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Paper Citation Record · LEDGER

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge

As of 9 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 2 inbound Pith citation observations for arXiv:2506.21618.

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

pith.paper-citation-record.v1
2506.21618 v1

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:45.065208Z

measured 10 of 10 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T20:01:39.628512Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-20T09:23:10.769497Z

Reference resolution

8 of 8 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad634e48-5342-40d2-881a-d2b58be6588f · outbound

This paper cites write newline.

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:44.343178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:20:44.343178Z digest=sha256:8ac16837acdcd8ecd76639726280355bcc5caad9b05b43de2dc9304ab0984ad2

Observation 798ddc0c-e922-4e05-8614-44b623c6e0c6 · outbound

This paper cites Revisit mixture models for multi-agent simulation: Experimental study within a unified framework, 2025.

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge Revisit mixture models for multi-agent simulation: Experimental study within a unified framework, 2025

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:46.514747Z

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=arxiv_source observed=2026-08-06T23:20:44.409036Z digest=sha256:26c2791106f5eb53ef55dbf57a8b589d8b9a140c0ddc813c2aa399d84606f8eb

Observation a908aec4-0ba4-496d-ad69-5ad20a2ff882 · outbound

This paper cites The waymo open sim agents challenge.

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge The waymo open sim agents challenge

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:46.284840Z

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=arxiv_source observed=2026-08-06T23:20:44.506492Z digest=sha256:f37b6a93648c028fb329586fe4827beb996b96aae97c394390787e47a64839d3

Observation 2ba3719f-6c3a-4c8a-a2c5-900b8de2e644 · outbound

This paper cites Trajeglish: Traffic Modeling as Next-Token Prediction.

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge Trajeglish: Traffic Modeling as Next-Token Prediction

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:44.617783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:20:44.617783Z digest=sha256:8fc736101d4c6ed41ae26d4042ff9b17e5ea91bca445cb12ec44f52b06e626c5

Observation 3ccaa82f-939f-4b1a-b6db-26fc8db88546 · outbound

This paper cites Motionlm: Multi-agent motion forecasting as language modeling.

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge Motionlm: Multi-agent motion forecasting as language modeling

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:46.044740Z

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=arxiv_source observed=2026-08-06T23:20:44.732605Z digest=sha256:ac37f5ce7b1c07c4ac1f5ea9ecaa1e101059413a73f28adaa210eed9f4eb0f53

Observation d52a4ff0-f5b7-46e8-a53e-ea1dcbce6836 · outbound

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

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge Smart: Scalable multi-agent real-time motion generation via next-token prediction

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:45.817520Z

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=arxiv_source observed=2026-08-06T23:20:44.835756Z digest=sha256:178311da7b9c713abb6a397e7085b46ed9c1ab36f42f1172c8eea5624db29f17

Observation bcfc6d98-0d56-4c82-a637-98a0c6da8282 · outbound

This paper cites Closed-loop supervised fine-tuning of tokenized traffic models.

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge Closed-loop supervised fine-tuning of tokenized traffic models

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:45.597086Z

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=arxiv_source observed=2026-08-06T23:20:44.984757Z digest=sha256:e4e66842c70a3685db6dc09ac01ae6c32fadfc9ad1964270096b3105561db358

Observation 02a0dc2f-2466-47d3-ab56-524068ab2371 · outbound

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

TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge Kigras: Kinematic-driven generative model for realistic agent simulation

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T23:20:45.355405Z

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=arxiv_source observed=2026-08-06T23:20:45.065208Z digest=sha256:7cb2ad565348558dd2438ea4c600bb25205c871800ecb215d732e0f812b51a0a

Pith citing papers

Observation c72bd7fe-a074-4c1b-bebb-8aefa3817d46 · inbound

RLFTSim: Realistic and Controllable Multi-Agent Traffic Simulation via Reinforcement Learning Fine-Tuning cites this paper.

RLFTSim: Realistic and Controllable Multi-Agent Traffic Simulation via Reinforcement Learning Fine-Tuning TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-20T09:23:10.771057Z

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=2026-05-20T09:19:06.011699Z digest=sha256:46270823a9b57f782d9abe216493d264166c2a54d80212e0e4280f19f50d9c04

Observation 8c587f65-62b5-4665-85ff-f50b28f651c9 · inbound

Agent-driven Long-tail Simulation for Autonomous Driving cites this paper.

Agent-driven Long-tail Simulation for Autonomous Driving TrajTok: Technical Report for 2025 Waymo Open Sim Agents Challenge

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-11T20:01:39.628512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T20:01:39.628512Z digest=sha256:e79b03fd30c90fb3b92efb279092d7db5ae0d056059fd9645d9c75eeb17fb6cb