Paper Citation Record · LEDGER

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation

As of 11 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.21734.

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

pith.paper-citation-record.v1
2505.21734 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:30:55.363308Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact0
verified fuzzy43
unresolved1
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 31807fe2-284c-4603-b270-0a5b985b2a99 · outbound

This paper cites Perception, planning, control, and coordination for autonomous vehicles,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Perception, planning, control, and coordination for autonomous vehicles,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:30:50.655438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf67fcd8-b608-4990-b7e9-51ce913589ae · outbound

This paper cites A decision-theoretic approach to planning, perception, and control,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation A decision-theoretic approach to planning, perception, and control,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:04.309337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d296e766-0f2d-49f8-92b3-30b4ecc8a7b7 · outbound

This paper cites A Survey of Deep Learning Techniques for Autonomous Driving,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation A Survey of Deep Learning Techniques for Autonomous Driving,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:04.120426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4158146c-c3e7-47e5-acb7-aea812a02a7e · outbound

This paper cites Recent Advancements in End-to-End Autonomous Driving Using Deep Learning: A Survey,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Recent Advancements in End-to-End Autonomous Driving Using Deep Learning: A Survey,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:03.901782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6977fe79-c27d-4b2a-b4be-85d28961d115 · outbound

This paper cites Learning to drive in a day,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Learning to drive in a day,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:03.741483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cf11ca73-5c5b-457c-8f96-efdbfff695c3 · outbound

This paper cites Diffstack: A differentiable and modular control stack for autonomous vehicles,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Diffstack: A differentiable and modular control stack for autonomous vehicles,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:03.585154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c1a86fc3-92bc-4f8a-b888-b6b0dd1b4086 · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation You Only Look Once: Unified, Real-Time Object Detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:03.341472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8fb22eaf-b35a-4720-bab4-1fbd1f5a1f76 · outbound

This paper cites Center-based 3d object detec- tion and tracking,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Center-based 3d object detec- tion and tracking,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:03.190352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation be31a0b8-05a8-4cf5-ae39-55cd2e2e13ae · outbound

This paper cites Deepfusion: Lidar- camera deep fusion for multi-modal 3d object detection,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Deepfusion: Lidar- camera deep fusion for multi-modal 3d object detection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:02.946852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 85263a0d-44ff-4639-a011-00d91ab4fe7f · outbound

This paper cites Motionnet: Joint perception and motion prediction for autonomous driving based on bird’s eye view maps,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Motionnet: Joint perception and motion prediction for autonomous driving based on bird’s eye view maps,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:02.696537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3786fc34-02ad-4126-969f-3329f20d441a · outbound

This paper cites Deep Learning-Based Vehicle Behavior Prediction for Au- tonomous Driving Applications: A Review,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Deep Learning-Based Vehicle Behavior Prediction for Au- tonomous Driving Applications: A Review,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:02.441127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9a2d7d3a-5ecd-489a-866c-34a96cadfb9d · outbound

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

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation One thousand and one hours: Self-driving motion prediction dataset,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:02.241639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 31a2ec7c-cc22-4528-8046-0f041e257c10 · outbound

This paper cites Deep learning based motion planning for autonomous vehicle using spatiotemporal lstm network,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Deep learning based motion planning for autonomous vehicle using spatiotemporal lstm network,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:02.069693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 58ce9eab-c9fd-44b6-868b-b4d6e1f83704 · outbound

This paper cites Integration of Reinforcement Learning Based Behavior Planning With Sampling Based Motion Planning for Automated Driving,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Integration of Reinforcement Learning Based Behavior Planning With Sampling Based Motion Planning for Automated Driving,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:01.850470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f99ef4c-c106-471c-bfd0-9d611eed347c · outbound

This paper cites Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:01.607241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c979d9cb-dbdf-440f-972b-ec8d5429a5fc · outbound

This paper cites Parallel Learning-Based Steering Control for Autonomous Driving,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Parallel Learning-Based Steering Control for Autonomous Driving,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:01.307324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0169a988-56cd-424a-b062-65e6cfffad21 · outbound

This paper cites Event-Triggered Model Pre- dictive Control With Deep Reinforcement Learning for Autonomous Driving,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Event-Triggered Model Pre- dictive Control With Deep Reinforcement Learning for Autonomous Driving,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:01.084737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4987783a-a26e-4d49-a51b-0442325a4364 · outbound

This paper cites Pontryagin differentiable programming: An end-to-end learning and control framework,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Pontryagin differentiable programming: An end-to-end learning and control framework,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:00.861662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f03becf8-e3da-4c74-afb4-a8917e448e11 · outbound

This paper cites Carl-Lead: Lidar-based End- to-End Autonomous Driving with Contrastive Deep Reinforcement Learning,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Carl-Lead: Lidar-based End- to-End Autonomous Driving with Contrastive Deep Reinforcement Learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:00.653941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a0dc267-32cc-4c53-a87e-63165017f362 · outbound

This paper cites Learning from all vehicles,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Learning from all vehicles,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:00.385249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2f8fd354-2b7e-4ce4-9d21-f72e2ad2e832 · outbound

This paper cites Multimodal end-to-end autonomous driving,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Multimodal end-to-end autonomous driving,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:00.146328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0e3e149c-4cac-444c-9a73-4330beb4c9a6 · outbound

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

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Transfuser: Imitation with transformer-based sensor fusion for au- tonomous driving,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:31:00.015611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4f0b5c63-09fd-42c5-b7ed-d055324f7d0a · outbound

This paper cites End-to-end model-free reinforcement learning for urban driving using implicit affordances,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation End-to-end model-free reinforcement learning for urban driving using implicit affordances,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:59.793508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9c3b47c9-4aba-40e3-ad59-8bff33d7fb43 · outbound

This paper cites Interpretable end-to-end urban autonomous driving with latent deep reinforcement learning,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Interpretable end-to-end urban autonomous driving with latent deep reinforcement learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:59.555573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3ccf4c2c-bf3e-41c0-be05-b7091273ac14 · outbound

This paper cites FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:59.395404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fe3f489b-a846-408d-88a2-c08debb743e2 · outbound

This paper cites High-speed au- tonomous racing using trajectory-aided deep reinforcement learning,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation High-speed au- tonomous racing using trajectory-aided deep reinforcement learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:59.224000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4e5c8a01-9f54-4721-95b4-5622c6a87bee · outbound

This paper cites Explanations in Autonomous Driving: A Survey,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Explanations in Autonomous Driving: A Survey,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:59.040669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 851862c9-d705-4b17-9801-4c16db2db081 · outbound

This paper cites Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:58.798704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 780f27f1-1a68-4001-af43-5657de1cde2d · outbound

This paper cites Interpretable learning for self-driving cars by visualizing causal attention,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Interpretable learning for self-driving cars by visualizing causal attention,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:58.632647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f048ef43-f739-4818-9e3e-fe6a035ee8a3 · outbound

This paper cites Deep model reassembly,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Deep model reassembly,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:58.431667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ce731b65-a200-4a31-a2c1-8d4c18ce4ba0 · outbound

This paper cites Differentiable algorithm networks for composable robot learn- ing,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Differentiable algorithm networks for composable robot learn- ing,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:58.156626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ce108e5-642c-4c4f-bc67-da12cb57737e · outbound

This paper cites Pypose: A library for robot learning with physics-based optimization,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Pypose: A library for robot learning with physics-based optimization,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:57.996766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2d760681-c712-410d-9051-c03875e59712 · outbound

This paper cites Pypose v0.6: The imperative programming interface for robotics,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Pypose v0.6: The imperative programming interface for robotics,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:57.811248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 13d5b9f3-8032-4792-bc67-94fc9a1edb3b · outbound

This paper cites Autonomous Automobile Trajectory Tracking for Off-Road Driving: Controller Design, Experimental Validation and Racing,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Autonomous Automobile Trajectory Tracking for Off-Road Driving: Controller Design, Experimental Validation and Racing,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:57.526640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5acd35bb-11ff-409f-b93b-8fe9703394b9 · outbound

This paper cites Minimum curvature trajectory planning and control for an autonomous race car,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Minimum curvature trajectory planning and control for an autonomous race car,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:57.182851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8a0c0285-9e9b-4697-afc3-00a17fb0b923 · outbound

This paper cites SLAM Toolbox: SLAM for the dynamic world,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation SLAM Toolbox: SLAM for the dynamic world,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:57.042043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 81eaa71d-ab3a-4ece-807a-2ac303807721 · outbound

This paper cites Autonomous vehicles on the edge: A survey on autonomous vehicle racing,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Autonomous vehicles on the edge: A survey on autonomous vehicle racing,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:56.901179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4207ab15-45ec-4962-b788-af81bcc52f3b · outbound

This paper cites Local INN: Implicit map representation and localization with invertible neural networks,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Local INN: Implicit map representation and localization with invertible neural networks,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:56.700088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9237fd7e-9933-4110-a720-197a52c8d5dd · outbound

This paper cites CommonRoad: Com- posable benchmarks for motion planning on roads,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation CommonRoad: Com- posable benchmarks for motion planning on roads,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:56.541210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6254b9d2-6abd-4d0e-9605-1179e86724da · outbound

This paper cites F1TENTH: An Open-source Evaluation Environment for Continuous Control and Reinforcement Learning,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation F1TENTH: An Open-source Evaluation Environment for Continuous Control and Reinforcement Learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:56.417445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 81d321bf-a9c8-4d73-8ea6-287fcce3b779 · outbound

This paper cites Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:56.211651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bf90aee4-0056-416c-80e8-cdbd4583f0bb · outbound

This paper cites A novel obstacle avoidance algorithm: “Follow the Gap Method.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation A novel obstacle avoidance algorithm: “Follow the Gap Method

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:56.035346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c44b1119-f86b-4b08-b495-3d3bed55f983 · outbound

This paper cites Implementation of the pure pursuit path tracking algorithm,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Implementation of the pure pursuit path tracking algorithm,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:55.789554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e59c4703-0bcf-41c0-8f59-d715de9dbbc1 · outbound

This paper cites Cddt: Fast approximate 2d ray casting for accelerated localization,.

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation Cddt: Fast approximate 2d ray casting for accelerated localization,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:30:55.531978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.