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Paper Citation Record · LEDGER

On Learning Closed-Loop Probabilistic Multi-Agent Simulator

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2508.00384.

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

pith.paper-citation-record.v1
2508.00384 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:15:54.481693Z

measured 29 of 29 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

29 of 29 outbound references displayed

  • verified exact0
  • verified fuzzy26
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1b0f737-a25a-4ad0-8be3-06c55244f6db · outbound

This paper cites Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.701140Z

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.

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Observation 2ca15440-ba8d-4182-92e4-d14b152444f0 · outbound

This paper cites Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.693955Z

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.

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Observation 232c8521-c3a9-45b3-8023-24de2cdcec76 · outbound

This paper cites Argoverse: 3d tracking and forecasting with rich maps,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Argoverse: 3d tracking and forecasting with rich maps,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.686955Z

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.

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Observation 655808d0-e983-42f3-afc7-6ca6026c26c7 · outbound

This paper cites Simnet: Learning reactive self-driving simulations from real-world observations,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Simnet: Learning reactive self-driving simulations from real-world observations,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.679963Z

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.

source=pdf_text observed=2026-08-06T10:15:54.417310Z digest=sha256:7b1ab8226df569a7955c16d02eae4aea08b3c80cde3baa6131165f78f76cecac

Observation a1a61965-1882-4695-a636-beadd4ff59e5 · outbound

This paper cites The waymo open sim agents challenge,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator The waymo open sim agents challenge,

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T10:15:54.419952Z digest=sha256:fd8f37a7522c28cf5431f2ddc203d7c5a085f55722b75bdca78757effaeaae03

Observation 0e6e74c2-0c4f-4810-9b42-bf4fc719e7f3 · outbound

This paper cites Generalizability analysis of graph-based trajectory predictor with vectorized representation,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Generalizability analysis of graph-based trajectory predictor with vectorized representation,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.665836Z

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.

source=pdf_text observed=2026-08-06T10:15:54.422436Z digest=sha256:02d9f8c5440fb24c71b7efae3e06b29e7af284d2c49b24f97b208fe853e81927

Observation d72bd6c1-3330-4e81-bebb-6b80bd71f6d8 · outbound

This paper cites Trafficsim: Learning to simulate realistic multi-agent behaviors,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Trafficsim: Learning to simulate realistic multi-agent behaviors,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.658688Z

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.

source=pdf_text observed=2026-08-06T10:15:54.425832Z digest=sha256:94e11a8476ff93dc3504c10ad444366b86ee427dd122ae0e434f6bbaabbee58a

Observation c7579b48-cd67-4899-80aa-127902336ff4 · outbound

This paper cites Quantifying uncertainty in motion prediction with variational bayesian mixture,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Quantifying uncertainty in motion prediction with variational bayesian mixture,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.651124Z

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.

source=pdf_text observed=2026-08-06T10:15:54.428168Z digest=sha256:3a228819d41203c28d812d4e8fbf9acb1f0a110c083d78c6c713988a960b61e4

Observation cd2ea420-b69b-4282-b5b9-f2901b41f59c · outbound

This paper cites Editing driver character: Socially-controllable behavior generation for interactive traffic simulation,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Editing driver character: Socially-controllable behavior generation for interactive traffic simulation,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.644136Z

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.

source=pdf_text observed=2026-08-06T10:15:54.430469Z digest=sha256:e84c377d52af5a4a26a9aed9f243a4850d74090e923818adc3e274e4f4a220f8

Observation 676f80c0-95be-4efe-a244-264a98adf899 · outbound

This paper cites Vectornet: Encoding hd maps and agent dynamics from vectorized representation,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Vectornet: Encoding hd maps and agent dynamics from vectorized representation,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.637183Z

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.

source=pdf_text observed=2026-08-06T10:15:54.432741Z digest=sha256:7abaa89db3dfea216b6174783cc477825d737d15e3bb2b6ddbdae7d6e1126a09

Observation 00188dbd-c7d3-414b-80db-e001eb2cd903 · outbound

This paper cites Motion transformer with global intention localization and local movement refinement,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Motion transformer with global intention localization and local movement refinement,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.629542Z

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.

source=pdf_text observed=2026-08-06T10:15:54.435075Z digest=sha256:d0ccb627d52eeef1d8532141af7ed24c05ed5ea4af1b979bf24f43a6ca8bad6c

Observation 11acc9f8-e27d-4ea9-8f86-054e5483f1ea · outbound

This paper cites TrafficBots V1.5: Traffic Simulation via Conditional VAEs and Transformers with Relative Pose Encoding.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator TrafficBots V1.5: Traffic Simulation via Conditional VAEs and Transformers with Relative Pose Encoding

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T10:15:54.437345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:15:54.437345Z digest=sha256:c8505c1213b7751c185a9ce532fa9ed0fa2e40e97729e3d5e7d1b7aff622515c

Observation 4e0ace60-5c28-40f3-af89-dd982914a9a4 · outbound

This paper cites Behaviorgpt: Smart agent simulation for autonomous driving with next-patch prediction,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Behaviorgpt: Smart agent simulation for autonomous driving with next-patch prediction,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.621642Z

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.

source=pdf_text observed=2026-08-06T10:15:54.440255Z digest=sha256:d4aa1e725f6b2ed85579d53e0af92b6d9dbcd9c8702c6e1d101350f3d8cd3ea6

Observation 2b56f7cf-3fe8-420c-b48d-169b5c60ed86 · outbound

This paper cites Smart: Scalable multi-agent real-time motion generation via next-token prediction,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Smart: Scalable multi-agent real-time motion generation via next-token prediction,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.613769Z

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.

source=pdf_text observed=2026-08-06T10:15:54.442881Z digest=sha256:90c9cc0061aab1db1797f22e7eeba8dd61739c1bceb39c6c75875cd405b93723

Observation bc1ea7ed-1f3d-4f07-b17a-0942ce178844 · outbound

This paper cites Drivegpt4: Interpretable end-to-end autonomous driving via large language model,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Drivegpt4: Interpretable end-to-end autonomous driving via large language model,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.606030Z

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.

source=pdf_text observed=2026-08-06T10:15:54.445189Z digest=sha256:bf8ca3fa80cc207947fdf2716065fe1db2b94f106a793e65e30a7774c141bf89

Observation 4e9fb571-1f07-4651-ae93-45c46bce74e8 · outbound

This paper cites Deep learning to represent subgrid processes in climate models,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Deep learning to represent subgrid processes in climate models,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.598866Z

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.

source=pdf_text observed=2026-08-06T10:15:54.448988Z digest=sha256:65b7d7f4aadf7f4064a4cd5ce6730a45b98dc3e0d55242af743c22b0ac26816e

Observation 35ccb028-df5e-488d-93c8-89b125ee7dce · outbound

This paper cites Learning particle physics by example: location-aware generative adversarial networks for physics synthesis,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Learning particle physics by example: location-aware generative adversarial networks for physics synthesis,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.590474Z

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.

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Observation a0814c66-7c6d-4a05-9392-e787243a83b5 · outbound

This paper cites Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention query- ing,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention query- ing,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.582422Z

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.

source=pdf_text observed=2026-08-06T10:15:54.454285Z digest=sha256:21e8c6df5ea0e24e15bda0b3b85e69326f99dec42c7fe2ee9281ca8668ddabaf

Observation 9fad1a75-11d7-42c2-bcf7-62018604686d · outbound

This paper cites Towards generalizable and interpretable motion prediction: A deep variational Bayes approach,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Towards generalizable and interpretable motion prediction: A deep variational Bayes approach,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.575182Z

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.

source=pdf_text observed=2026-08-06T10:15:54.457086Z digest=sha256:74ffb77ef0897c7ca9b5ffb55d6e77b150a3babef959294813bac41d8c0efe0a

Observation ac0ce208-5cef-4a17-be5d-ce81ca9da0c4 · outbound

This paper cites Query-centric trajectory prediction,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Query-centric trajectory prediction,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.567767Z

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.

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Observation 0bd41df1-a47b-4102-b484-99a620ac438d · outbound

This paper cites Fourier fea- tures let networks learn high frequency functions in low dimensional domains,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Fourier fea- tures let networks learn high frequency functions in low dimensional domains,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.560289Z

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.

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Observation c4c570e2-3cdd-46b4-b1f6-b49959a6cb3f · outbound

This paper cites Attention is all you need,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Attention is all you need,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T10:15:54.464249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:15:54.464249Z digest=sha256:d75337d627b2c4184ae5355229b661d9a2531873297b02f4586c7473e4be8564

Observation e5439bef-23c1-49fb-a474-9d49f5c66c67 · outbound

This paper cites Scalable diffusion models with transform- ers,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Scalable diffusion models with transform- ers,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.548690Z

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.

source=pdf_text observed=2026-08-06T10:15:54.467416Z digest=sha256:c5f148a9d5d08c07a22627a91634f5b152cefca54c57fd6fd45c4b223feed868

Observation 4c416098-e5f9-4f3a-85b4-9b24224864b0 · outbound

This paper cites Multiverse transformer: 1st place solution for waymo open sim agents challenge 2023,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Multiverse transformer: 1st place solution for waymo open sim agents challenge 2023,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.541369Z

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.

source=pdf_text observed=2026-08-06T10:15:54.469763Z digest=sha256:d3f14cb839d505ce75318db09fe2fd885ec44b6800a637f6af4db8917d1783cb

Observation 08791bbc-a6aa-48a0-829f-0175258a8ade · outbound

This paper cites Solving motion planning tasks with a scalable generative model,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Solving motion planning tasks with a scalable generative model,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.534182Z

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.

source=pdf_text observed=2026-08-06T10:15:54.472081Z digest=sha256:6125f38cbc0c86cb1af273cddde563ab8061cee8beb675727e13a6819fb226dc

Observation 44ac1476-b0ab-428f-a59f-8c0506789d36 · outbound

This paper cites Kigras: Kinematic-driven generative model for realistic agent simulation,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Kigras: Kinematic-driven generative model for realistic agent simulation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.527494Z

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.

source=pdf_text observed=2026-08-06T10:15:54.474413Z digest=sha256:d0d6e9d40a4b561aa2eb3f56c3277b73631f829179e3daf75bc9b360c06dc19d

Observation c7b50e7d-3b73-420a-87e0-7002fffc2d31 · outbound

This paper cites Decoupled weight decay regularization,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Decoupled weight decay regularization,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T10:15:54.476851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:15:54.476851Z digest=sha256:68a4764b0f388db4c588b03d2d75e6c21e99593b7dc6a833cbdbef6da027c32e

Observation 0623fc4d-6c41-4c70-9730-091836f51618 · outbound

This paper cites Sgdr: Stochastic gradient descent with warm restarts,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Sgdr: Stochastic gradient descent with warm restarts,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.516907Z

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.

source=pdf_text observed=2026-08-06T10:15:54.479296Z digest=sha256:fd72122294c1f55f9d4f686f1a5bc747aecf1502ca3d5e5720ecf0b54bd13289

Observation 7b71a61f-a9ae-4d36-b0ca-484204a173d3 · outbound

This paper cites Kigras: Kinematic-driven generative model for realistic agent simulation,.

On Learning Closed-Loop Probabilistic Multi-Agent Simulator Kigras: Kinematic-driven generative model for realistic agent simulation,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:15:54.509352Z

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.

source=pdf_text observed=2026-08-06T10:15:54.481693Z digest=sha256:5e4232eae6e7d48a7de7910869be52f1f8d7fe1e63790f9bd15c6120111eedf8

Pith citing papers

No inbound Pith citation observations are available.