Paper Citation Record · LEDGER

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

As of 19 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 11 inbound Pith citation observations for arXiv:2504.19580.

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

pith.paper-citation-record.v1
2504.19580 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:54:07.816800Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:04:11.122014Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.596676Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy10
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80b0b9f7-d587-41fe-b305-25dc447e9dee · outbound

This paper cites Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.717745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e85afc62-04e4-43fa-93a2-713f89c36cb0 · outbound

This paper cites Multi-agent tra- jectory prediction with difficulty-guided feature enhancement network,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Multi-agent tra- jectory prediction with difficulty-guided feature enhancement network,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.145333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d565191f-ec93-4810-aa30-15d146d43bd7 · outbound

This paper cites PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.725506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a43838d-ed06-438d-8fd3-1ccd1ccc1716 · outbound

This paper cites Planning-oriented autonomous driving,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Planning-oriented autonomous driving,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.135985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e039992-8365-4912-a71f-82061b335439 · outbound

This paper cites Vad: Vectorized scene representation for efficient autonomous driving,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Vad: Vectorized scene representation for efficient autonomous driving,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.732982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d90dc9ac-cf57-4fbc-9363-b33afd69fa14 · outbound

This paper cites Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.736196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be2b4f31-dab2-4af5-ab34-cefd3dd46d01 · outbound

This paper cites Multimodal motion prediction with stacked transformers,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Multimodal motion prediction with stacked transformers,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.115180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 17450b80-aca6-424d-ac24-04bb354aafbf · outbound

This paper cites Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.105687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bbde181b-b4dd-4b0c-9542-e85ff7ac3916 · outbound

This paper cites R2p2: A reparameterized pushforward policy for diverse, precise generative path forecasting,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving R2p2: A reparameterized pushforward policy for diverse, precise generative path forecasting,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.096017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a010c76e-d830-4f35-9129-00f54c4a8e06 · outbound

This paper cites DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.748548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd00c96b-81ea-4696-8e55-4298f1af5821 · outbound

This paper cites DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.752159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06312728-ecf4-4d7f-af89-552103a90239 · outbound

This paper cites DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.755405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74f22575-5dda-4d8f-aa90-64df70a1c4b5 · outbound

This paper cites Transfuser: Imitation with transformer-based sensor fusion for au- tonomous driving,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Transfuser: Imitation with transformer-based sensor fusion for au- tonomous driving,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.086076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de9c649f-2263-4231-87cd-ce77d22cb668 · outbound

This paper cites VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.762204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9628b06-66f1-4348-a092-ac9107942e04 · outbound

This paper cites Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.765633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 449b595d-d427-411c-8fb4-4e9dda1955f0 · outbound

This paper cites Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.769163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53a570a2-d320-4898-bf78-bd0dc954c634 · outbound

This paper cites DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.772419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40bfb2af-9c69-46c0-ad13-991b3e7b99f2 · outbound

This paper cites Adaptive mixtures of local experts,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Adaptive mixtures of local experts,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.775757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbff2076-814b-4f86-a100-9541899ba21a · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.778712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38c8e510-7080-4ca8-ae65-c116ec1dcb17 · outbound

This paper cites GPT-4 Technical Report.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving GPT-4 Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.782148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f484e6d9-f892-47f2-a876-b436e628d14f · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.785406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a18c059a-8363-4a45-bdc5-64d399aa6b76 · outbound

This paper cites Generalizing Motion Planners with Mixture of Experts for Autonomous Driving.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Generalizing Motion Planners with Mixture of Experts for Autonomous Driving

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.788371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63a36351-f89f-465d-8ad2-fbd4a21eb573 · outbound

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

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.791655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 370dd5b3-9ad6-46be-9ac8-ed79fbb5e310 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Planning with Diffusion for Flexible Behavior Synthesis

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.794873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd37a8d1-8451-4b9b-b648-48561f85fb03 · outbound

This paper cites Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.064661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b7a10343-3810-4425-b6bd-40873bfc7171 · outbound

This paper cites Is ego status all you need for open-loop end-to-end autonomous driving?.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Is ego status all you need for open-loop end-to-end autonomous driving?

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.054913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b5d7d826-a3bd-48f0-9a6d-7dfa8e4da178 · outbound

This paper cites End-to-end autonomous driving: Advancements and challenges,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving End-to-end autonomous driving: Advancements and challenges,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.044819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07c6f7ab-a36d-4f84-a39b-2b335269d6fb · outbound

This paper cites Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.807362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10792723-f4df-4d36-a7ec-26602e5668ff · outbound

This paper cites Para- drive: Parallelized architecture for real-time autonomous driving,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Para- drive: Parallelized architecture for real-time autonomous driving,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.810818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7773dbe-7379-492f-a0de-035f91ed90a7 · outbound

This paper cites Goalflow: Goal-driven flow matching for multimodal trajec- tories generation in end-to-end autonomous driving,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Goalflow: Goal-driven flow matching for multimodal trajec- tories generation in end-to-end autonomous driving,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.813929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af24b882-9d8b-4945-afda-8c73f2e42e65 · outbound

This paper cites Openscene: The largest up-to-date 3d occu- pancy prediction benchmark in autonomous driving,.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving Openscene: The largest up-to-date 3d occu- pancy prediction benchmark in autonomous driving,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:54:08.029758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 84bd7ce3-6532-4b39-8df0-b425f62230b7 · inbound

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving cites this paper.

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:36:24.349477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4d7be0ed-7c69-414c-b9c6-38d453307678 · inbound

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving cites this paper.

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T20:04:11.122014Z

Source-reported events for the cited work

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Observation 9be33e9a-a135-4427-a66c-d153a75a0731 · inbound

PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving cites this paper.

PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:57:00.723011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3b648663-b9b8-40cb-af35-a610eda663e4 · inbound

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving cites this paper.

DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-17T06:48:01.028936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eff02468-6ce2-4c94-8196-62655eb1ffa9 · inbound

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving cites this paper.

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:59:59.467147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 46db6237-eec9-46a3-8416-e93744106b84 · inbound

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale cites this paper.

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T23:03:24.983389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a1928321-b2de-4bbd-90d3-2d5df2365770 · inbound

DriveFuture: Future-Aware Latent World Models for Autonomous Driving cites this paper.

DriveFuture: Future-Aware Latent World Models for Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:01:17.900268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4b09d7d3-0a21-4311-a158-89f39de3a56d · inbound

CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning cites this paper.

CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:59:01.628975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 29b4b2c6-c41d-4834-9775-dab13dcd11c5 · inbound

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving cites this paper.

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:54:21.277879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3c9c32b-2ebf-4caf-9f13-73edbdf706b6 · inbound

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving cites this paper.

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:55:28.893843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation face8a7c-b025-4f68-ba7b-68dd342a2b41 · inbound

Teaching Vision-Language-Action Models What to See and Where to Look cites this paper.

Teaching Vision-Language-Action Models What to See and Where to Look ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T16:48:39.597940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.