Pith. sign in

Paper Citation Record · LEDGER

On Learning Closed-Loop Probabilistic Multi-Agent Simulator

As of 17 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 2026-08-16T06:30:59.297886+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

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.409309Z digest=sha256:d3f2a47f40d569a96cefe12a8b25454062bae66c1097f3a14d20900f3c7218ab

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.412081Z digest=sha256:db4efe34de05d03363917d29443dbf57fd46b4b9d1234574b32441ce44ccfccb

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.414761Z digest=sha256:360dbfe35c80e486023edfcc03507da7b5d9d9790de5fa09efc5f4f319b789ef

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.417310Z digest=sha256:76317691277c8e097f8525dc8bfde19d63da56b3bcd600cdf85c6417a9ffb524

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
raw_fallback, observed 2026-08-06T10:15:54.672883Z

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=2026-08-06T10:15:54.419952Z digest=sha256:6a662be2b1a0b5b6a4a50366e8385e812909d6e420e6e6f4b6f31ddfef82656b

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.422436Z digest=sha256:1c06a2749865e34ddc6c135cfe62ae0ef6f83bd032228173bbb1e84dc043cede

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.425832Z digest=sha256:b08c242d63cbfc6d08f4491a38c00bf7db24dfa921fe8d8424c3ce6bace3321c

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.428168Z digest=sha256:749f5913233df10721e099646caf1da0b64d82272c6fc90b3dde22ff8076fb4b

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.430469Z digest=sha256:8912b4de0d07935d4377ba6732de667a887e97adb322170acb4336eae09875ff

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.432741Z digest=sha256:230a0f8ddb94d244c03916dc75664fc4123e5993d05d38b9d21f2776ee65edd3

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.435075Z digest=sha256:31ca2b7964da36a35bf6fb1c67022efba30b688f70432273970aac52875b2a37

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=sha256:897d37d94c5a8a0a1a94b828a83550740b3b7d0a080bd1412637c28f00ba9c1e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.440255Z digest=sha256:76cf73b1d18688af13f35aedf202b382d7a38fbaee99752f9c9403c11eb337cd

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.442881Z digest=sha256:25c2527049be35aaf6b68a9805630f2ef5b77f1b5b89c28b361ea8b280a72776

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.445189Z digest=sha256:53f20ac705730097a3873827b3de6ae5b2beda2602134feba003fc8759370c29

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.448988Z digest=sha256:e22d50be097ba208380329f34847e84f5f89193749fac087e613890d32ca2955

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.451961Z digest=sha256:e3d1cf3649ec4e58182c058f7be6dab2f652c2cfdaf9e22c04b3f1ccfe894eb7

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.454285Z digest=sha256:7b3cd2cb53330b783e986d5c82882cef4f1da3afde823a4d81b27cdc2b755c7e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.457086Z digest=sha256:75a265915ccadf1990c1e3c11bba291dc104503bc2d2272d1bbea743f2cb1c80

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.459460Z digest=sha256:d8fb386eb5a8edd900ec420e967a0058abbfb4e22d65b36d40fd54db1a8b00af

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.461830Z digest=sha256:7963e1d56542ea392095de6abd82b277875591aae0a808e3e23b1160d4d06f43

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=sha256:4baac0b8e7267b47cf30bfc0f612eacf51dcd51c0f87099cc8d9b4ddbdbf2969

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.467416Z digest=sha256:068cf592f0d0a40c86920fe956ccf18eec07b6f6c196a80c63801d13479b65ae

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.469763Z digest=sha256:3af48c4bce954286cf1688137986dda1c92c7a81c2357315279671b4d0c39fc1

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.472081Z digest=sha256:8f9c5e370c82103be884c08a0f10c152c5d0c8dceb04675f2173e70a35a0736a

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.474413Z digest=sha256:c688800e5070bfd06d9a68f9eb5cd78e3d37374451be5bd576d9aa4f7b1e0df6

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=sha256:58c37f71b3085ecad827667e926f387ec539a660ea465427ffd47efbd210b229

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.479296Z digest=sha256:dfc4770f825dcaeb3037b3700324a7038390fe2c6f96979c46b137c3a70f9c0e

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 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T10:15:54.481693Z digest=sha256:ba5e954511d8f28d113dbddfd3070d2a49f38f53842435c6ce4061f179f83f8b

Pith citing papers

No inbound Pith citation observations are available.