LiAuto-GeoX: Efficient Grounded Driving Transformer | Paper Citation Record

Observation d736fe20-bc98-4447-9d50-86e52a24a5eb · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer nuscenes: A multimodal dataset for autonomous driving

Reference 1

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Observation 69903d47-43d4-4b7f-b6c7-a58c2c51f8bd · outbound

This paper cites Vadv2: End-to-end vectorized autonomous driving via probabilistic planning.ICLR, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Vadv2: End-to-end vectorized autonomous driving via probabilistic planning.ICLR, 2026

Reference 2

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Observation 74dc6935-0edb-4159-ab1a-7a22ab9d56d9 · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer Drivinggpt: Unifying driving world modeling and planning with multi-modal autoregressive transformers

Reference 3

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Observation bf0be160-4abc-4b50-9577-ef5159c29199 · outbound

This paper cites Bevdistill: Cross-modal bev distillation for multi-view 3d object detection.arXiv, 2022.

LiAuto-GeoX: Efficient Grounded Driving Transformer Bevdistill: Cross-modal bev distillation for multi-view 3d object detection.arXiv, 2022

Reference 4

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Observation f565b0fe-2bd8-4c4c-9b75-181f51867abd · outbound

This paper cites Openscene: The largest up-to-date 3d occupancy prediction bench- mark in autonomous driving.

LiAuto-GeoX: Efficient Grounded Driving Transformer Openscene: The largest up-to-date 3d occupancy prediction bench- mark in autonomous driving

Reference 5

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Observation 9f304731-6b74-46c2-8138-bc245cea11e2 · outbound

This paper cites Sparseworld: A flexible, adaptive, and efficient 4d occupancy world model powered by sparse and dynamic queries.

LiAuto-GeoX: Efficient Grounded Driving Transformer Sparseworld: A flexible, adaptive, and efficient 4d occupancy world model powered by sparse and dynamic queries

Reference 6

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Observation 54ccc197-7d4d-468c-92a8-4304da66bf00 · outbound

This paper cites Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking.NeurIPS, 37:28706–28719, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking.NeurIPS, 37:28706–28719, 2024

Reference 7

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Observation 14fe80e6-8f6a-42dc-b2d1-6f4ce008409b · outbound

This paper cites Sparseworld-tc: Trajectory-conditioned sparse occupancy world model.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Sparseworld-tc: Trajectory-conditioned sparse occupancy world model.arXiv, 2025

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 71bdc983-2a0a-4096-ac63-cfb84d7a6f32 · outbound

This paper cites Artemis: Autoregressive end-to-end trajectory planning with mixture of experts for autonomous driving.IEEE RAL, 11(1):226–233, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Artemis: Autoregressive end-to-end trajectory planning with mixture of experts for autonomous driving.IEEE RAL, 11(1):226–233, 2025

Reference 9

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Observation 83fc67ee-1daa-4b23-b449-9eca277cbe0a · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

LiAuto-GeoX: Efficient Grounded Driving Transformer Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 10

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Observation fa51b45a-f719-402c-a2ff-bc8e2c1fd965 · outbound

This paper cites Dome: Taming diffusion model into high-fidelity controllable occupancy world model.arXiv, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer Dome: Taming diffusion model into high-fidelity controllable occupancy world model.arXiv, 2024

Reference 11

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Observation a5b48923-cf71-4813-915c-084624121d81 · outbound

This paper cites 3d packing for self-supervised monocular depth estimation.

LiAuto-GeoX: Efficient Grounded Driving Transformer 3d packing for self-supervised monocular depth estimation

Reference 12

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Observation 0e68335f-d074-4eca-be35-9a59b08017d7 · outbound

This paper cites Distilling the knowledge in a neural network.

LiAuto-GeoX: Efficient Grounded Driving Transformer Distilling the knowledge in a neural network

Reference 13

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Observation 6efb426f-aac0-407f-bda0-22410045d4a0 · outbound

This paper cites Lrm: Large reconstruction model for single image to 3d.

LiAuto-GeoX: Efficient Grounded Driving Transformer Lrm: Large reconstruction model for single image to 3d

Reference 14

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Observation f8043ab9-76d1-43f4-9983-cd94f3595d39 · outbound

This paper cites One thousand and one hours: Self-driving motion prediction dataset.

LiAuto-GeoX: Efficient Grounded Driving Transformer One thousand and one hours: Self-driving motion prediction dataset

Reference 15

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Observation 0b99c806-23e7-4f0e-a58c-8497e355ed18 · outbound

This paper cites Planning-oriented autonomous driving.

LiAuto-GeoX: Efficient Grounded Driving Transformer Planning-oriented autonomous driving

Reference 16

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Observation 71eac3da-3b37-4d01-ade1-d52bb621f10e · outbound

This paper cites Bevdet4d: Exploit temporal cues in multi-camera 3d object detection.arXiv, 2022.

LiAuto-GeoX: Efficient Grounded Driving Transformer Bevdet4d: Exploit temporal cues in multi-camera 3d object detection.arXiv, 2022

Reference 17

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Observation 0fe2eec4-6aee-49ca-bce0-9cba7763337e · outbound

This paper cites Bevdet: High-performance multi-camera 3d object detection in bird-eye-view.arXiv, 2021.

LiAuto-GeoX: Efficient Grounded Driving Transformer Bevdet: High-performance multi-camera 3d object detection in bird-eye-view.arXiv, 2021

Reference 18

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Observation 05d02189-7914-4e0c-a0c6-6aacc69f7d0a · outbound

This paper cites Tig-bev: Multi-view bev 3d object detection via target inner-geometry learning.arXiv, 2022.

LiAuto-GeoX: Efficient Grounded Driving Transformer Tig-bev: Multi-view bev 3d object detection via target inner-geometry learning.arXiv, 2022

Reference 19

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Observation 2ebdf374-62ad-4f20-837b-09c80136a51d · outbound

This paper cites Tri-perspective view for vision-based 3d semantic occupancy prediction.

LiAuto-GeoX: Efficient Grounded Driving Transformer Tri-perspective view for vision-based 3d semantic occupancy prediction

Reference 20

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Observation 491761bb-e9d0-4fb9-a7d6-11533a625192 · outbound

This paper cites Occtens: 3d occupancy world model via temporal next-scale prediction.IEEE RAL, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Occtens: 3d occupancy world model via temporal next-scale prediction.IEEE RAL, 2026

Reference 21

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Observation b609beb9-3d3f-46b7-8893-76df5d8fc409 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.ACM Trans.

LiAuto-GeoX: Efficient Grounded Driving Transformer 3d gaussian splatting for real-time radiance field rendering.ACM Trans

Reference 22

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Observation cd1027b8-3b46-4b58-834e-75ef8c8e49a4 · outbound

This paper cites X3kd: Knowledge distillation across modal- ities, tasks and stages for multi-camera 3d object detection.

LiAuto-GeoX: Efficient Grounded Driving Transformer X3kd: Knowledge distillation across modal- ities, tasks and stages for multi-camera 3d object detection

Reference 23

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Observation 40c27cf7-8d71-415a-9369-601263a68574 · outbound

This paper cites Grounding image matching in 3d with mast3r.

LiAuto-GeoX: Efficient Grounded Driving Transformer Grounding image matching in 3d with mast3r

Reference 24

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Observation e72d43e5-b57b-4bbb-a443-023b5d48986e · outbound

This paper cites Semi-supervised vision-centric 3d occupancy world model for autonomous driving.

LiAuto-GeoX: Efficient Grounded Driving Transformer Semi-supervised vision-centric 3d occupancy world model for autonomous driving

Reference 25

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Observation e6b38abb-3af9-43ce-a7d5-a5197bdcf0a4 · outbound

This paper cites V oxformer: Sparse voxel transformer for camera-based 3d semantic scene completion.

LiAuto-GeoX: Efficient Grounded Driving Transformer V oxformer: Sparse voxel transformer for camera-based 3d semantic scene completion

Reference 26

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Observation 276e4ce2-5328-4d82-9a87-d2976f32a3e9 · outbound

This paper cites Enhancing end-to-end autonomous driving with latent world model.ICLR, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Enhancing end-to-end autonomous driving with latent world model.ICLR, 2025

Reference 27

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Observation a7b08df4-eea9-4914-8d80-4ad392f7a28e · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer End-to-end driving with online trajectory evaluation via bev world model

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation d08e538e-eb5e-4b2e-8383-ad40e374de15 · outbound

This paper cites Drivevla-w0: World models amplify data scaling law in autonomous driving.ICLR, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Drivevla-w0: World models amplify data scaling law in autonomous driving.ICLR, 2026

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 4cd346e2-56dd-48a5-833f-ef616b19fe77 · outbound

This paper cites Bevdepth: Acquisition of reliable depth for multi-view 3d object detection.

LiAuto-GeoX: Efficient Grounded Driving Transformer Bevdepth: Acquisition of reliable depth for multi-view 3d object detection

Reference 30

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Observation 4902e27b-658e-48ed-8a07-c6a62d30e99a · outbound

This paper cites Recogdrive: A reinforced cognitive framework for end-to-end autonomous driving.ICLR, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Recogdrive: A reinforced cognitive framework for end-to-end autonomous driving.ICLR, 2026

Reference 31

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Observation 5b5599e0-87bc-40a6-8d4e-4321102b0a44 · outbound

This paper cites Hydra-mdp: End-to-end multimodal planning with multi-target hydra-distillation.arXiv, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer Hydra-mdp: End-to-end multimodal planning with multi-target hydra-distillation.arXiv, 2024

Reference 32

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Observation a8fa39d3-5d34-42d1-9979-dd5a24be1ede · outbound

This paper cites Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers.IEEE TPAMI, 47(3):2020–2036, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers.IEEE TPAMI, 47(3):2020–2036, 2024

Reference 33

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Observation d66bab72-ddb7-47f9-9b7d-edc570d5d4bb · outbound

This paper cites Diffusion-based contextual reconstruction for point cloud segmentation with limited annotations.AAAI, 40(8): 6780–6788, Mar.

LiAuto-GeoX: Efficient Grounded Driving Transformer Diffusion-based contextual reconstruction for point cloud segmentation with limited annotations.AAAI, 40(8): 6780–6788, Mar

Reference 34

Resolution: verified exact; doi, observed 2026-06-28T02:41:31.847526Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4285a2d5-a1a9-4657-9385-04f3bf95ec43 · outbound

This paper cites Bevfusion: A simple and robust lidar-camera fusion framework.

LiAuto-GeoX: Efficient Grounded Driving Transformer Bevfusion: A simple and robust lidar-camera fusion framework

Reference 35

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Observation 1616dade-a5f1-47b1-b728-b6d9c527fae5 · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer Diffusiondrive: Truncated diffusion model for end-to-end autonomous driving

Reference 36

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Observation b71882a5-6368-451c-8877-c431ffca4ad0 · outbound

This paper cites I2- world: Intra-inter tokenization for efficient dynamic 4d scene forecasting.

LiAuto-GeoX: Efficient Grounded Driving Transformer I2- world: Intra-inter tokenization for efficient dynamic 4d scene forecasting

Reference 37

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Observation 4cdd5f6c-10e5-4dea-9716-9978eb004195 · outbound

This paper cites Adathinkdrive: Adaptive thinking via reinforcement learning for autonomous driving.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Adathinkdrive: Adaptive thinking via reinforcement learning for autonomous driving.arXiv, 2025

Reference 38

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Observation 395cdbe0-3f96-4e61-8fa4-30020b397978 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.CACM, 65 (1):99–106, 2021.

LiAuto-GeoX: Efficient Grounded Driving Transformer Nerf: Representing scenes as neural radiance fields for view synthesis.CACM, 65 (1):99–106, 2021

Reference 39

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Observation de3ecdb8-af8a-4aa7-bf3b-bab347678b93 · outbound

This paper cites Mast3r-slam: Real-time dense slam with 3d reconstruction priors.

LiAuto-GeoX: Efficient Grounded Driving Transformer Mast3r-slam: Real-time dense slam with 3d reconstruction priors

Reference 40

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Observation 4c75676d-cff7-4939-b902-45dbd9c291de · outbound

This paper cites Dinov2: Learning robust visual features without supervision.arXiv, 2023.

LiAuto-GeoX: Efficient Grounded Driving Transformer Dinov2: Learning robust visual features without supervision.arXiv, 2023

Reference 41

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Observation e8242a74-eaab-4199-b32a-369a8279351b · outbound

This paper cites Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision.

LiAuto-GeoX: Efficient Grounded Driving Transformer Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision

Reference 42

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Observation b83a4f0b-7f3b-4f7c-bd24-9830e7525bcd · outbound

This paper cites Omnivggt: Omni-modality driven visual geometry grounded transformer.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Omnivggt: Omni-modality driven visual geometry grounded transformer.arXiv, 2025

Reference 43

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Observation df33ef23-04d1-47ae-b3cf-4aafd4b385a3 · outbound

This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d.

LiAuto-GeoX: Efficient Grounded Driving Transformer Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation a74c6831-05bb-466a-b2fe-1aec63897bc5 · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer Multi-modal fusion transformer for end-to-end autonomous driving

Reference 45

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Observation ea0ee314-22b8-44fe-93be-c434e1649bf6 · outbound

This paper cites Fastvggt: Training-free acceleration of visual geometry transformer.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Fastvggt: Training-free acceleration of visual geometry transformer.arXiv, 2025

Reference 46

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Observation 7834f91a-424d-43f2-b169-134993622479 · outbound

This paper cites Come: Adding scene-centric forecasting control to occupancy world model.NeurIPS, 38:70–96, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Come: Adding scene-centric forecasting control to occupancy world model.NeurIPS, 38:70–96, 2026

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 7b598f1e-b03f-483c-be97-c06105b759cc · outbound

This paper cites Litevggt: Boosting vanilla vggt via geometry-aware cached token merging.

LiAuto-GeoX: Efficient Grounded Driving Transformer Litevggt: Boosting vanilla vggt via geometry-aware cached token merging

Reference 48

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Observation df328570-598d-44bf-b043-06dc32e399d7 · outbound

This paper cites Drivelm: Driving with graph visual question answering.

LiAuto-GeoX: Efficient Grounded Driving Transformer Drivelm: Driving with graph visual question answering

Reference 49

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Observation f4fa47b6-1560-40fd-904e-953f7af1b4ec · outbound

This paper cites Training very deep networks.

LiAuto-GeoX: Efficient Grounded Driving Transformer Training very deep networks

Reference 50

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Observation 2b92354b-ddb5-45f8-b3ed-cd8a1d0a083d · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

LiAuto-GeoX: Efficient Grounded Driving Transformer Scalability in perception for autonomous driving: Waymo open dataset

Reference 51

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Observation 537bebac-5e06-4fb7-8053-35946ff84701 · outbound

This paper cites Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.NeurIPS, 36:64318–64330, 2023.

LiAuto-GeoX: Efficient Grounded Driving Transformer Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving.NeurIPS, 36:64318–64330, 2023

Reference 52

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Observation 18d167b9-dc02-46da-9663-ff6b3e532573 · outbound

This paper cites Drivevlm: The convergence of autonomous driving and large vision-language models.arXiv, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer Drivevlm: The convergence of autonomous driving and large vision-language models.arXiv, 2024

Reference 53

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Observation 14723948-bdb5-41ae-9423-98dbe1e3f4a0 · outbound

This paper cites Least-squares estimation of transformation parameters between two point patterns.IEEE TPAMI, 13(4):376–380, 1991.

LiAuto-GeoX: Efficient Grounded Driving Transformer Least-squares estimation of transformation parameters between two point patterns.IEEE TPAMI, 13(4):376–380, 1991

Reference 54

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Observation 05e95815-16ad-4208-9176-b1f9980faed2 · outbound

This paper cites Vggt: Visual geometry grounded transformer.

LiAuto-GeoX: Efficient Grounded Driving Transformer Vggt: Visual geometry grounded transformer

Reference 55

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 24055aa1-47d9-42c0-ac50-f0363e0edfa8 · outbound

This paper cites Regularizing nighttime weirdness: Efficient self-supervised monocular depth estimation in the dark.

LiAuto-GeoX: Efficient Grounded Driving Transformer Regularizing nighttime weirdness: Efficient self-supervised monocular depth estimation in the dark

Reference 56

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 8e084a06-db21-4f47-825e-5ea9af8599cf · outbound

This paper cites Continuous 3d perception model with persistent state.

LiAuto-GeoX: Efficient Grounded Driving Transformer Continuous 3d perception model with persistent state

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 6d4ab06f-999b-407d-bedb-d75edcc9c558 · outbound

This paper cites Dust3r: Geometric 3d vision made easy.

LiAuto-GeoX: Efficient Grounded Driving Transformer Dust3r: Geometric 3d vision made easy

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation c927d161-06fd-4036-b618-fe249a5efe9d · outbound

This paper cites Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception.

LiAuto-GeoX: Efficient Grounded Driving Transformer Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception

Reference 59

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 43092c7a-6530-42b0-a4d7-b9066636e81f · outbound

This paper cites pi3: Permutation-equivariant visual geometry learning.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer pi3: Permutation-equivariant visual geometry learning.arXiv, 2025

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 26161b7b-d1eb-4832-8201-02858a5366d1 · outbound

This paper cites Distillbev: Boosting multi-camera 3d object detection with cross-modal knowledge distillation.

LiAuto-GeoX: Efficient Grounded Driving Transformer Distillbev: Boosting multi-camera 3d object detection with cross-modal knowledge distillation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation b4934d20-b097-4d29-9042-6a22480d5c9c · outbound

This paper cites Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving.

LiAuto-GeoX: Efficient Grounded Driving Transformer Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving

Reference 62

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation fb8b8107-f570-4ae3-b267-e75895b2ec01 · outbound

This paper cites Weathergen: A unified diverse weather generator for lidar point clouds via spider mamba diffusion.

LiAuto-GeoX: Efficient Grounded Driving Transformer Weathergen: A unified diverse weather generator for lidar point clouds via spider mamba diffusion

Reference 63

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation b610b7ae-a854-4c1f-943c-4170d7b4171b · outbound

This paper cites Gem: Generating lidar world model via deformable mamba.arXiv, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Gem: Generating lidar world model via deformable mamba.arXiv, 2026

Reference 64

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation a91c3581-9078-4ac4-8d4f-c2f989b1bf61 · outbound

This paper cites Distill to think, foresee to act: Cognitive-physical reinforcement learning for autonomous driving.arXiv, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Distill to think, foresee to act: Cognitive-physical reinforcement learning for autonomous driving.arXiv, 2026

Reference 65

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 1114843d-46ce-4add-ac8d-cb19c10e05b9 · outbound

This paper cites Drivelaw: Unifying planning and video generation in a latent driving world.CVPR, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Drivelaw: Unifying planning and video generation in a latent driving world.CVPR, 2026

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 8d130a23-69d1-4a69-93fd-68b9f749b0b9 · outbound

This paper cites Pandaset: Advanced sensor suite dataset for autonomous driving.

LiAuto-GeoX: Efficient Grounded Driving Transformer Pandaset: Advanced sensor suite dataset for autonomous driving

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 19034c1b-c174-4df0-89e8-3fddb29cbad0 · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer Goalflow: Goal-driven flow matching for multimodal trajectories generation in end-to-end autonomous driving

Reference 68

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 680d1da5-a1da-4010-b5e4-ef865bd21432 · outbound

This paper cites Delta- triplane transformers as occupancy world models.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Delta- triplane transformers as occupancy world models.arXiv, 2025

Reference 69

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 1a4911e6-8987-4f29-ab2e-d5238d93dd28 · outbound

This paper cites Occ-llm: Enhancing autonomous driving with occupancy-based large language models.

LiAuto-GeoX: Efficient Grounded Driving Transformer Occ-llm: Enhancing autonomous driving with occupancy-based large language models

Reference 70

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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Observation 2e281bf3-e528-476d-9b99-fbb250089064 · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer Depth anything: Unleashing the power of large-scale unlabeled data

Reference 71

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 2082148b-7a82-4e08-b4fa-c476b5204e19 · outbound

This paper cites Depth anything v2.NeurIPS, 37:21875–21911, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer Depth anything v2.NeurIPS, 37:21875–21911, 2024

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 9a3cd497-3b5b-4aea-9af7-434d6f12407a · outbound

This paper cites Masked generative distillation.

LiAuto-GeoX: Efficient Grounded Driving Transformer Masked generative distillation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation c28b5851-02ec-4556-b4e0-f0de45a1c4c9 · outbound

This paper cites Drivesuprim: Towards precise trajectory selection for end-to-end planning.

LiAuto-GeoX: Efficient Grounded Driving Transformer Drivesuprim: Towards precise trajectory selection for end-to-end planning

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 5a42c5f2-ccfa-4b3e-977b-e546355c5912 · outbound

This paper cites Mvsnet: Depth inference for unstructured multi-view stereo.

LiAuto-GeoX: Efficient Grounded Driving Transformer Mvsnet: Depth inference for unstructured multi-view stereo

Reference 75

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2a5dee9-da89-4b9d-8619-21eae83ef442 · outbound

This paper cites Flashocc: Fast and memory-efficient occupancy prediction via channel-to-height plugin.arXiv, 2023.

LiAuto-GeoX: Efficient Grounded Driving Transformer Flashocc: Fast and memory-efficient occupancy prediction via channel-to-height plugin.arXiv, 2023

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation a0334c93-add4-4ae0-8cc5-54fe8c53b74f · outbound

This paper cites Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer.arXiv, 2016.

LiAuto-GeoX: Efficient Grounded Driving Transformer Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer.arXiv, 2016

Reference 77

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 3fd2c200-6647-44b2-8d27-a3a7ede51795 · outbound

This paper cites An efficient occupancy world model via decoupled dynamic flow and image-assisted training.arXiv, 2024.

LiAuto-GeoX: Efficient Grounded Driving Transformer An efficient occupancy world model via decoupled dynamic flow and image-assisted training.arXiv, 2024

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 64a199f6-5c56-4e35-928a-50bbe6c9d077 · outbound

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

LiAuto-GeoX: Efficient Grounded Driving Transformer Epona: Autoregressive diffusion world model for autonomous driving

Reference 79

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 60f1f884-2bb9-4162-ad8c-1284832ba1ed · outbound

This paper cites Pointdistiller: Structured knowledge distillation towards efficient and compact 3d detection.

LiAuto-GeoX: Efficient Grounded Driving Transformer Pointdistiller: Structured knowledge distillation towards efficient and compact 3d detection

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94dbd7ab-64b5-44c3-bdca-55ada4c81d0e · outbound

This paper cites Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion.

LiAuto-GeoX: Efficient Grounded Driving Transformer Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion

Reference 81

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 92b0f049-6d67-4975-9f2b-07ed265d04b0 · outbound

This paper cites Decoupled knowledge distillation.

LiAuto-GeoX: Efficient Grounded Driving Transformer Decoupled knowledge distillation

Reference 82

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation cbe9dd5c-2a49-4ba3-a819-60a3be53aa4f · outbound

This paper cites From forecasting to planning: Policy world model for collaborative state-action prediction.NeurIPS, 38:134585–134611, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer From forecasting to planning: Policy world model for collaborative state-action prediction.NeurIPS, 38:134585–134611, 2026

Reference 83

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation cf074a29-c64c-4c8c-8ff1-f9f5b32fe95c · outbound

This paper cites Unidistill: A universal cross-modality knowledge distillation framework for 3d object detection in bird’s-eye view.

LiAuto-GeoX: Efficient Grounded Driving Transformer Unidistill: A universal cross-modality knowledge distillation framework for 3d object detection in bird’s-eye view

Reference 84

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7f05f4d-8439-481d-9680-18357b58259e · outbound

This paper cites Autovla: A vision-language-action model for end-to-end autonomous driving with adaptive reasoning and reinforcement fine-tuning.NeurIPS, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Autovla: A vision-language-action model for end-to-end autonomous driving with adaptive reasoning and reinforcement fine-tuning.NeurIPS, 2025

Reference 85

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

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Observation 3c166c52-89f7-4a9e-8136-915ca9da9cb4 · outbound

This paper cites Dvgt: Driving visual geometry transformer.arXiv, 2025.

LiAuto-GeoX: Efficient Grounded Driving Transformer Dvgt: Driving visual geometry transformer.arXiv, 2025

Reference 86

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25f796ab-4c83-42eb-a8dc-1c08ca833f32 · outbound

This paper cites Dvgt-2: Vision-geometry-action model for autonomous driving at scale.arXiv, 2026.

LiAuto-GeoX: Efficient Grounded Driving Transformer Dvgt-2: Vision-geometry-action model for autonomous driving at scale.arXiv, 2026

Reference 87

Resolution: unresolved; no resolver link, observed 2026-06-28T02:36:49.451297Z

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