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Paper Citation Record · LEDGER

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers

As of 9 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2512.15038.

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

pith.paper-citation-record.v1
2512.15038 v3

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T06:42:12.349268Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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.

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Reference resolution

43 of 43 outbound references displayed

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Outbound references

Observation fa2adc83-076e-4c58-9497-0f6b4fb194b1 · outbound

This paper cites Autonomous driving system: A comprehensive survey,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Autonomous driving system: A comprehensive survey,

Reference 1

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source=pdf_text observed=2026-08-04T06:42:08.196968Z digest=sha256:2c44a68856ca48dd2ee7804cfb78581a73766850ae7da70f7c56f120f389e502

Observation 114a21b1-b25c-49fb-b949-b673d6898114 · outbound

This paper cites End-to-end autonomous driving: Challenges and frontiers,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers End-to-end autonomous driving: Challenges and frontiers,

Reference 2

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Observation 1656e27e-96e2-49c0-9d04-73a14007c873 · outbound

This paper cites Genad: Generative end-to-end autonomous driving,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Genad: Generative end-to-end autonomous driving,

Reference 3

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Observation a2236027-f716-4932-8b38-40a618dec567 · outbound

This paper cites End- to-end autonomous driving through v2x cooperation,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers End- to-end autonomous driving through v2x cooperation,

Reference 4

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Observation b62cd66e-9860-4df5-b3dd-c0ca8dbd19fc · outbound

This paper cites A survey of optimization-based task and motion planning: From classical to learning approaches,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers A survey of optimization-based task and motion planning: From classical to learning approaches,

Reference 5

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Observation 4199b51a-a8df-4345-a750-6c7fe1ba4743 · outbound

This paper cites Real-time performance-focused localization techniques for autonomous vehicle: A review,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Real-time performance-focused localization techniques for autonomous vehicle: A review,

Reference 6

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source=pdf_text observed=2026-08-04T06:42:08.792351Z digest=sha256:8113afc4fe71fd92111962593024ea31a2bbf72b51ee415c63baf0c3300d538a

Observation 228bda8d-a05e-42f9-b324-4cc47d2d748e · outbound

This paper cites Unitr: A unified and efficient multi-modal transformer for bird’s-eye- view representation,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Unitr: A unified and efficient multi-modal transformer for bird’s-eye- view representation,

Reference 7

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source=pdf_text observed=2026-08-04T06:42:08.894636Z digest=sha256:066e8c9e6ec503fc31e17c64105cb3ee8fe6787fdaa3f70e27b511a2adc3d43e

Observation 4d079edf-3195-4747-9490-66c1e91d9f06 · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models

Reference 8

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Observation 969acd42-9607-4625-87fb-08f2a0dd3b5f · outbound

This paper cites Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding

Reference 9

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source=pdf_text observed=2026-08-04T06:42:09.060661Z digest=sha256:bf4fe42487cfa1d11353cab6d614f08a8d0a7e726ba5c0b48b9b59788870feb6

Observation 37197ade-4f8f-43b3-861b-6ff012c5b9da · outbound

This paper cites A safe motion planning and reliable control framework for autonomous vehicles,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers A safe motion planning and reliable control framework for autonomous vehicles,

Reference 10

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source=pdf_text observed=2026-08-04T06:42:09.232389Z digest=sha256:11cac1e01d175d78dd0bf83d5985dd1898eb7532ef2cdeaaf29da700ac0a0906

Observation e88e6fac-fab5-4207-a6e9-34a50a4b1fb0 · outbound

This paper cites Llm3: Large language model-based task and motion planning with motion failure reasoning,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Llm3: Large language model-based task and motion planning with motion failure reasoning,

Reference 11

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source=pdf_text observed=2026-08-04T06:42:09.303192Z digest=sha256:37b02a69d63b73eb07f24a9de084674512280d34e4ad4e2c7d21486837d6a947

Observation 7c8702ec-e9c1-4254-aa4b-0ea9bc3b51ea · outbound

This paper cites Motion planning for autonomous driving: The state of the art and future perspectives,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Motion planning for autonomous driving: The state of the art and future perspectives,

Reference 12

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source=pdf_text observed=2026-08-04T06:42:09.409365Z digest=sha256:d8f24f1646c2b554d5be91d0fc364f91815dea87136e2aa447e2cf0a8b5cdb1f

Observation 17eeec67-fdfe-45db-b44d-8b7539a413ef · outbound

This paper cites Recent advancements in end-to-end au- tonomous driving using deep learning: A survey,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Recent advancements in end-to-end au- tonomous driving using deep learning: A survey,

Reference 13

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source=pdf_text observed=2026-08-04T06:42:09.488397Z digest=sha256:64cbb6973a37707bd9d36b7c6851348110828c149e433d2f962ba27826b9d011

Observation ec4f6b3a-135b-4c74-b688-a001513e669b · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Is ego status all you need for open-loop end-to-end autonomous driving?

Reference 14

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source=pdf_text observed=2026-08-04T06:42:09.549765Z digest=sha256:c77c27996da83626b3db29b75203c8aef913a8b433d2463aab75ad1d6f8eb96d

Observation 3b1da4e5-eb3b-4b0e-8936-c9cd4566409a · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Transfuser: Imitation with transformer-based sensor fusion for au- tonomous driving,

Reference 15

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source=pdf_text observed=2026-08-04T06:42:09.668546Z digest=sha256:6fcf4a884b84c290fe3545a9e098ff033aa5ea0f1801fa719d6cafa234032150

Observation f7341712-c8f9-4176-9b1b-b62796c4c902 · outbound

This paper cites Planning-oriented autonomous driving,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Planning-oriented autonomous driving,

Reference 16

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source=pdf_text observed=2026-08-04T06:42:09.785763Z digest=sha256:e53dcc4c1104fd17effa34121135166c3377e48fc6358c11cb7252dad456342b

Observation bc158e81-0f93-4dce-b547-03651516e8d5 · outbound

This paper cites FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving

Reference 17

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source=pdf_text observed=2026-08-04T06:42:09.886345Z digest=sha256:31706dccb3fdcbe34d9676bc341d7a1b44792582da52d60be7b4b01fca65c882

Observation f8effc4d-582d-4ffa-a569-4bf721ddad3c · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Vad: Vectorized scene representation for efficient autonomous driving,

Reference 18

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source=pdf_text observed=2026-08-04T06:42:09.963221Z digest=sha256:16a876dd25bdb8dc198e82566d97e70e715d1de42513fd80674ccd2f8451b9cb

Observation 8153c4cb-8621-41d2-9751-526f460555be · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

Reference 19

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source=pdf_text observed=2026-08-04T06:42:10.048508Z digest=sha256:1cfb4a7c5741de42c0fbf6a40f117da367b3e16af29d8d6e7f874523492b2275

Observation 08013cd4-d48d-4046-a926-a76802013654 · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 20

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source=pdf_text observed=2026-08-04T06:42:10.160650Z digest=sha256:4536da905b241cd08bed1d56907e20470cdaaad8e4cbc6251e7452370113c494

Observation faf04377-9739-4250-b404-5bfeeda3bc66 · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation

Reference 21

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source=pdf_text observed=2026-08-04T06:42:10.255843Z digest=sha256:6cb535542b6c6944e29445c15ec9e5434dba43b53a506393cc9657962fad9cb0

Observation 829bce12-606c-40c0-a0c2-b4164ec12fd6 · outbound

This paper cites Diffusion policy: Visuomotor policy learning via ac- tion diffusion,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Diffusion policy: Visuomotor policy learning via ac- tion diffusion,

Reference 22

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source=pdf_text observed=2026-08-04T06:42:10.377547Z digest=sha256:62bf97352eef74a38e4e2a480e546318b8c5bbb76b489e4c29c134bdd817a846

Observation 5863703e-13ff-4763-8d3b-5162d8055bf0 · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving

Reference 23

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source=pdf_text observed=2026-08-04T06:42:10.484406Z digest=sha256:71d163b81fb90f09f4dcdecdf301bff29b81d65cf157b6ce036c5a6c6a1d5af7

Observation fcbfcd38-957d-47c0-bdad-54e4dbad50cb · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba

Reference 24

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source=pdf_text observed=2026-08-04T06:42:10.562951Z digest=sha256:dcc541871b25dd33e963baad7b10bc383dd4ccd38794fd0593c649ebbfc674a7

Observation be286ddb-ec76-4cf6-9948-993a0262f8c5 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 25

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source=pdf_text observed=2026-08-04T06:42:10.758548Z digest=sha256:16aa89dd9a318c830c23232814ef075f7b76afc8bc7a6b94bac952ec62ea1d4d

Observation 7557a26c-f3b1-4d54-9067-80960d93a2a6 · outbound

This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 26

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source=pdf_text observed=2026-08-04T06:42:10.887455Z digest=sha256:9292b464f415dac3d82b8d6c73a39c0c5bcc51a8b5affc1801f586ecb2ac1f9b

Observation 484e32c7-8ad0-4861-ab94-cf1432376e1b · outbound

This paper cites RWKV: Reinventing RNNs for the Transformer Era.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers RWKV: Reinventing RNNs for the Transformer Era

Reference 27

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source=pdf_text observed=2026-08-04T06:42:11.005933Z digest=sha256:b606e0e81c94a18153d27eddd38eb4d86fc10b29cf3f329a79d5269d09d40a13

Observation 87a15669-53da-4ed0-8674-aad7e832c006 · outbound

This paper cites Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence

Reference 28

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source=pdf_text observed=2026-08-04T06:42:11.129890Z digest=sha256:d4f41f5525e4963d4b88d292920842db2f3ed60ab1a0a76b719722b75b473a53

Observation 26ffc75b-6aae-46b9-b9c6-83bb4a5ca03c · outbound

This paper cites RWKV-7 "Goose" with Expressive Dynamic State Evolution.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers RWKV-7 "Goose" with Expressive Dynamic State Evolution

Reference 29

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source=pdf_text observed=2026-08-04T06:42:11.241474Z digest=sha256:bc836a029bb9b11106334bf347f33f3c44bc2f1ac166a45e277e7687f6bd5c56

Observation 4c1ace1b-38cd-492d-af25-fb949571089d · outbound

This paper cites Kimi Linear: An Expressive, Efficient Attention Architecture.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Kimi Linear: An Expressive, Efficient Attention Architecture

Reference 30

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source=pdf_text observed=2026-08-04T06:42:11.328087Z digest=sha256:e0b59097d79af27c2e49be41a513b4215efd78fc2d38228209a31434ad82f749

Observation 05e25a5d-3b99-4e4b-826b-ff6739d35d97 · outbound

This paper cites Transdiffuser: End-to-end trajectory generation with decorrelated multi-modal representation for autonomous driving,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Transdiffuser: End-to-end trajectory generation with decorrelated multi-modal representation for autonomous driving,

Reference 31

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source=pdf_text observed=2026-08-04T06:42:11.423087Z digest=sha256:2911c0795e858477b09c453a894ae48eeb9d5ee4e49a0bf4e51d6a6750578da4

Observation 18f43daf-49c7-4a58-96d7-a5d7a7c8071d · outbound

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

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking,

Reference 32

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source=pdf_text observed=2026-08-04T06:42:11.472183Z digest=sha256:424fee9584f9caa6e5d5cf165f9a5e68d31785fd1e156386c34a4152ee4704e1

Observation e4874338-c31b-42a4-bfc8-ec92f820e0da · outbound

This paper cites iPad: Iterative Proposal-centric End-to-End Autonomous Driving.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers iPad: Iterative Proposal-centric End-to-End Autonomous Driving

Reference 33

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source=pdf_text observed=2026-08-04T06:42:11.529109Z digest=sha256:70c6790769964eca0bb1b9baa9005762b98fbdd637f80e5f5b8ae85bcd11d27a

Observation 3379c951-d59c-4332-ae9f-565a51e060aa · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Retentive Network: A Successor to Transformer for Large Language Models

Reference 34

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source=pdf_text observed=2026-08-04T06:42:11.583117Z digest=sha256:74037b748a03262720c5dd6952a32e628be4b13601ef5b5e84f9ecd8c9408ab7

Observation 4002f371-98c1-42ad-a503-05a0a3d207c5 · outbound

This paper cites Gated linear atten- tion transformers with hardware-efficient training,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Gated linear atten- tion transformers with hardware-efficient training,

Reference 35

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source=pdf_text observed=2026-08-04T06:42:11.669844Z digest=sha256:8379dd66914f51b5a4f8d5aa8258e19ca349ea2caff422b9f81b25cc26d7af13

Observation 97543755-aa72-4848-8216-667d4eb6cda2 · outbound

This paper cites Linear transformers are secretly fast weight programmers,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Linear transformers are secretly fast weight programmers,

Reference 36

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source=pdf_text observed=2026-08-04T06:42:11.763339Z digest=sha256:7b58773acb3c78db0ea63aed5611500e3dcde13c892088cba6b506a63a424e5b

Observation 0f4f63cb-5634-4f2c-9059-2b8852ea28f6 · outbound

This paper cites Adaptive switching circuits,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Adaptive switching circuits,

Reference 37

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no resolver link, observed 2026-08-04T06:42:11.859629Z

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source=pdf_text observed=2026-08-04T06:42:11.859629Z digest=sha256:ce294e3737090021fd965c54523da4da680f670e5a51f27e0dadcdcade4a69e1

Observation 89921422-127d-466e-a755-21bce9b43d24 · outbound

This paper cites Parallelizing Linear Transformers with the Delta Rule over Sequence Length.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Parallelizing Linear Transformers with the Delta Rule over Sequence Length

Reference 38

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no resolver link, observed 2026-08-04T06:42:11.959356Z

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source=pdf_text observed=2026-08-04T06:42:11.959356Z digest=sha256:17a9e502535ab98f3b63912e48abc8101021b7304c0bb7fa38bc3aededdc1254

Observation 013a6ae4-1c0e-4e7e-8ca5-024214193d35 · outbound

This paper cites Attention is all you need,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Attention is all you need,

Reference 39

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no resolver link, observed 2026-08-04T06:42:12.048303Z

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source=pdf_text observed=2026-08-04T06:42:12.048303Z digest=sha256:0d363b84fcef33be4110d68923a15d87f348cdbfd3f81b653fa5709eeaa221a9

Observation b8b7b24f-8db3-4a81-9a2d-3eadd5cb40b1 · outbound

This paper cites Fla: A triton-based library for hardware- efficient implementations of linear attention mechanism,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Fla: A triton-based library for hardware- efficient implementations of linear attention mechanism,

Reference 40

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source=pdf_text observed=2026-08-04T06:42:12.106717Z digest=sha256:876f978ad771a2106fa9fd33ee8f8005bec71fb630fb052bb04befd0590f01d0

Observation a933b2b0-1aba-401a-8416-ff2c4e640bc2 · outbound

This paper cites Deep residual learning for image recognition,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Deep residual learning for image recognition,

Reference 41

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no resolver link, observed 2026-08-04T06:42:12.177680Z

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source=pdf_text observed=2026-08-04T06:42:12.177680Z digest=sha256:9a5dee66196d0a421d3485b1aff24fa6004175450e440bdd94c51615c97ecd08

Observation d8b924cc-352d-4daa-a52e-202f74543e39 · outbound

This paper cites Carla: An open urban driving simulator,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Carla: An open urban driving simulator,

Reference 42

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no resolver link, observed 2026-08-04T06:42:12.275905Z

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source=pdf_text observed=2026-08-04T06:42:12.275905Z digest=sha256:70e361af782c49edfdadcd49df88ecb02fd5efacc894414b3bfd63a35ae06185

Observation f7806e76-30df-411e-88f0-9398be4c21ac · outbound

This paper cites Bench2drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving,.

LADY: Linear Attention for Autonomous Driving Efficiency without Transformers Bench2drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving,

Reference 43

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source=pdf_text observed=2026-08-04T06:42:12.349268Z digest=sha256:6b5d7c71c4ebbf153961045258f7c5915e9ff9560452295a8465e270cc4a8343

Pith citing papers

No inbound Pith citation observations are available.