound

This paper cites End to End Learning for Self-Driving Cars.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning End to End Learning for Self-Driving Cars

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T00:31:53.503457Z

Source-reported events for the cited work

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Observation 20a83b34-8160-4165-a1d8-fad5d633a2d4 · outbound

This paper cites Multi-modal fusion transformer for end-to-end autonomous driving,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Multi-modal fusion transformer for end-to-end autonomous driving,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:00.699390Z

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Observation b86c0481-e1e0-4d37-8102-955fe74a881e · outbound

This paper cites Deeply- supervised nets,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Deeply- supervised nets,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:00.465554Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 73f0afe5-5bd0-4944-bc04-566d55916067 · outbound

This paper cites iMacHSR: intermediate multi-access heterogeneous supervision and regularization scheme toward architecture-agnostic training,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning iMacHSR: intermediate multi-access heterogeneous supervision and regularization scheme toward architecture-agnostic training,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:00.291496Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 41bd6e24-0319-4d14-b21f-8fe8827ad2aa · outbound

This paper cites VLP: vision language planning for autonomous driving,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning VLP: vision language planning for autonomous driving,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:32:00.071786Z

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Observation 7c46012b-443a-4b8c-8239-23541dfdd6a6 · outbound

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

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning nuscenes: A multimodal dataset for autonomous driving,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:59.850278Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7bc30a6-d561-4faf-bd0b-449480d8675e · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:59.659014Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7d9a85d7-48f1-4489-b2bd-a4011f5620a6 · outbound

This paper cites Genad: Generative end-to-end autonomous driving,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Genad: Generative end-to-end autonomous driving,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:59.490812Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8d29204a-5fca-4b69-bb91-59cc8cd3d5df · outbound

This paper cites Going deeper with convolutions,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Going deeper with convolutions,

Reference 22

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Observation 57db37ae-e211-4e98-b33e-758fa7738a13 · outbound

This paper cites DeepMIM: deep supervision for masked image modeling,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning DeepMIM: deep supervision for masked image modeling,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:59.041163Z

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Observation 48f209fb-2ae3-4690-970d-ff3aff739233 · outbound

This paper cites Interpretable decision-making for end- to-end autonomous driving,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Interpretable decision-making for end- to-end autonomous driving,

Reference 24

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Observation d5a6d5fa-b399-4f29-8ed8-c237ef1e3c26 · outbound

This paper cites VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

Reference 25

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This paper cites An overview of statistical learning theory,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning An overview of statistical learning theory,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:58.866791Z

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Observation c0026e0f-271b-42cf-8b47-bfc82b6b933b · outbound

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PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T00:31:55.513265Z

Source-reported events for the cited work

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Observation 41ef39d1-96ce-480f-b0e8-b8d2782183c5 · outbound

This paper cites an unresolved cited work.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Unresolved cited work

Reference 28

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Source-reported events for the cited work

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Observation 4d709bb8-accb-4b76-b9aa-156c4654b6fb · outbound

This paper cites Amortized inference in proba- bilistic reasoning,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Amortized inference in proba- bilistic reasoning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:58.551816Z

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Observation eede7a3d-ff30-409f-b545-5ddcc3eef3b3 · outbound

This paper cites On information and sufficiency,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning On information and sufficiency,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:58.333598Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7683c554-a4e6-4284-b65b-95722ffb16f0 · outbound

This paper cites Auto-encoding variational bayes,.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Auto-encoding variational bayes,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:58.130441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a8b0203-3e58-437f-94ac-0796062a1ad5 · outbound

This paper cites 6a illustrates the TE encoder used as the default in VLP.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning 6a illustrates the TE encoder used as the default in VLP

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:57.898873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8ebe0a65-ba89-4829-ae20-dc9d3619d5cc · outbound

This paper cites 6b and 6c show our MLP-based encoders for ALP and SLP, respectively.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning 6b and 6c show our MLP-based encoders for ALP and SLP, respectively

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:57.574580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8849c516-18dc-4802-bde0-593f80e212fe · outbound

This paper cites To construct a distributional target, we generate a corresponding posterior queryfrom GT annotations while condition- ing on theprior query.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning To construct a distributional target, we generate a corresponding posterior queryfrom GT annotations while condition- ing on theprior query

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:57.440494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 98b90ee0-d571-4583-9845-d95efb2e22f3 · outbound

This paper cites Each head is a stack of linear layers with dimensions[D, 2D, 2D, D].

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Each head is a stack of linear layers with dimensions[D, 2D, 2D, D]

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:57.260044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d3ce7c49-198a-4995-a459-083d62ea319b · outbound

This paper cites Hidden dimension is set toD= 256.

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning Hidden dimension is set toD= 256

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:31:57.036062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.