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Paper Citation Record · LEDGER

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation

As of 16 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2506.17213.

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

pith.paper-citation-record.v1
2506.17213 v2

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:15:25.496878Z

measured 56 of 56 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

56 of 56 outbound references displayed

  • verified exact1
  • verified fuzzy32
  • unresolved22
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cf4133b3-81d0-4bcc-93a3-4bbc6a8c12e2 · outbound

This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.272874Z digest=sha256:bbf66a9a174ab3e5fb2c66e506f8390e36ec1153b9f45f350e3c1693f365c3de

Observation 8068e5f6-25f8-4b89-bb58-4c6df0947eb6 · outbound

This paper cites Implicit latent variable model for scene-consistent motion forecasting.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Implicit latent variable model for scene-consistent motion forecasting

Reference 2

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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=2026-08-15T19:15:25.278364Z digest=sha256:e707d3fbd0c31b53fe1bca4237113b4af80d032842353740d60a91f337fc8d68

Observation a2d1f496-c304-4f35-b1ae-674129926beb · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 3

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source=pdf_text observed=2026-08-15T19:15:25.282180Z digest=sha256:7b4b856c77e270c9dc97bac99b7a485e40f75bec4db7c3a6ca9d3976cedeba37

Observation 81445ebe-ab0c-474f-82e4-062e958bfec7 · outbound

This paper cites SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.285921Z digest=sha256:cb7ffe96da1795804a1839fe8a08dbac7f495b86be76c850c814740ad4b8cae1

Observation 152a979c-8ed6-4a79-8c16-f5926faa2851 · outbound

This paper cites Rift: Closed-loop rl fine-tuning for realistic and controllable traf- fic simulation, 2025.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Rift: Closed-loop rl fine-tuning for realistic and controllable traf- fic simulation, 2025

Reference 5

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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=2026-08-15T19:15:25.290768Z digest=sha256:0fbc43f99ba36430942b3cfc2b048619861d27752436aff73a4824d526acc3f9

Observation 6b924b24-074c-4ec9-8dc0-a792b7aec364 · outbound

This paper cites Sledge: Synthesizing driving environments with generative models and rule-based traffic.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Sledge: Synthesizing driving environments with generative models and rule-based traffic

Reference 6

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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=2026-08-15T19:15:25.294722Z digest=sha256:6d452cd49f43eff32dc5da0b68b53dd6bc091c6adc8e9901f9776155002f8ef3

Observation a77c0a0b-3c20-429b-a4f1-ba3465a6445f · outbound

This paper cites Robust Autonomy Emerges from Self-Play.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Robust Autonomy Emerges from Self-Play

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.299216Z digest=sha256:3af0f31db58449c9572d66dc1331557bf14c30e2f4997b674e5dc389dec1a21f

Observation f980ccf0-7085-40b6-97f3-46e027cfa995 · outbound

This paper cites RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.303823Z digest=sha256:76f1321c30d154b0a2bc135f5d28b26ebe40a27c1ad63b43004f174c037cf603

Observation dad9be7e-c9f4-4217-b254-bb2d280d7cdc · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Large scale interactive motion forecasting for autonomous driving: The waymo open mo- tion dataset

Reference 9

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raw_fallback, observed 2026-08-15T19:15:26.067197Z

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=2026-08-15T19:15:25.308005Z digest=sha256:26580acf8dafabbdf9554eb93ace44b2aa2e91240fb887af7b491abafee06f1a

Observation e264f2ee-1880-4aed-ab8d-833712f4e564 · outbound

This paper cites Trafficgen: Learning to generate diverse and re- alistic traffic scenarios.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Trafficgen: Learning to generate diverse and re- alistic traffic scenarios

Reference 10

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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=2026-08-15T19:15:25.311423Z digest=sha256:af3180bc4ad6d317966edcf54d6b64e5602ff2fbc7ecc8a9f17b851e68ca663e

Observation 4a56793e-afcb-4fce-85bf-873848bc891f · outbound

This paper cites Solv- ing motion planning tasks with a scalable generative model.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Solv- ing motion planning tasks with a scalable generative model

Reference 11

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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=2026-08-15T19:15:25.316398Z digest=sha256:783fe292013f8f91d2e46e84e330aa538e00509b34d8b68d2dc340947061c571

Observation 59469840-168f-4e8b-b288-5f834f63662b · outbound

This paper cites Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.323675Z digest=sha256:4a1e34eb0986093e8344bac5a210a9faa463a5ac906bc5c1fb141a33a7edb904

Observation 214eb6e0-9ee8-4c83-8f0b-16dc1ca218d9 · outbound

This paper cites Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning

Reference 13

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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=2026-08-15T19:15:25.327510Z digest=sha256:3a63d16eb3d9fced128d0ef598c8c1b25addcaa6b71983825424304239951a14

Observation 3fd3123f-3d95-4aef-945d-7ba8f8cacccd · outbound

This paper cites The waymo open sim agents challenge.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation The waymo open sim agents challenge

Reference 14

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raw_fallback, observed 2026-08-15T19:15:26.015110Z

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=2026-08-15T19:15:25.331131Z digest=sha256:346f16bad2cd0d72c7b03734315dd139ee132c41859e5155bedb934050f31be1

Observation d6d78f5a-cb3b-4ce0-85dd-5b7f952ed8e3 · outbound

This paper cites Refaat, and Benjamin Sapp.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Refaat, and Benjamin Sapp

Reference 15

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raw_fallback, observed 2026-08-15T19:15:26.004421Z

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=2026-08-15T19:15:25.334525Z digest=sha256:06460d9e92ad24d35da6c3733572829124fadf3849088420fd991ab7f1c68b49

Observation 496c42fb-3fd2-40d0-b261-28e475c52d17 · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Trajeglish: Traffic Modeling as Next-Token Prediction

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.337880Z digest=sha256:c7830bde09d696df8c47fc9773e26742df5bbb250384e81d0a0d2f8c662967f8

Observation ead492b8-4083-4652-a54e-dbce5c770424 · outbound

This paper cites Generating useful accident-prone driv- ing scenarios via a learned traffic prior.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Generating useful accident-prone driv- ing scenarios via a learned traffic prior

Reference 17

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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=2026-08-15T19:15:25.341554Z digest=sha256:9ba46e459f11ac368d0b66a7b0bba808ae91f76ba46bef20acf2717d317d6015

Observation f2edffcf-e564-4817-8c29-b5622462e9b2 · outbound

This paper cites CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning

Reference 18

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source=pdf_text observed=2026-08-15T19:15:25.345407Z digest=sha256:8177eead66beeaa1e33ce7503adf7ca020c53e24b8798e93e23844bdb5f72734

Observation 10168e7a-6ad1-44ec-b0d8-ac2a2c946baf · outbound

This paper cites Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environments.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environments

Reference 19

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source=pdf_text observed=2026-08-15T19:15:25.349480Z digest=sha256:5b46f1dcb091748fb212c726e20a097dc0d00a65debadeb2496ce37bdd4fc367

Observation 922f5dc8-4a26-4740-aba2-74bfebd59264 · outbound

This paper cites Trajectron++: Dynamically-feasible trajec- tory forecasting with heterogeneous data.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Trajectron++: Dynamically-feasible trajec- tory forecasting with heterogeneous data

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=2026-08-15T19:15:25.353102Z digest=sha256:8e68cdc3d0189229589c9fb6c731204032fe2f01d57703ccacb769f9103f43b4

Observation 21c5e0d4-ea64-4c05-a18d-a052f0956ec6 · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Motionlm: Multi-agent motion forecast- ing as language modeling

Reference 21

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raw_fallback, observed 2026-08-15T19:15:25.974538Z

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=2026-08-15T19:15:25.356392Z digest=sha256:1bbc812779e3cc2c70e1312f923d0361672b14928472040e044d0a1d106e7336

Observation 0e3184a7-e9df-4f61-9501-bf630fcf235e · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Trafficsim: Learning to simulate realistic multi- agent behaviors

Reference 22

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raw_fallback, observed 2026-08-15T19:15:25.963147Z

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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=2026-08-15T19:15:25.359910Z digest=sha256:54811c9f271bd81bfda89f61ee10ddb8c507409c129d89fe1fb2596a1411f2fa

Observation 9c7dd942-af8f-471d-808d-459a8703b1c9 · outbound

This paper cites Scenegen: Learning to generate realistic traffic scenes.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Scenegen: Learning to generate realistic traffic scenes

Reference 23

Resolution
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raw_fallback, observed 2026-08-15T19:15:25.952579Z

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=2026-08-15T19:15:25.363216Z digest=sha256:01c23c9ed0fe2bba6c6b541c5477930a1288ab6568f07c8b3415fdb18baeb292

Observation b9dcde9a-d0a0-4afd-8eed-0d2c1f055399 · outbound

This paper cites Language conditioned traffic generation.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Language conditioned traffic generation

Reference 24

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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=2026-08-15T19:15:25.366453Z digest=sha256:6c6323f5f0785a26aaf1fb3bb0e3519f177dafc9119e75f374f00094784351be

Observation 3a28b449-88ee-43e1-b457-7867a62a6eb3 · outbound

This paper cites Promptable closed-loop traffic simulation.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Promptable closed-loop traffic simulation

Reference 25

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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=2026-08-15T19:15:25.369769Z digest=sha256:49443838c4ed982bce8313525515f3e9b86766803a8cbaa6483603f9f04bb252

Observation e79480a9-d8fa-4517-8f5a-3770f4e36119 · outbound

This paper cites Interactive Post-Training for Vision-Language-Action Models.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Interactive Post-Training for Vision-Language-Action Models

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.373313Z digest=sha256:a467171e3b561bca891d7632f44c264a639257d90815c629fae76eeeffb1a8b9

Observation 87e0d940-bdaf-49fd-9f56-ba970611073f · outbound

This paper cites Scenediffuser++: City-scale traffic simulation via a generative world model.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Scenediffuser++: City-scale traffic simulation via a generative world model

Reference 27

Resolution
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raw_fallback, observed 2026-08-15T19:15:25.920913Z

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=2026-08-15T19:15:25.377024Z digest=sha256:2c696533b31484c0075992d03c8e1c523a4ff14dd2022e073ef8baf992ab21ef

Observation f92fc0f2-b85e-4faf-8b70-9961f93f44ec · outbound

This paper cites MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.380108Z digest=sha256:fd0e24b472a9bca111a1869047b727891a6aec13b73c0a16bb6a2bba8c5f11a3

Observation d162c7a5-0aa5-4af0-bc19-a95b21f4c0b3 · outbound

This paper cites Advsim: Generating safety-critical sce- narios for self-driving vehicles.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Advsim: Generating safety-critical sce- narios for self-driving vehicles

Reference 29

Resolution
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raw_fallback, observed 2026-08-15T19:15:25.910928Z

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=2026-08-15T19:15:25.383567Z digest=sha256:9592c5290d4862e620cd13c33d17543e38c12f1e8732b5a104dd9798c0ec5e22

Observation aca9170e-3d96-4361-89f4-11c30b2226e6 · outbound

This paper cites Flow: A modular learn- ing framework for mixed autonomy traffic.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Flow: A modular learn- ing framework for mixed autonomy traffic

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.900814Z

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=2026-08-15T19:15:25.387150Z digest=sha256:46f756cdaea76dcc5a245f7c28b375b28f241e277b6d57e39c02a6e03dbdbad0

Observation 88669b28-8d7f-4d24-9067-f80eddf38114 · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Smart: Scalable multi-agent real-time motion generation via next-token prediction

Reference 31

Resolution
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raw_fallback, observed 2026-08-15T19:15:25.889188Z

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=2026-08-15T19:15:25.391224Z digest=sha256:e93993937d2fb9eed03c17f7851aa006fa2191893d4b06af67aa48b8282de3fc

Observation 2d3e178c-80ec-441d-94ef-dd2065a60598 · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.394634Z digest=sha256:2ffd054900a0c91c85b0cd43ceae3e88b0b66717f7c29ca76089c9a9b859e639

Observation 3f71b7ac-3e5c-496d-9c74-ddb22333a99d · outbound

This paper cites AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.399258Z digest=sha256:6e400012b34ecc9f69b1ee125bc02e0afe694f2d705d3d527e81e2298d1f7bbc

Observation bfa1906d-a91a-4c5b-bb0a-3206ec5df574 · outbound

This paper cites Gpd- 1: Generative pre-training for driving, 2024.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Gpd- 1: Generative pre-training for driving, 2024

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.879292Z

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=2026-08-15T19:15:25.402937Z digest=sha256:f912d31351e8d956a6cfa413df34b5e68ff3de000d848cdab5964c66f23c3da5

Observation 815522ea-4ab6-45f2-8720-b02a3e6c770d · outbound

This paper cites Diffscene: Diffusion-based safety-critical sce- nario generation for autonomous vehicles.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Diffscene: Diffusion-based safety-critical sce- nario generation for autonomous vehicles

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.868315Z

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=2026-08-15T19:15:25.406243Z digest=sha256:66a62279231f5b2374ad951c8a23f96c53189a1311d3ed206ec76e3ea31b2088

Observation d49db82e-6445-4e25-8b9c-5ad4d66f6b60 · outbound

This paper cites Bits: Bi-level imitation for traffic simulation.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Bits: Bi-level imitation for traffic simulation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.856785Z

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=2026-08-15T19:15:25.409558Z digest=sha256:14d2cd1e96fa62d5b7b59845e52158cc9e971afa3a4ac8105dbb923e23d359a3

Observation 0896c1b0-c55e-459b-bd12-f4e19c3ec7ff · outbound

This paper cites Modality- specialized synergizers for interleaved vision-language gen- eralists.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Modality- specialized synergizers for interleaved vision-language gen- eralists

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.846541Z

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=2026-08-15T19:15:25.413376Z digest=sha256:36297554665469b840b96f06af2572e7e5f59a669b91d68747dc97a769098e22

Observation beb0ea72-e94f-4417-a3ef-e3dd289b9a02 · outbound

This paper cites RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous Driving.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous Driving

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-15T19:15:25.562700Z

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=2026-08-15T19:15:25.416760Z digest=sha256:cc715665bcee4f00a3ed244fff25de6542a6bfe7dd50fdcf50733d1bf1cf7267

Observation 59317500-3853-4731-92cb-21024766ada4 · outbound

This paper cites Learning realistic traffic agents in closed-loop.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Learning realistic traffic agents in closed-loop

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.834864Z

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=2026-08-15T19:15:25.420368Z digest=sha256:922e98744989972a8b0c3790cfcb86956b15d7c437cfa91b03ab854870529652

Observation 43f256c2-a7ad-4916-a2e4-5cc0edddbdd2 · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation TrafficBots V1.5: Traffic Simulation via Conditional VAEs and Transformers with Relative Pose Encoding

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T19:15:25.424175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.424175Z digest=sha256:e5807a1411f85c86df395296411aa11d70fc697d2ae774f53384db67c50d23b7

Observation 109b6200-ea27-4c27-8e5f-b782b75af022 · outbound

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

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Closed- loop supervised fine-tuning of tokenized traffic models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.823928Z

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=2026-08-15T19:15:25.429004Z digest=sha256:36d7f7802b5854f7a2ba4360795a53a835ccf5a558d0d42f47a5cd7f07411a2b

Observation 8a7b6e26-85fa-4ec8-92d2-2c7aed70861c · outbound

This paper cites KiGRAS: Kinematic-Driven Generative Model for Realistic Agent Simulation.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation KiGRAS: Kinematic-Driven Generative Model for Realistic Agent Simulation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T19:15:25.433579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.433579Z digest=sha256:53596d7a58c7ad94588392e93200a8470135a4b02b83cf45c6062c9218ddd773

Observation d14e3274-5326-4907-b449-49fe4ebba592 · outbound

This paper cites Multi-agent tensor fusion for contextual trajectory predic- tion.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Multi-agent tensor fusion for contextual trajectory predic- tion

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.812154Z

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=2026-08-15T19:15:25.437384Z digest=sha256:47d7b8bf72eb6f59fdf0cddc7f41275282d6627b847fd4f126c5a7f0aabf0b8c

Observation d29a8849-b83a-458f-a230-dd6b5181a326 · outbound

This paper cites Language-guided traffic simulation via scene-level diffusion.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Language-guided traffic simulation via scene-level diffusion

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T19:15:25.440835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.440835Z digest=sha256:3ee36cb37f31c0f76b32a965790b576ac4cd227279b823b008b6235d847a7b86

Observation d511bcc4-bbe7-4fec-bdc6-e1df771ebb9d · outbound

This paper cites Guided conditional diffusion for controllable traffic simula- tion.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Guided conditional diffusion for controllable traffic simula- tion

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.794481Z

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=2026-08-15T19:15:25.444302Z digest=sha256:b562349f8c3cff8b7a6c7c97a155081ddc5ccf124a427b6b805ed5d0f21d756a

Observation bd628ef8-78f8-4273-8bc4-4b5162c607b0 · outbound

This paper cites BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T19:15:25.447874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:15:25.447874Z digest=sha256:737afd6368b8ba0a774749744c64493a93d063e8a152c5bb566a482073f3f3ff

Observation 273ab280-dab5-4b0a-a8dd-87330eeb355d · outbound

This paper cites Otherwise, the steps not satisfy the conditions above have Ms = 0, including the EOS.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Otherwise, the steps not satisfy the conditions above have Ms = 0, including the EOS

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.761677Z

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=2026-08-15T19:15:25.459555Z digest=sha256:29dc7b914d73384df151e60d3e16705a1885a0a51608e9029bb037bd0bad09fa

Observation b9dbbb1e-fe8b-4c97-96ca-62206d399a23 · outbound

This paper cites an unresolved cited work.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:15:25.749084Z

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=2026-08-15T19:15:25.463524Z digest=sha256:13b4d551c6a605280069258118eda65e42e6104720aeb6529739977330a80df8

Observation f1f421ad-18e6-4bbd-a861-55dbeb521fc4 · outbound

This paper cites an unresolved cited work.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:15:25.772391Z

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=2026-08-15T19:15:25.470997Z digest=sha256:564b7a9ed2d4c74fa15cdf395e9eef839b22abfba981631bcb638ca104bafaa8

Observation bfdae6ae-0c45-4bfe-9933-aeb04b11ba67 · outbound

This paper cites Then the total lossLct 1:N for the entire temporal control to- ken sequence is calculated similar to Equation 17 which takesY ct,Xct,M ct as inputs.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Then the total lossLct 1:N for the entire temporal control to- ken sequence is calculated similar to Equation 17 which takesY ct,Xct,M ct as inputs

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.726069Z

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=2026-08-15T19:15:25.478581Z digest=sha256:2e18434f1677f3496b37f2fd303e5ff9fd061f1271cee6598bf4b3d245444e51

Observation 663343b8-561c-47c2-91a4-1286baf938ae · outbound

This paper cites an unresolved cited work.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:15:25.783279Z

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=2026-08-15T19:15:25.482649Z digest=sha256:9ee9cd3f159018a43d6e76aacd41a7fe5c37e928e2ffb7f9793851ff15d73951

Observation a1ecedf0-1cff-4b7a-8e94-fdbdc652a71e · outbound

This paper cites an unresolved cited work.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:15:25.737058Z

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=2026-08-15T19:15:25.485875Z digest=sha256:54fa7798d7ec580453f66fb343d5f4a9198b376717ccb947d8688c7dd15576c2

Observation 80ff9234-45a2-4e74-88da-468612a9ae84 · outbound

This paper cites Then the total lossLcs 1:M′ for the spatial control tokens is ob- tained similar to Equation 17.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Then the total lossLcs 1:M′ for the spatial control tokens is ob- tained similar to Equation 17

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.714518Z

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=2026-08-15T19:15:25.489193Z digest=sha256:d4371eba8b13bc9cdbd3147c2148004258a2e8ae16a26ed4f41d89b163b27259

Observation 0b0bf18e-e159-4b4a-9b2f-c0e68554e198 · outbound

This paper cites an unresolved cited work.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:15:25.703378Z

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=2026-08-15T19:15:25.492884Z digest=sha256:7ead986db210fa5dd6f9d7745c1acbce28904886e6447bd790c1217fdc3b8b00

Observation ce53994b-1a60-46b3-9c3b-3f5dc21130fb · outbound

This paper cites flickering.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation flickering

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:15:25.692740Z

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=2026-08-15T19:15:25.496878Z digest=sha256:f57397223f214732743bae064373cd33df98c7cbb168202d7f9ab2a190ce4d68

Observation 33acd620-e339-4f33-aba8-57f00ac1b611 · outbound

This paper cites an unresolved cited work.

Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation Unresolved cited work

Reference 404

Resolution
parse uncertain
raw_fallback, observed 2026-08-15T19:15:26.036215Z

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=2026-08-15T19:15:25.320233Z digest=sha256:7ea72aa2e4d98ba90e35598472ba9bbcb69e70de639bc7a9226a4e5e3f76c95f

Pith citing papers

No inbound Pith citation observations are available.