EponaV2: Driving World Model with Comprehensive Future Reasoning | Paper Citation Record

Observation 5b2af608-fa2c-4df7-a041-96b07a9ec321 · outbound

This paper cites Building normalizing flows with stochastic interpolants.

EponaV2: Driving World Model with Comprehensive Future Reasoning Building normalizing flows with stochastic interpolants

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.125344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6d3e526b-5d58-465a-98da-29ba6fe9dfcd · outbound

This paper cites Qwen3-VL Technical Report.

EponaV2: Driving World Model with Comprehensive Future Reasoning Qwen3-VL Technical Report

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.415904Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 87a28916-015b-47c7-bfaf-096534eef718 · outbound

This paper cites RoboTron-Sim: Improving real-world driving via simulated hard-case.

EponaV2: Driving World Model with Comprehensive Future Reasoning RoboTron-Sim: Improving real-world driving via simulated hard-case

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.427203Z

Source-reported events for the cited work

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Observation d209af04-47f0-4570-a16c-0cf9adb32d06 · outbound

This paper cites nuScenes: A multimodal dataset for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning nuScenes: A multimodal dataset for autonomous driving

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T13:10:48.016300Z

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Observation 8168d5ee-3df1-4431-a517-c24ee3aa7da3 · outbound

This paper cites Pseudo-simulation for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Pseudo-simulation for autonomous driving

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.119981Z

Source-reported events for the cited work

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Observation 60e42396-0e5f-439c-b74d-53218628507e · outbound

This paper cites SAM 3: Segment Anything with Concepts.

EponaV2: Driving World Model with Comprehensive Future Reasoning SAM 3: Segment Anything with Concepts

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.606585Z

Source-reported events for the cited work

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Observation 52a93869-6257-4d53-baa8-4f37d2dd8476 · outbound

This paper cites Devil is in narrow policy: Unleashing exploration in driving vla models.

EponaV2: Driving World Model with Comprehensive Future Reasoning Devil is in narrow policy: Unleashing exploration in driving vla models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.722613Z

Source-reported events for the cited work

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Observation 05b856bd-dd79-4bcc-ad4f-9d2e69268b73 · outbound

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

EponaV2: Driving World Model with Comprehensive Future Reasoning VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.649738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac9a65f2-b247-4658-a140-bccb117d3370 · outbound

This paper cites DrivingGPT: Unifying driving world modeling and planning with multi-modal autoregressive transformers.

EponaV2: Driving World Model with Comprehensive Future Reasoning DrivingGPT: Unifying driving world modeling and planning with multi-modal autoregressive transformers

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.270582Z

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Observation 037a99b4-b773-4dda-886f-e5b7e00551d1 · outbound

This paper cites TransFuser: Imitation with transformer-based sensor fusion for autonomous driving.IEEE transactions on pattern analysis and machine intelligence, 45(11):12878–12895.

EponaV2: Driving World Model with Comprehensive Future Reasoning TransFuser: Imitation with transformer-based sensor fusion for autonomous driving.IEEE transactions on pattern analysis and machine intelligence, 45(11):12878–12895

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.231056Z

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Observation 4868bfcb-be75-4b89-b0c7-55a3980b420d · outbound

This paper cites NA VSIM: Data-driven non-reactive autonomous vehicle simulation and benchmarking.

EponaV2: Driving World Model with Comprehensive Future Reasoning NA VSIM: Data-driven non-reactive autonomous vehicle simulation and benchmarking

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.191341Z

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Observation 6be5266c-c959-4096-aa54-3a97fd1cd58a · outbound

This paper cites Scaling vision transformers to 22 billion parameters.

EponaV2: Driving World Model with Comprehensive Future Reasoning Scaling vision transformers to 22 billion parameters

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.266089Z

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Observation 1165cc00-c32d-4593-be08-c8c5e37f3a7d · outbound

This paper cites Interleave-vla: Enhancing robot manipulation with interleaved image-text instructions.

EponaV2: Driving World Model with Comprehensive Future Reasoning Interleave-vla: Enhancing robot manipulation with interleaved image-text instructions

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.634790Z

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Observation c7b5d543-6f38-4bd7-965a-1220d1f42c20 · outbound

This paper cites Rap: 3d rasterization augmented end-to-end planning.arXiv preprint arXiv:2510.04333.

EponaV2: Driving World Model with Comprehensive Future Reasoning Rap: 3d rasterization augmented end-to-end planning.arXiv preprint arXiv:2510.04333

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.785241Z

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Observation f6c542d4-a414-4835-92e8-9ab405733446 · outbound

This paper cites ORION: A holistic end-to-end autonomous driving framework by vision-language instructed action generation.

EponaV2: Driving World Model with Comprehensive Future Reasoning ORION: A holistic end-to-end autonomous driving framework by vision-language instructed action generation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.287158Z

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Observation fc782787-14d9-4da3-b90b-0857f20b4ddb · outbound

This paper cites FlowAD: Ego-scene interactive modeling for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning FlowAD: Ego-scene interactive modeling for autonomous driving

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.453153Z

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Observation 2f5516ce-9ef6-4277-96a7-0f3b87d2bddc · outbound

This paper cites Tan et al.

EponaV2: Driving World Model with Comprehensive Future Reasoning Tan et al

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.134799Z

Source-reported events for the cited work

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Observation 8a882fc2-4122-4ed1-a5cc-85bbf8058cfd · outbound

This paper cites Percept-W AM: Perception-enhanced world-awareness-action model for robust end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Percept-W AM: Perception-enhanced world-awareness-action model for robust end-to-end autonomous driving

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.773113Z

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Observation 37055550-ba9b-4eba-8d93-bfa47ec30a04 · outbound

This paper cites Distilling multi-modal large language models for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Distilling multi-modal large language models for autonomous driving

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.179423Z

Source-reported events for the cited work

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Observation e0829407-1c22-481c-bb31-85e58067ebb4 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851.

EponaV2: Driving World Model with Comprehensive Future Reasoning Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.175506Z

Source-reported events for the cited work

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Observation 666c60c5-5477-4a1e-80b1-5fb6da32c6ae · outbound

This paper cites an unresolved cited work.

EponaV2: Driving World Model with Comprehensive Future Reasoning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-15T05:15:04.274208Z

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Observation 5d72aee6-567a-4616-aee4-08368ba6c145 · outbound

This paper cites Planning-oriented autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Planning-oriented autonomous driving

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.257259Z

Source-reported events for the cited work

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Observation 3076f2fe-987a-49a7-98f5-6de8d0301a2f · outbound

This paper cites Prioritizing perception-guided self- supervision: A new paradigm for causal modeling in end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Prioritizing perception-guided self- supervision: A new paradigm for causal modeling in end-to-end autonomous driving

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.215838Z

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Observation 69144ec1-451e-4e5a-9f30-3eb15c84de2f · outbound

This paper cites Dino-tok: Adapting dino for visual tokenizers.

EponaV2: Driving World Model with Comprehensive Future Reasoning Dino-tok: Adapting dino for visual tokenizers

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.670680Z

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Observation d5785ccc-c832-43d6-af7e-18001a544c02 · outbound

This paper cites Spatial retrieval augmented autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Spatial retrieval augmented autonomous driving

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.741808Z

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Observation dbfa16d1-670d-4a03-bdc8-90ba14d54cbb · outbound

This paper cites V AD: Vectorized scene representation for efficient autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning V AD: Vectorized scene representation for efficient autonomous driving

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.252609Z

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Observation 2cf152e4-04d5-47a3-9f2a-8cdbef8caf14 · outbound

This paper cites Scaling Laws for Neural Language Models.

EponaV2: Driving World Model with Comprehensive Future Reasoning Scaling Laws for Neural Language Models

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.683667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5ed3e05a-f074-4c57-aa5b-2dce3c2e555b · outbound

This paper cites SynAD: Enhancing real-world end-to-end autonomous driving models through synthetic data integration.

EponaV2: Driving World Model with Comprehensive Future Reasoning SynAD: Enhancing real-world end-to-end autonomous driving models through synthetic data integration

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.221696Z

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Observation e71a0b73-181a-4d35-a829-41800c56206a · outbound

This paper cites Safedrive: Fine-grained safety reasoning for end-to-end driving in a sparse world.

EponaV2: Driving World Model with Comprehensive Future Reasoning Safedrive: Fine-grained safety reasoning for end-to-end driving in a sparse world

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.761521Z

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Observation 4ed48ea4-5bc2-4225-b018-dccfe7d35c55 · outbound

This paper cites Driving on registers.

EponaV2: Driving World Model with Comprehensive Future Reasoning Driving on registers

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.261561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1b031243-146c-4785-b2ab-e1de46a82db6 · outbound

This paper cites VLR-Driver: Large vision-language-reasoning models for embodied autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning VLR-Driver: Large vision-language-reasoning models for embodied autonomous driving

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.225357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bc778ee4-e03a-492b-b652-520e97376f6c · outbound

This paper cites Sgdrive: Scene-to-goal hierarchical world cognition for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Sgdrive: Scene-to-goal hierarchical world cognition for autonomous driving

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.444872Z

Source-reported events for the cited work

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Observation 81b7a5aa-1309-443e-a67c-06b377247ccb · outbound

This paper cites SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-22T02:03:27.523663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7b9a9b6e-045d-4828-a484-70870465c9c4 · outbound

This paper cites Discrete diffusion for reflective vision-language-action models in autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Discrete diffusion for reflective vision-language-action models in autonomous driving

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.484556Z

Source-reported events for the cited work

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Observation aeabeedb-0efe-4b0f-9d7d-d76c32674a34 · outbound

This paper cites Enhancing End-to-End Autonomous Driving with Latent World Model.

EponaV2: Driving World Model with Comprehensive Future Reasoning Enhancing End-to-End Autonomous Driving with Latent World Model

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:38:52.003079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5813aa8b-2a3a-4424-8ffd-1fefe9163b72 · outbound

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

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-17T06:48:01.146010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 488364e1-8764-45d0-a81b-0b4b50268a3e · outbound

This paper cites End-to-end driving with online trajectory evaluation via BEV world model.

EponaV2: Driving World Model with Comprehensive Future Reasoning End-to-end driving with online trajectory evaluation via BEV world model

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.211871Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 18aabbb7-4156-432b-9948-85999a4cf083 · outbound

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

EponaV2: Driving World Model with Comprehensive Future Reasoning ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:36:24.555133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0923ed12-8785-428a-afc0-f456d577c9bd · outbound

This paper cites an unresolved cited work.

EponaV2: Driving World Model with Comprehensive Future Reasoning Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-05-15T05:15:04.248064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation da4e1be7-4d39-443d-95fa-3a4905e05747 · outbound

This paper cites BEVFormer: Learning bird’s-eye-view representation from Lidar-camera via spatiotemporal transformers.

EponaV2: Driving World Model with Comprehensive Future Reasoning BEVFormer: Learning bird’s-eye-view representation from Lidar-camera via spatiotemporal transformers

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.152633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4c79f644-236f-498a-8790-99e1d974eb71 · outbound

This paper cites DiffusionDrive: Truncated diffusion model for end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning DiffusionDrive: Truncated diffusion model for end-to-end autonomous driving

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.130081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dfd02757-2013-4fef-a5fa-d361c49c92a3 · outbound

This paper cites Depth Anything 3: Recovering the Visual Space from Any Views.

EponaV2: Driving World Model with Comprehensive Future Reasoning Depth Anything 3: Recovering the Visual Space from Any Views

Reference 42

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T05:15:02.533212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 941724b1-67c2-4e7b-9035-a43c54c26b30 · outbound

This paper cites an unresolved cited work.

EponaV2: Driving World Model with Comprehensive Future Reasoning Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-05-15T05:15:04.278511Z

Source-reported events for the cited work

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Observation d6a62b20-7ca5-4789-bcb0-5db115b97d95 · outbound

This paper cites CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.696453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation adee3224-4ef2-4295-a23a-5f96489cbbe6 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

EponaV2: Driving World Model with Comprehensive Future Reasoning Flow-GRPO: Training Flow Matching Models via Online RL

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.778731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ca28abfa-e636-4909-a1ea-ceba2d68227a · outbound

This paper cites Guideflow: Constraint-guided flow matching for planning in end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Guideflow: Constraint-guided flow matching for planning in end-to-end autonomous driving

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.663948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c3831704-27f6-45f4-a88e-3bb3472f6863 · outbound

This paper cites CogDriver: Integrating Cognitive Inertia for Temporally Coherent Planning in Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning CogDriver: Integrating Cognitive Inertia for Temporally Coherent Planning in Autonomous Driving

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.728919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3f70ec53-b8ef-434f-acfe-7474fe05081e · outbound

This paper cites arXiv preprint arXiv:2509.23589 (2025) 10.

EponaV2: Driving World Model with Comprehensive Future Reasoning arXiv preprint arXiv:2509.23589 (2025) 10

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.749586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f899078c-00ed-404b-ac2e-31ac01857321 · outbound

This paper cites GaussianFusion: Gaussian-based multi-sensor fusion for end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning GaussianFusion: Gaussian-based multi-sensor fusion for end-to-end autonomous driving

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.207941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 04f44a02-d9a4-4067-9d76-9fb41916f741 · outbound

This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

EponaV2: Driving World Model with Comprehensive Future Reasoning Flow straight and fast: Learning to generate and transfer data with rectified flow

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.170982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5344a174-dc29-4d34-91f4-eecac0e60c80 · outbound

This paper cites ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.708640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f2524657-156c-4bf9-8b8a-e2968c220789 · outbound

This paper cites Unleashing vla potentials in autonomous driving via explicit learning from failures.

EponaV2: Driving World Model with Comprehensive Future Reasoning Unleashing vla potentials in autonomous driving via explicit learning from failures

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.734828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation abd3a3ce-0c64-4559-b3a5-9dae432150b8 · outbound

This paper cites LEAD: Minimizing learner-expert asymmetry in end-to-end driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning LEAD: Minimizing learner-expert asymmetry in end-to-end driving

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.239108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 90732b62-6bac-43ad-b118-112c514e3fc5 · outbound

This paper cites Embodied cognition augmented end2end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Embodied cognition augmented end2end autonomous driving

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.139504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0448e560-3b8f-4cbd-b55b-372857ddb2b0 · outbound

This paper cites ColaVLA: Leveraging cognitive latent reasoning for hierarchical parallel trajectory planning in autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning ColaVLA: Leveraging cognitive latent reasoning for hierarchical parallel trajectory planning in autonomous driving

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.525981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ce923690-5aaf-467e-ac2f-264e34e7bc80 · outbound

This paper cites Multi-modal fusion transformer for end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Multi-modal fusion transformer for end-to-end autonomous driving

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.148436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a866d89e-0557-4c40-bdbd-0ee324810524 · outbound

This paper cites Diffusion Policy Policy Optimization.

EponaV2: Driving World Model with Comprehensive Future Reasoning Diffusion Policy Policy Optimization

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-16T08:48:15.161771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0ac4bce4-36d3-420c-8511-7741aef28d45 · outbound

This paper cites SVG- T2I: Scaling up text-to-image latent diffusion model without variational autoencoder.

EponaV2: Driving World Model with Comprehensive Future Reasoning SVG- T2I: Scaling up text-to-image latent diffusion model without variational autoencoder

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.677679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72972041-0f39-448b-a0cd-0a92f91f8129 · outbound

This paper cites Latent diffusion model without variational autoencoder.

EponaV2: Driving World Model with Comprehensive Future Reasoning Latent diffusion model without variational autoencoder

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.628124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4bce54b4-283b-4444-9efa-97c5b8abed7b · outbound

This paper cites DriveLM: Driving with Graph Visual Question Answering.

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveLM: Driving with Graph Visual Question Answering

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.561817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2903c575-a36c-48bc-8b5d-27343f62c065 · outbound

This paper cites DINOv3.

EponaV2: Driving World Model with Comprehensive Future Reasoning DINOv3

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.701534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation de8ce91e-ba23-4ae1-a255-4d2e0c90c4a0 · outbound

This paper cites Denoising Diffusion Implicit Models.

EponaV2: Driving World Model with Comprehensive Future Reasoning Denoising Diffusion Implicit Models

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.613119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5e2ff852-8424-4d1f-909d-357b8ce2d66e · outbound

This paper cites Don’t shake the wheel: Momentum-aware planning in end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Don’t shake the wheel: Momentum-aware planning in end-to-end autonomous driving

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.295958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0bdaa065-a586-49b0-803a-eef8a8c09a76 · outbound

This paper cites DriveMamba: Task-centric scalable state space model for efficient end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveMamba: Task-centric scalable state space model for efficient end-to-end autonomous driving

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.166769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 467eda4a-4dc1-4500-b74b-30aa949ff13c · outbound

This paper cites SparseDrive: End- to-end autonomous driving via sparse scene representation.

EponaV2: Driving World Model with Comprehensive Future Reasoning SparseDrive: End- to-end autonomous driving via sparse scene representation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.218673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 819bc156-4326-4e68-940b-8bb846abd852 · outbound

This paper cites Latent Chain-of-Thought World Modeling for End-to-End Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Latent Chain-of-Thought World Modeling for End-to-End Driving

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.641555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation eaad2e8b-7857-44da-ba24-fc3a7ef07a69 · outbound

This paper cites CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention.

EponaV2: Driving World Model with Comprehensive Future Reasoning CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.690676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 64ab177b-e249-4d5e-91b6-f2ba36548d5d · outbound

This paper cites HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder.

EponaV2: Driving World Model with Comprehensive Future Reasoning HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.791752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b65d94df-4cf5-4cac-ac1f-fbba59d8af89 · outbound

This paper cites SimScale: Learning to Drive via Real-World Simulation at Scale.

EponaV2: Driving World Model with Comprehensive Future Reasoning SimScale: Learning to Drive via Real-World Simulation at Scale

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.803992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ee5135ea-17e0-4fc0-8378-59bb10a87b77 · outbound

This paper cites DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models.

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.766696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 132ac404-275e-44ae-ba58-625925dec7f2 · outbound

This paper cites arXiv preprint arXiv:2602.20794 (2026) 10.

EponaV2: Driving World Model with Comprehensive Future Reasoning arXiv preprint arXiv:2602.20794 (2026) 10

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.798130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6785a478-a0b1-435a-9e43-c66f7ad19eda · outbound

This paper cites arXiv preprint arXiv:2602.20060 (2026) 2, 3, 4, 10, 11, 12, 20.

EponaV2: Driving World Model with Comprehensive Future Reasoning arXiv preprint arXiv:2602.20060 (2026) 2, 3, 4, 10, 11, 12, 20

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:15:02.620790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0075bc6d-b026-4ce1-96b6-bc84b72ebe05 · outbound

This paper cites DriveDreamer: Towards real-world-drive world models for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveDreamer: Towards real-world-drive world models for autonomous driving

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.305135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5a369f61-abdf-4f1a-9241-4bf774540371 · outbound

This paper cites Unifying language-action understanding and generation for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Unifying language-action understanding and generation for autonomous driving

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.579797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5bda2089-fd48-483b-9c49-b3b519d8bc53 · outbound

This paper cites Unified Vision-Language-Action Model.

EponaV2: Driving World Model with Comprehensive Future Reasoning Unified Vision-Language-Action Model

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.541356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6bc764e1-0227-4433-bece-ca844b2cc056 · outbound

This paper cites Metric3D: Towards zero-shot metric 3D prediction from a single image.

EponaV2: Driving World Model with Comprehensive Future Reasoning Metric3D: Towards zero-shot metric 3D prediction from a single image

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.187337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e6a6e4bf-9b15-45ab-a410-b4c048937ec9 · outbound

This paper cites DriveLaW:Unifying Planning and Video Generation in a Latent Driving World.

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

Reference 77

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.435349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 42f64b1d-2ae0-422b-890a-de8e5fccdfc0 · outbound

This paper cites GoalFlow: Goal-driven flow matching for multimodal trajectories generation in end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning GoalFlow: Goal-driven flow matching for multimodal trajectories generation in end-to-end autonomous driving

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.300723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 82999c22-ae68-481f-8c71-dbb92f2a51a6 · outbound

This paper cites WAM-Flow: Parallel coarse-to-fine motion planning via discrete flow matching for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning WAM-Flow: Parallel coarse-to-fine motion planning via discrete flow matching for autonomous driving

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.291371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9cbd84a4-c3fd-4802-b775-a311fa006205 · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

EponaV2: Driving World Model with Comprehensive Future Reasoning Depth anything: Unleashing the power of large-scale unlabeled data

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.283141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 175f358b-a063-4501-9108-45b5e85e6c06 · outbound

This paper cites Depth Anything V2.

EponaV2: Driving World Model with Comprehensive Future Reasoning Depth Anything V2

Reference 81

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.597514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0988589c-67c2-445b-b757-24019f021e89 · outbound

This paper cites DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:05:28.917220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4c8f4fd6-7265-42e4-9cbf-594e8dcb623a · outbound

This paper cites Raw2Drive: Reinforce- ment learning with aligned world models for end-to-end autonomous driving (in CARLA v2).

EponaV2: Driving World Model with Comprehensive Future Reasoning Raw2Drive: Reinforce- ment learning with aligned world models for end-to-end autonomous driving (in CARLA v2)

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.243450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 42e5e94b-e9ac-4934-8cc1-0b1f983602f6 · outbound

This paper cites AutoDrive-P3: Unified chain of perception-prediction-planning thought via reinforcement fine-tuning.

EponaV2: Driving World Model with Comprehensive Future Reasoning AutoDrive-P3: Unified chain of perception-prediction-planning thought via reinforcement fine-tuning

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.509386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b3bb734c-3e7a-4fc7-a47a-2f7bd272a1b3 · outbound

This paper cites DistillDrive: End-to-end multi-mode autonomous driving distillation by isomorphic hetero-source planning model.

EponaV2: Driving World Model with Comprehensive Future Reasoning DistillDrive: End-to-end multi-mode autonomous driving distillation by isomorphic hetero-source planning model

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.234909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dc8142e5-281a-4585-ae8a-6816b6b8db6c · outbound

This paper cites AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving

Reference 86

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.477460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6470fb99-c241-4d6f-afd9-4df0767cfb0f · outbound

This paper cites FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:19:43.280111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 42b9ea81-1c70-4ab6-90d5-09b70ebd0d2e · outbound

This paper cites Scaling vision transformers.

EponaV2: Driving World Model with Comprehensive Future Reasoning Scaling vision transformers

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.227885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4f8861a0-d4fd-43f1-8711-6472d9052c1c · outbound

This paper cites Bridging past and future: End-to-end autonomous driving with historical prediction and planning.

EponaV2: Driving World Model with Comprehensive Future Reasoning Bridging past and future: End-to-end autonomous driving with historical prediction and planning

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.204338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5f3e72a9-917b-4c1d-a043-8324d8e43c55 · outbound

This paper cites Future-aware end-to-end driving: Bidirectional modeling of trajectory planning and scene evolution.

EponaV2: Driving World Model with Comprehensive Future Reasoning Future-aware end-to-end driving: Bidirectional modeling of trajectory planning and scene evolution

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.144241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 63a497bd-3404-4ce7-a358-f459826a5135 · outbound

This paper cites ResWorld: Temporal residual world model for end-to-end autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning ResWorld: Temporal residual world model for end-to-end autonomous driving

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.162285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7b2423fa-32d4-44e1-baa5-f97bf2dd6598 · outbound

This paper cites Epona: Autoregressive diffusion world model for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning Epona: Autoregressive diffusion world model for autonomous driving

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.195151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 212fa04f-ad10-4fff-8ae8-9db318755c21 · outbound

This paper cites MindDriver: Introducing progressive multimodal reasoning for autonomous driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning MindDriver: Introducing progressive multimodal reasoning for autonomous driving

Reference 93

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.469903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ce128f8f-1ae9-4983-b5fb-210e354bc0a0 · outbound

This paper cites DiffE2E: Rethinking end-to-end driving with a hybrid diffusion-regression-classification policy.

EponaV2: Driving World Model with Comprehensive Future Reasoning DiffE2E: Rethinking end-to-end driving with a hybrid diffusion-regression-classification policy

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.156949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 39aef02e-ad0f-4a68-a706-8ca05aae7abc · outbound

This paper cites From Forecasting to Planning: Policy world model for collaborative state-action prediction.

EponaV2: Driving World Model with Comprehensive Future Reasoning From Forecasting to Planning: Policy world model for collaborative state-action prediction

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.183150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b9ca94b-4aab-49e3-ba25-d20da7e91f87 · outbound

This paper cites World4Drive: End-to-end autonomous driving via intention-aware physical latent world model.

EponaV2: Driving World Model with Comprehensive Future Reasoning World4Drive: End-to-end autonomous driving via intention-aware physical latent world model

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T05:15:04.199377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3650c40f-bf8c-4ec5-aa3d-fb1e006366ab · outbound

This paper cites Resad: Normalized residual trajectory modeling for end-to-end autonomous driving.arXiv preprint arXiv:2510.08562.

EponaV2: Driving World Model with Comprehensive Future Reasoning Resad: Normalized residual trajectory modeling for end-to-end autonomous driving.arXiv preprint arXiv:2510.08562

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.552451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f31cd2d8-5eee-4eef-af8f-d20a900ef559 · outbound

This paper cites AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning.

EponaV2: Driving World Model with Comprehensive Future Reasoning AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning

Reference 98

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:15:02.588641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 922f9931-29b8-4d9c-9ead-f56bcf6b8392 · outbound

This paper cites re- gions important for driving.

EponaV2: Driving World Model with Comprehensive Future Reasoning re- gions important for driving

Reference 99

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T05:15:02.715198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers