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Paper Citation Record · LEDGER

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving

As of 7 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2607.04812.

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

pith.paper-citation-record.v1
2607.04812 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T13:09:16.091741Z

measured 55 of 55 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

55 of 55 outbound references displayed

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Outbound references

Observation 3921291e-4caa-4e84-b5c8-489c48bd2c8c · outbound

This paper cites Intentnet: Learning to predict intention from raw sensor data,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Intentnet: Learning to predict intention from raw sensor data,

Reference 1

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Observation e66280e1-5c93-4b6d-80ac-7c8d04062adc · outbound

This paper cites MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction

Reference 2

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Observation 53338978-2e88-4a97-8549-b3db41fb7110 · outbound

This paper cites Efficient baselines for motion prediction in autonomous driving,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Efficient baselines for motion prediction in autonomous driving,

Reference 3

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Observation 61cc1232-bf73-4d86-bef7-d870ec9fd81a · outbound

This paper cites FIERY: Future instance segmentation in bird’s-eye view from surround monocular cameras,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving FIERY: Future instance segmentation in bird’s-eye view from surround monocular cameras,

Reference 4

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Observation 2734260b-57c0-4945-8996-f088bacb003f · outbound

This paper cites Powerbev: A powerful yet lightweight framework for instance prediction in bird’s-eye view,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Powerbev: A powerful yet lightweight framework for instance prediction in bird’s-eye view,

Reference 5

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Observation 709f2c87-d141-407b-9f10-14f0f507d032 · outbound

This paper cites Fast and efficient transformer- based method for bird’s eye view instance prediction,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Fast and efficient transformer- based method for bird’s eye view instance prediction,

Reference 6

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Observation 8fb7bc6e-0006-4e34-b8b8-e1b5d61f965d · outbound

This paper cites Learning transferable visual models from natural language supervision,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Learning transferable visual models from natural language supervision,

Reference 7

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Observation 8ba7f202-ceaf-40de-a416-636d5055e4ec · outbound

This paper cites Segment anything,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Segment anything,

Reference 8

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Observation 24bb9ffc-2a5d-4111-9562-02feec16e6db · outbound

This paper cites Pop-3d: Open-vocabulary 3d occupancy prediction from images,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Pop-3d: Open-vocabulary 3d occupancy prediction from images,

Reference 9

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Observation 0a82a82b-2dbc-491f-aa48-3b322082a27c · outbound

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

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving nuScenes: A multimodal dataset for autonomous driving

Reference 10

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Observation 0d2b35cb-3803-4f96-8640-ebafca303d44 · outbound

This paper cites Scaling up visual and vision-language representation learning with noisy text supervision,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Scaling up visual and vision-language representation learning with noisy text supervision,

Reference 11

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Observation 7f557005-6f63-4a70-8a5c-d0dcd2bea5db · outbound

This paper cites Sigmoid loss for language image pre-training,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Sigmoid loss for language image pre-training,

Reference 12

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Observation 74775c49-3507-45e3-ab64-5161072d25fb · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 13

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Observation d84e936c-4ab5-4f6b-944a-5ab7f77cc296 · outbound

This paper cites Maskclip: Masked self-distillation advances contrastive language-image pretraining,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Maskclip: Masked self-distillation advances contrastive language-image pretraining,

Reference 14

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Observation 6cbdde72-e9e7-413b-801f-24cf06d0d4c8 · outbound

This paper cites Zegclip: Towards adapting clip for zero-shot semantic segmentation,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Zegclip: Towards adapting clip for zero-shot semantic segmentation,

Reference 15

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Observation 4f2bc3d3-b42c-4fbf-9c84-4ebb9c8526c8 · outbound

This paper cites Emerging properties in self-supervised vision transformers,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Emerging properties in self-supervised vision transformers,

Reference 16

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Observation e670de08-2844-4363-b910-bf956e78cae9 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving DINOv2: Learning Robust Visual Features without Supervision

Reference 17

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Observation 680bd8ac-e051-44d2-b0d3-9ff091083a12 · outbound

This paper cites DINOv3.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving DINOv3

Reference 18

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Observation e3d73cad-fb8c-470b-bd91-d24e97297041 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving SAM 2: Segment Anything in Images and Videos

Reference 19

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Observation dc6bf809-671c-4b02-8de0-ebdfcff047c1 · outbound

This paper cites SAM 3: Segment Anything with Concepts.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving SAM 3: Segment Anything with Concepts

Reference 20

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Observation c9c97a69-7ed4-4510-a386-2defd39581cf · outbound

This paper cites Visual instruction tuning,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Visual instruction tuning,

Reference 21

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Observation 4603b61e-b8c0-42a3-a6c0-b537cabd0cda · outbound

This paper cites Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking

Reference 22

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Observation 95c717bc-5e48-4cbb-9cf7-b96077342bae · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 23

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Observation 5dd3991a-3ea1-44e4-a132-2826b675b821 · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 24

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Observation cd5a015d-154a-4491-b36b-8f3b51b74012 · outbound

This paper cites Openworld- sam: Extending sam2 for universal image segmentation with language prompts,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Openworld- sam: Extending sam2 for universal image segmentation with language prompts,

Reference 25

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Observation ae0ec5f4-c605-4f68-bed1-1c55a22e3af6 · outbound

This paper cites Lposs: Label propagation over patches and pixels for open-vocabulary semantic segmentation,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Lposs: Label propagation over patches and pixels for open-vocabulary semantic segmentation,

Reference 26

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Observation 6d11d4e9-86cd-47cb-940a-72b87e18d0af · outbound

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

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Tri-perspective view for vision-based 3d semantic occupancy prediction,

Reference 27

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Observation 2f537d4e-49e0-4a39-b652-d70b0a77a5f9 · outbound

This paper cites Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction,

Reference 28

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Observation d271e12f-b085-4d5c-8765-f73768221851 · outbound

This paper cites OVO: Open-Vocabulary Occupancy.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving OVO: Open-Vocabulary Occupancy

Reference 29

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Observation fa287471-8b59-4449-a89a-a10f6b183dff · outbound

This paper cites Talk2bev: Language-enhanced bird’s-eye view maps for autonomous driving,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Talk2bev: Language-enhanced bird’s-eye view maps for autonomous driving,

Reference 30

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Observation 7508fd87-3572-45b1-984b-c7c6831cdf9f · outbound

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

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Bevformer: learning bird’s-eye-view representation from lidar- camera via spatiotemporal transformers,

Reference 31

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Observation 49d1b76b-1bda-4ef2-bdbb-9fbfba627d9f · outbound

This paper cites Bevsegformer: Bird’s eye view semantic segmentation from arbitrary camera rigs,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Bevsegformer: Bird’s eye view semantic segmentation from arbitrary camera rigs,

Reference 32

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Observation 0210e984-dcb2-4473-8cad-a42bdbb1eb3d · outbound

This paper cites Gaussiancar: Gaussian splatting for efficient camera-radar fusion,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Gaussiancar: Gaussian splatting for efficient camera-radar fusion,

Reference 33

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Observation c7def5a8-c9b9-4ade-a357-67d9b656b04e · outbound

This paper cites Pointbev: A sparse approach for bev predictions,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Pointbev: A sparse approach for bev predictions,

Reference 34

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Observation f81a2f64-c9f5-4749-aadc-015305f294c2 · outbound

This paper cites Fb- bev: Bev representation from forward-backward view transformations,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Fb- bev: Bev representation from forward-backward view transformations,

Reference 35

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Observation d78088c5-e12f-4a6d-9cea-82555afdc2af · outbound

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

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Is ego status all you need for open-loop end-to-end autonomous driving?

Reference 36

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:2420b5d973bb8c2099491cdb4e4fbd15dd99c4a36d9bd435d8e967f2407efc72

Observation 0fcdcda7-f56a-4aba-8a53-588e19ab186b · outbound

This paper cites Lmdrive: Closed-loop end-to-end driving with large language models,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Lmdrive: Closed-loop end-to-end driving with large language models,

Reference 37

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:57fcc41f6b7273730e9cdef3b5abfdde97b12af52ad21382240f83d73fdb1383

Observation d78f862e-e468-49b8-a8a9-7aec7fb333e9 · outbound

This paper cites BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving

Reference 38

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:0360866ef5dac1b576a8e05f36c7c9c13ccd1ff0a4c8b8a1fb965e89c07a9adc

Observation 71531627-045e-4352-851c-aa9100e5aafe · outbound

This paper cites Safety-enhanced autonomous driving using interpretable sensor fusion transformer,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Safety-enhanced autonomous driving using interpretable sensor fusion transformer,

Reference 39

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:d6db67da706e6c3573e6a5f47e917e1c02fe853da579d159071a363fb06feeae

Observation 3d484879-c3e3-4640-9468-fa183e86bafd · outbound

This paper cites Reasonnet: End-to-end driving with temporal and global reasoning,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Reasonnet: End-to-end driving with temporal and global reasoning,

Reference 40

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:6ad1b4aa4be8906f10d49e877ecb536461f63e867575e28297c10377f4f3ef7d

Observation 4dc0a4f8-3440-4985-8760-f612a015dfd1 · outbound

This paper cites Vectornet: Encoding hd maps and agent dynamics from vectorized representation,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Vectornet: Encoding hd maps and agent dynamics from vectorized representation,

Reference 41

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:c1faff761a5fbec78eb534f45c635f5ad64b0586999fa8fc5b3815ca8f2465bf

Observation 7af982be-9dee-4278-934d-7590c2c96c22 · outbound

This paper cites Learning lane graph representations for motion forecasting,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Learning lane graph representations for motion forecasting,

Reference 42

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:f97c9c4a4b297d493b378b775b44b073f07ee22ce7f583270724efde9232ab7e

Observation bfc5475a-f142-43d3-ab72-e7b4b89ba658 · outbound

This paper cites Scene Transformer: A unified architecture for predicting multiple agent trajectories.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Scene Transformer: A unified architecture for predicting multiple agent trajectories

Reference 43

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:e00a845c8d07c91c0f9c4667445fb1fdf34fc3e9d4c10c55cd2c36788eac8262

Observation 07526994-2c71-4a67-8023-37a42a7174fd · outbound

This paper cites Hivt: Hierarchical vector transformer for multi-agent motion prediction,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Hivt: Hierarchical vector transformer for multi-agent motion prediction,

Reference 44

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:20a64dc6eaa768bf9d8ccc9fac4e3ae7ab892dbac895d767b0efc49981d731e8

Observation 3864c6e5-ed82-47c0-8a4e-d2827e2ae8aa · outbound

This paper cites Motion transformer with global intention localization and local movement refinement,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Motion transformer with global intention localization and local movement refinement,

Reference 45

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:b6157d6cb5c0f7a87f46ff14d1be382b0e909e425febef2662a820f1897c21c1

Observation a95697ae-e0cf-480a-8bf5-5ff9d0feca2f · outbound

This paper cites Query-centric trajectory prediction,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Query-centric trajectory prediction,

Reference 46

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:8af3fec2a26592ff69525e2f02d4614cb5a409ec44423f69a5b5a22d25f6dc42

Observation ad10ffbe-2458-40cd-8830-15197e6f4eb4 · outbound

This paper cites Vip3d: End-to-end visual trajectory prediction via 3d agent queries,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Vip3d: End-to-end visual trajectory prediction via 3d agent queries,

Reference 47

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:3a1a13e8f509ed119fd64201352eaa88877509d9813a355056d51a9474b9c8fa

Observation 8568be9b-3466-4aa9-8321-1af372421a78 · outbound

This paper cites Detra: A unified model for object detection and trajectory forecasting,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Detra: A unified model for object detection and trajectory forecasting,

Reference 48

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:fa3e5e3f64645e3c81bfaf1acb703c290c2fab7fb98b819bf4cc7cff10285ef0

Observation e89f1159-f755-423c-bc49-539ce8763614 · outbound

This paper cites BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

Reference 49

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:d917cdacb41af6dd4fabbfc61eb049d7d1d70fa9909c923b34698fcfedf39f24

Observation c476862e-1f45-4998-9102-d6fe456a7cef · outbound

This paper cites Stretchbev: Stretching future instance prediction spatially and temporally,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Stretchbev: Stretching future instance prediction spatially and temporally,

Reference 50

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:d9f0734542d61b3ab02d63d167eb40b21ba0e143936c49a747d75e60cf44c11d

Observation ec62347d-6be3-4cc0-9f28-9e7a1f2ce359 · outbound

This paper cites St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,

Reference 51

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:e5ea20115910fc3df9e47f44e4ac30a30539702e2dcc771a02650c3bdd92f841

Observation b0427ed1-77a7-460b-b9a0-0698cf148789 · outbound

This paper cites Dmp: Difference-guided motion prediction for vision-centric autonomous driving,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Dmp: Difference-guided motion prediction for vision-centric autonomous driving,

Reference 52

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:ebbb83db37e5fd70298137440f702e0571ca156dfe0ed5815f55c4683f120cc2

Observation 60fbeb17-931b-4f24-af3b-df011f6dc5d4 · outbound

This paper cites BEVPredFormer: Spatio-temporal Attention for BEV Instance Prediction in Autonomous Driving.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving BEVPredFormer: Spatio-temporal Attention for BEV Instance Prediction in Autonomous Driving

Reference 53

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:48af3c661da00ccea50530d3009b066958131ebef340ad5999f6131ae9de7fff

Observation 4c762c00-d2a9-4bef-a0fd-1275d08116a5 · outbound

This paper cites Efficientvit: Memory efficient vision transformer with cascaded group attention,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving Efficientvit: Memory efficient vision transformer with cascaded group attention,

Reference 54

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:5c2ae24e6ae95535bcb809a5aa58c01e396f09ea3a0356de0998a08663eadb35

Observation baab87fe-4eb1-4308-9e39-0041a567294b · outbound

This paper cites St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,.

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,

Reference 55

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source=pdf_text observed=2026-07-11T13:09:16.091741Z digest=sha256:91f3439c8ffdbd52f3dc9c562d89e3a6f784988bceb4b84f95c6809311168d94

Pith citing papers

No inbound Pith citation observations are available.