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Paper Citation Record · LEDGER

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects

As of 8 August 2026, this Paper Citation Record lists 100 of 159 outbound references and 3 inbound Pith citation observations for arXiv:2505.20223.

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

pith.paper-citation-record.v1
2505.20223 v1

Coverage vector

measured 100 of 159 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:02:59.697040Z

measured 103 of 103 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:31:04.402197Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T06:36:24.910354Z

Reference resolution

100 of 159 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved98
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 663e5ac3-418e-4ddc-a461-70af4bf1f826 · outbound

This paper cites Attention is all you need,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Attention is all you need,

Reference 1

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Observation c63bf9aa-272f-44d7-b700-115f9621b624 · outbound

This paper cites Language mod- els are few-shot learners,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Language mod- els are few-shot learners,

Reference 2

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Observation 65659f55-0a3e-47e1-b0ff-3caa7e3cc70a · outbound

This paper cites Pre- train, prompt, and predict: A systematic survey of prompting methods in natural language processing,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Pre- train, prompt, and predict: A systematic survey of prompting methods in natural language processing,

Reference 3

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Observation 51f783f4-4d4a-4411-a8a4-b1cbb609926d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects LLaMA: Open and Efficient Foundation Language Models

Reference 4

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source=pdf_text observed=2026-08-07T14:02:51.126475Z digest=sha256:53fbf328bce7c69a00eb33068490067639f3950f1fe21a4dc1b4f7c468e94143

Observation 9da2a40e-2ec1-4170-85ab-179a6777c354 · outbound

This paper cites When brain-inspired ai meets agi,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects When brain-inspired ai meets agi,

Reference 5

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Observation 8d9666fe-3740-4f74-b530-389a84c74dab · outbound

This paper cites Deep reinforcement learning for autonomous driving: A survey,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Deep reinforcement learning for autonomous driving: A survey,

Reference 6

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Observation 744662ec-c315-4a4b-a0e2-429a0c266ffe · outbound

This paper cites Prospective role of foundation models in advancing autonomous vehicles,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Prospective role of foundation models in advancing autonomous vehicles,

Reference 7

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Observation 560c3e65-ffd1-4b7e-aadd-0dd888f242bf · outbound

This paper cites Large language models for autonomous driving (llm4ad): Concept, benchmark, simulation, and real-vehicle experiment,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Large language models for autonomous driving (llm4ad): Concept, benchmark, simulation, and real-vehicle experiment,

Reference 8

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source=pdf_text observed=2026-08-07T14:02:51.531945Z digest=sha256:aff6ff9132326638f29e27f5479c0c910ab4d7e6b97a848b34baf4cea06562d4

Observation b39f0e72-8e6d-4f40-8ddd-3784512ceb96 · outbound

This paper cites A survey on multimodal large language models for autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A survey on multimodal large language models for autonomous driving,

Reference 9

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source=pdf_text observed=2026-08-07T14:02:51.601214Z digest=sha256:d817f734c0e0367ff51bfb47bcc3361f898baa5ff1b29f3e163eb20b8437cf77

Observation dd32f0f6-72fc-4f18-b7c6-a3916f652d21 · outbound

This paper cites A survey on recent advancements in autonomous driving using deep reinforcement learning: Applications, challenges, and solutions,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A survey on recent advancements in autonomous driving using deep reinforcement learning: Applications, challenges, and solutions,

Reference 10

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Observation aa79fb91-6281-46ae-84db-c825480b7aba · outbound

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

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects End-to-end autonomous driving: Challenges and frontiers,

Reference 11

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Observation 601af090-ea34-4f5d-b679-bc6f233de48a · outbound

This paper cites Towards Reasoning in Large Language Models: A Survey.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards Reasoning in Large Language Models: A Survey

Reference 12

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source=pdf_text observed=2026-08-07T14:02:51.848351Z digest=sha256:ba4b29f003cd2c46cd59b39b9ec77cadc3811a1b91bc5bfe266dee621dd2c7d1

Observation ad3baf55-2b1c-4eea-8b7e-8821f8eab6d6 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Chain-of-thought prompting elicits reasoning in large language models,

Reference 13

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source=pdf_text observed=2026-08-07T14:02:51.954313Z digest=sha256:2a78c7b6d9baf563f79a5c453553a6228eb6cbc79ccc02f883ffc573426edcee

Observation b8eb9a20-a1c3-4105-b6bf-bd2cdb7a5227 · outbound

This paper cites Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought

Reference 14

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source=pdf_text observed=2026-08-07T14:02:52.066758Z digest=sha256:75c4aef2704af38082bf53ea99e90acb6d1bec3193252d1ec151f8dbad8c75bb

Observation 38b7f929-2dc0-4823-9d75-eb1762c63349 · outbound

This paper cites OpenAI o1 System Card.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects OpenAI o1 System Card

Reference 15

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source=pdf_text observed=2026-08-07T14:02:52.166416Z digest=sha256:bbbf9fb13071a481b8e10e46547cfd54f8633071d0c2b0434adbfd57bf8051ab

Observation f231b601-39de-448b-ac81-b29db633d717 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

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source=pdf_text observed=2026-08-07T14:02:52.270919Z digest=sha256:1c9b5aec5015557cfe86000a21cd8b1b1193336331d43ae41b955fd55ce571a5

Observation 15c829fb-3079-4505-8883-815fa3cce16a · outbound

This paper cites Cot-tl: Low-resource tem- poral knowledge representation of planning instructions using chain- of-thought reasoning,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Cot-tl: Low-resource tem- poral knowledge representation of planning instructions using chain- of-thought reasoning,

Reference 17

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source=pdf_text observed=2026-08-07T14:02:52.367393Z digest=sha256:9a8b5f777671f070686331096f2cbe7c827034d2b5e4eca634721e0ee7bfcada

Observation fa0f5f09-f282-4798-8530-8edec6a1ac0a · outbound

This paper cites DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving

Reference 18

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source=pdf_text observed=2026-08-07T14:02:52.458348Z digest=sha256:72b3bd6570db9f33c52d668d7625d9eca80fddd78036a6e9ccc2c994c737fc89

Observation 0925c016-6e7f-4623-b05d-652e7cb02c6f · outbound

This paper cites MedCoT: Medical Chain of Thought via Hierarchical Expert.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects MedCoT: Medical Chain of Thought via Hierarchical Expert

Reference 19

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source=pdf_text observed=2026-08-07T14:02:52.541026Z digest=sha256:845d4709f994fb0925de47168a4eeced248f975c62dc80585991864050cb479a

Observation aa858c26-4e73-4fbe-99de-87ce904bccc7 · outbound

This paper cites Leveraging nlp in finance: A synergistic approach using large language models and chain-of-thought reasoning,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Leveraging nlp in finance: A synergistic approach using large language models and chain-of-thought reasoning,

Reference 20

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source=pdf_text observed=2026-08-07T14:02:52.651386Z digest=sha256:ffbcbeb33d384b51c10d9e420b0a1b2282410589bfdac8f5768ca98e3aedc7d8

Observation 63d556ef-4e20-4813-b7d4-3824b8e545b1 · outbound

This paper cites M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects M$^3$CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought

Reference 21

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source=pdf_text observed=2026-08-07T14:02:52.740516Z digest=sha256:2ab041f6f3a815371f3ff83d1c20b5e2e33d511d602f5cda3f102bdf7ccaea0f

Observation fdb45d00-378f-4842-ae06-ce1331c8b08e · outbound

This paper cites Drive like a human: Rethinking autonomous driving with large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Drive like a human: Rethinking autonomous driving with large language models,

Reference 22

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source=pdf_text observed=2026-08-07T14:02:52.852967Z digest=sha256:605946ad880380928ecf33e8bfc228bc2300d6fc42264fe6e5c37ec40c490c6b

Observation a46ddc6f-dd02-4bf1-a6f9-062712f95483 · outbound

This paper cites Learning autonomous driving tasks via human feedbacks with large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Learning autonomous driving tasks via human feedbacks with large language models,

Reference 23

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source=pdf_text observed=2026-08-07T14:02:52.903770Z digest=sha256:70eb91f23d7240594cce5fb6f719549c241f1d8be5c6bd30aaed4c560215c5b9

Observation e0b987ba-5b9b-41d5-b6eb-36396d7ed565 · outbound

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

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models

Reference 24

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source=pdf_text observed=2026-08-07T14:02:53.015580Z digest=sha256:3a156b549c480226fea82d6935d7bab49ae89a154390c062d120184268cc4cc2

Observation 89570ff0-2cb6-4843-b5fb-49a4ed124488 · outbound

This paper cites Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Reason2drive: Towards interpretable and chain-based reasoning for autonomous driving,

Reference 25

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source=pdf_text observed=2026-08-07T14:02:53.126310Z digest=sha256:4f1e2b5406c5c82cf598241404e95b9f77c81fdb5b768762255f9a820f6859dd

Observation 2404c084-287e-4f9d-9e11-1d38d0539dc1 · outbound

This paper cites LLM4Drive: A Survey of Large Language Models for Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects LLM4Drive: A Survey of Large Language Models for Autonomous Driving

Reference 26

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source=pdf_text observed=2026-08-07T14:02:53.174375Z digest=sha256:59d17de0f022e73e15cdcb38b87385eb72ae83d4665683b62364872d75a8c022

Observation 5bff2686-be74-40ae-afd4-161b0015a577 · outbound

This paper cites A Survey for Foundation Models in Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A Survey for Foundation Models in Autonomous Driving

Reference 27

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source=pdf_text observed=2026-08-07T14:02:53.294595Z digest=sha256:26464e159c7ce69a79e4409745c026c6040beee55e3ff3dbc3f998d443ccdee5

Observation d380e08a-d47d-4dcc-b2b0-3a284471ea20 · outbound

This paper cites Vision language models in autonomous driving: A survey and outlook,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Vision language models in autonomous driving: A survey and outlook,

Reference 28

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source=pdf_text observed=2026-08-07T14:02:53.380505Z digest=sha256:87d21df4444d6610839dcb8f052eff2b71d42eb87b2196cd706bab4a4c009ccf

Observation 9c71fd43-2ccf-4957-8110-e48dc76293a7 · outbound

This paper cites Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

Reference 29

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source=pdf_text observed=2026-08-07T14:02:53.463046Z digest=sha256:baf82122efc7ce46c3a5a8cb24521c66b129433db2433b68094dcdfba1d1b87f

Observation ce7996c1-aa5c-4dd7-a350-50dd53c84a9c · outbound

This paper cites Towards Better Chain-of-Thought Prompting Strategies: A Survey.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards Better Chain-of-Thought Prompting Strategies: A Survey

Reference 30

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source=pdf_text observed=2026-08-07T14:02:53.517484Z digest=sha256:f83524f7a326dfd6f532367ece240852fb04370711ecca4a5e1550b04736abb3

Observation ac7e5d37-944c-422c-8a5a-38fa28eba77e · outbound

This paper cites Scalable end-to-end autonomous vehicle testing via rare-event simu- lation,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Scalable end-to-end autonomous vehicle testing via rare-event simu- lation,

Reference 31

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Observation 1df2791b-3e0a-414b-8477-89e7bc5572fc · outbound

This paper cites Planning-oriented autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Planning-oriented autonomous driving,

Reference 32

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source=pdf_text observed=2026-08-07T14:02:53.703978Z digest=sha256:791b4dcc76d872e340861792be331868903d4eda2699acbaa6fe7a753d60c450

Observation b4d420e6-92ac-4c59-bc5b-3c21e935d068 · outbound

This paper cites End-to- end urban driving by imitating a reinforcement learning coach,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects End-to- end urban driving by imitating a reinforcement learning coach,

Reference 33

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source=pdf_text observed=2026-08-07T14:02:53.785427Z digest=sha256:08cbde1456de55e12537fe77727b6f55a4dd3eaf6bfd894678c95381c39e7d33

Observation 13f16675-bee9-4212-a350-f90047c6ff8c · outbound

This paper cites Imitation learning for agile autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Imitation learning for agile autonomous driving,

Reference 34

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source=pdf_text observed=2026-08-07T14:02:53.892072Z digest=sha256:4f7d99c715eeebe74a6121bb3b8c408362bf193c1e1adb38f1b44f2d2e12feee

Observation 01ca70c2-8d5d-400c-8768-4e9791b2371c · outbound

This paper cites Continual Adaptation for Autonomous Driving with the Mixture of Progressive Experts Network.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Continual Adaptation for Autonomous Driving with the Mixture of Progressive Experts Network

Reference 35

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source=pdf_text observed=2026-08-07T14:02:53.985148Z digest=sha256:4d5c987f0469c567a3915b6c45e7f233dc4769f7362361cd4bb1f8b97b737215

Observation 4a27b592-bf88-4d50-9219-6458d5b231fd · outbound

This paper cites Towards Knowledge-driven Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards Knowledge-driven Autonomous Driving

Reference 36

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source=pdf_text observed=2026-08-07T14:02:54.058433Z digest=sha256:a03da06c14728f120ad83b1c0eb517654c0d5620e1f589a245351c76df6a684d

Observation 336eb2e5-13cf-4e70-b52a-a597374c2426 · outbound

This paper cites Congested traffic states in empirical observations and microscopic simulations,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Congested traffic states in empirical observations and microscopic simulations,

Reference 37

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Observation 2a2fbc21-9181-41ab-a80f-9f956cecbe48 · outbound

This paper cites Rule-based optimal control for autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Rule-based optimal control for autonomous driving,

Reference 38

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Observation 2fc2b7fe-41f5-4e21-aab2-dd0184e877b4 · outbound

This paper cites A reinforcement learning-based adaptive path tracking approach for autonomous driv- ing,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A reinforcement learning-based adaptive path tracking approach for autonomous driv- ing,

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source=pdf_text observed=2026-08-07T14:02:54.311092Z digest=sha256:9eca3397d8d7b7219b2b5b07c01452f87724a1d291194dc9180cdbad4e788f0c

Observation f996e140-bef9-4197-a12d-3c36c83a1b35 · outbound

This paper cites High-level decision making for automated highway driving via behavior cloning,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects High-level decision making for automated highway driving via behavior cloning,

Reference 40

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source=pdf_text observed=2026-08-07T14:02:54.371801Z digest=sha256:3507fbca3272230e8fda398c7ccc8323229bd53b581fd412f1f2eb10be651de4

Observation ebf6e2f3-88bd-405e-bf7c-64f98b633b77 · outbound

This paper cites DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

Reference 41

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source=pdf_text observed=2026-08-07T14:02:54.489719Z digest=sha256:cc193b6e4cf66c840f3c90b73b24cf50eeeabb09dc8035d68f6f1b8fa008508f

Observation b31184b9-f863-4bba-9aa7-5523647c443b · outbound

This paper cites WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model

Reference 42

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source=pdf_text observed=2026-08-07T14:02:54.573103Z digest=sha256:7545aa74bc5dbac1a645af28b27a948576a6b8f5cc326669bad848fc97264d65

Observation 533c5f6e-0975-4463-8d09-65b22f1d17a2 · outbound

This paper cites Brachman and H.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Brachman and H

Reference 43

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source=pdf_text observed=2026-08-07T14:02:54.635612Z digest=sha256:bc69d8e9e182c424fdf2230520b34f681a8a1dbf66835edc5cedf25247566fdf

Observation b91d63d8-6028-4394-83f3-e7d694b1c80f · outbound

This paper cites Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 44

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source=pdf_text observed=2026-08-07T14:02:54.752609Z digest=sha256:19339fc172580f858fb01e0347d0fc2a0ed207c0323c443746c2da2333a5f033

Observation 26703b63-7af4-4b00-9a7c-07bb6f5f9b92 · outbound

This paper cites A comprehensive study on self-learning methods and implications to autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A comprehensive study on self-learning methods and implications to autonomous driving,

Reference 45

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source=pdf_text observed=2026-08-07T14:02:54.860445Z digest=sha256:3ec1266229f2bf53db98c7d1497c030a5c7e1b6125321303325c96785d1dcb36

Observation fa058ea4-baa8-4583-92fe-16da88d1ba72 · outbound

This paper cites The role of world models in shaping autonomous driving: A comprehensive survey,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects The role of world models in shaping autonomous driving: A comprehensive survey,

Reference 46

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source=pdf_text observed=2026-08-07T14:02:54.934732Z digest=sha256:808bfd3526c636100b8aecf0ac02ce11c7792813ad72c0427227fa3d9b1bbce6

Observation ab429029-08fe-411a-a344-2390bf1f48f7 · outbound

This paper cites Curiosity-driven exploration by self-supervised prediction,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Curiosity-driven exploration by self-supervised prediction,

Reference 47

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source=pdf_text observed=2026-08-07T14:02:55.052803Z digest=sha256:704811b456902ffd9fe0891dd066c32bf60da55bd6d3ea3a5554abf50e6c117d

Observation 99b8eb33-5605-49a5-8aee-37cc8fbeab6a · outbound

This paper cites Enhancing autonomous driving through dual-process learning with behavior and reflection integration,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Enhancing autonomous driving through dual-process learning with behavior and reflection integration,

Reference 48

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source=pdf_text observed=2026-08-07T14:02:55.158127Z digest=sha256:7c612ff9cb07f732c6f521d80d45532927b62fe17cf7368dbf6ea00431605234

Observation 725eb47e-cb08-4a10-981d-25af9d6245b4 · outbound

This paper cites Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Reference 49

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source=pdf_text observed=2026-08-07T14:02:55.273259Z digest=sha256:46e0c1180c3ebf5d9ca0194d3a51c8d71f48d8a239e899affd41cf31d2581def

Observation 019aeed8-ad03-45d8-a6ef-6fa04966190c · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Gemini: A Family of Highly Capable Multimodal Models

Reference 50

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source=pdf_text observed=2026-08-07T14:02:55.374948Z digest=sha256:84cb62d6ea2a8dc19e4df6f2b7caea4035ffef4273a3895f4dff79bd98d6d7fe

Observation a10b06be-4b14-4f46-9e31-4e9c62b0573f · outbound

This paper cites GPT-4o System Card.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects GPT-4o System Card

Reference 51

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source=pdf_text observed=2026-08-07T14:02:55.436788Z digest=sha256:41014c239abb3cfe779ecc2ff005148d1d05b7782a7364c7121e7ace1ffa7c95

Observation 6f58b97a-8393-4891-8ef3-1673de7ac92a · outbound

This paper cites DeepSeek-V3 Technical Report.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects DeepSeek-V3 Technical Report

Reference 52

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source=pdf_text observed=2026-08-07T14:02:55.533148Z digest=sha256:6af21f320a533a2928d82d3e3ddfd8e48b004b50494491c6b62bb7ec34bd6366

Observation 0e80ff4e-2037-4898-9829-b1420011be5a · outbound

This paper cites Enhancing Advanced Visual Reasoning Ability of Large Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Enhancing Advanced Visual Reasoning Ability of Large Language Models

Reference 53

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source=pdf_text observed=2026-08-07T14:02:55.604831Z digest=sha256:086f3439d43f4b7b63111ef4ec3b2253cef5d67752cd6d17fafd737fe47362bb

Observation 9bf7b884-fd2e-49a7-9980-3b5bf327536f · outbound

This paper cites MM-LLMs: Recent Advances in MultiModal Large Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects MM-LLMs: Recent Advances in MultiModal Large Language Models

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source=pdf_text observed=2026-08-07T14:02:55.661646Z digest=sha256:54ea56893c389571f0923602403f554a3422a8165446c98b3058779759b70899

Observation 58e388ac-6946-4a66-8d9a-accd269b82d1 · outbound

This paper cites Visual Large Language Models for Generalized and Specialized Applications.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Visual Large Language Models for Generalized and Specialized Applications

Reference 55

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source=pdf_text observed=2026-08-07T14:02:55.719810Z digest=sha256:1dd4a0df8a1d0f826d229a3ece1b510ac1764eeaf264c4d94e9f792252e4a550

Observation 9fdab3cf-cd22-429e-96dc-6a66b5e280e7 · outbound

This paper cites Opendrivevla: Towards end-to-end autonomous driving with large vision language action model,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Opendrivevla: Towards end-to-end autonomous driving with large vision language action model,

Reference 56

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source=pdf_text observed=2026-08-07T14:02:55.828210Z digest=sha256:0fc0082f5034162ea6aa915d67b5e328aeb7b775e72c0eacaeaded379ba624f7

Observation b89d0e49-2a1c-4d4f-ac52-577db36fbdc1 · outbound

This paper cites AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning

Reference 57

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source=pdf_text observed=2026-08-07T14:02:55.924550Z digest=sha256:d2c39bc4044180070151b1199ffc5274d3e52fc3599bee3e00ee4e47c286b199

Observation bee5e22c-5fb3-4f0c-8512-3488c0aa1ae2 · outbound

This paper cites A survey of efficient reasoning for large rea- soning models: Language, multimodality, and beyond,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A survey of efficient reasoning for large rea- soning models: Language, multimodality, and beyond,

Reference 58

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source=pdf_text observed=2026-08-07T14:02:55.993367Z digest=sha256:4f899df3ab69d46ff22d491d5b0830c43b5b070300d4ba0203274195411996f6

Observation 4c45481f-929c-4ebe-aed3-1afe8b173b69 · outbound

This paper cites Language models show human-like content effects on reasoning tasks.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Language models show human-like content effects on reasoning tasks

Reference 59

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source=pdf_text observed=2026-08-07T14:02:56.061494Z digest=sha256:b71db3cf218a4dd27d16f38c2c1d0779e4672fac58a02b41e9c31b3508c7d496

Observation 59eae496-43f2-4f92-a190-689ab3753902 · outbound

This paper cites To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

Reference 60

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source=pdf_text observed=2026-08-07T14:02:56.160760Z digest=sha256:16d029dca7554513c871787473bbbe8985c06265a66df2be29bef29106bd3ea7

Observation c9ce969c-c73b-435a-97d6-46290be719ab · outbound

This paper cites Let’s verify step by step,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Let’s verify step by step,

Reference 61

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source=pdf_text observed=2026-08-07T14:02:56.227423Z digest=sha256:981ceedc9130af76bf86f859e2d8f7b773b774c716d71dd8321cb645e7677bd3

Observation c7989f9e-a768-4632-841e-a03eab871c72 · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Large lan- guage models are zero-shot reasoners,

Reference 62

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source=pdf_text observed=2026-08-07T14:02:56.322360Z digest=sha256:28bf6f36cd1f202135807fd553509acc8e967d909cab3cf3663a19ed234c4d42

Observation 8d23f732-cc91-46cf-81a5-af025008f3e6 · outbound

This paper cites On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

Reference 63

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source=pdf_text observed=2026-08-07T14:02:56.412306Z digest=sha256:f541b45ce74daddc7f613208b619dfe7336d2ac4c8a43a20470830061871bcd1

Observation d6b79275-e562-4289-9fe0-c0b130dfce09 · outbound

This paper cites Supervised Chain of Thought.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Supervised Chain of Thought

Reference 64

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source=pdf_text observed=2026-08-07T14:02:56.529809Z digest=sha256:d416cad6f161b3b6e159297cbd430d280b49719b5bb7a1b6206420918f579e2a

Observation 69270bdb-1169-4a6e-b25e-f34ee9cef0e6 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Self-Consistency Improves Chain of Thought Reasoning in Language Models

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source=pdf_text observed=2026-08-07T14:02:56.641227Z digest=sha256:7de39bc2cddfae7952e85d1e360a131613ca3df85928a6f765965c3c53e88213

Observation a84f319a-5d5b-4e99-9b03-4051eba9346b · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Tree of thoughts: Deliberate problem solving with large language models,

Reference 66

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source=pdf_text observed=2026-08-07T14:02:56.761642Z digest=sha256:9bd36b02c5e69b1e60dd4b9d5868f0ab43521f5bccac31d39c3d30b5da301dab

Observation 10955948-506c-4d85-9d07-9ed73a2b22a2 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Graph of thoughts: Solving elaborate problems with large language models,

Reference 67

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Observation 7d95eca2-2377-423e-ac5c-add77ad57053 · outbound

This paper cites Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning,

Reference 68

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source=pdf_text observed=2026-08-07T14:02:56.911862Z digest=sha256:279818850833e994cd3b042e81d08b00acb34b158cc59f77fa20fb3e41a972c5

Observation c8763ff9-10b6-4436-a687-abc1eb4f5234 · outbound

This paper cites Multimodal Chain-of-Thought Reasoning in Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Multimodal Chain-of-Thought Reasoning in Language Models

Reference 69

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source=pdf_text observed=2026-08-07T14:02:56.990545Z digest=sha256:c78b8734a428b031f5417166cac4937a42b2b024a6eb772a039c86db4bbbf9c4

Observation e45595e9-31c2-4450-b34c-7b47859967f1 · outbound

This paper cites A Language Agent for Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects A Language Agent for Autonomous Driving

Reference 70

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source=pdf_text observed=2026-08-07T14:02:57.079563Z digest=sha256:f299c024a2132e3e51dfb17c13ec99697dbbc0e6b711dafd540b0537c577659c

Observation 86859163-4c97-4365-8de0-168e9ceacb07 · outbound

This paper cites Dolphins: Multimodal language model for driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Dolphins: Multimodal language model for driving,

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Observation 1a976bd2-47d8-4e8c-84cb-cafa5d8ac1f9 · outbound

This paper cites DriveAgent: Multi-Agent Structured Reasoning with LLM and Multimodal Sensor Fusion for Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects DriveAgent: Multi-Agent Structured Reasoning with LLM and Multimodal Sensor Fusion for Autonomous Driving

Reference 73

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source=pdf_text observed=2026-08-07T14:02:57.346857Z digest=sha256:f44f98dd11812730c1fdb8fb2656139ad1ca4e30eab23a91d193953c6b9e277f

Observation 4b9637e6-6616-49a8-9092-0bcbe7df8dfa · outbound

This paper cites Agentthink: A unified framework for tool-augmented chain-of-thought reasoning in vision-language models for autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Agentthink: A unified framework for tool-augmented chain-of-thought reasoning in vision-language models for autonomous driving,

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source=pdf_text observed=2026-08-07T14:02:57.428840Z digest=sha256:ef81c62ce7d95537fd01652058eb0742a8ca3436a1b15d47b1e8fa356677d81f

Observation c0253f50-8516-4e93-afe4-6528de626d2f · outbound

This paper cites WOMD-Reasoning: A Large-Scale Dataset for Interaction Reasoning in Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects WOMD-Reasoning: A Large-Scale Dataset for Interaction Reasoning in Driving

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source=pdf_text observed=2026-08-07T14:02:57.503593Z digest=sha256:48d0669cba0713719eceba2f7a495e2be73c2faa078563cbd2fc1f603194d156

Observation 33030df3-64b5-41d6-9807-be7af78f4b4a · outbound

This paper cites Lc-llm: Explainable lane-change intention and trajectory predictions with large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Lc-llm: Explainable lane-change intention and trajectory predictions with large language models,

Reference 76

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Observation 438c2878-122b-49ba-ae7e-c800e41cba86 · outbound

This paper cites CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting

Reference 77

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Observation d659b427-3f25-4226-9bb1-cc8ab43fa427 · outbound

This paper cites Senserag: Constructing environmental knowledge bases with proactive querying for llm-based autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Senserag: Constructing environmental knowledge bases with proactive querying for llm-based autonomous driving,

Reference 78

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source=pdf_text observed=2026-08-07T14:02:57.851219Z digest=sha256:acec1505846ba54efa9960cf444e50ca0ebf74808d3be5c7aa6780fbfed853e3

Observation 4b644a42-ab1f-43da-86a3-c2e2ef9add01 · outbound

This paper cites GPT-Driver: Learning to Drive with GPT.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects GPT-Driver: Learning to Drive with GPT

Reference 79

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source=pdf_text observed=2026-08-07T14:02:57.960590Z digest=sha256:1443e7e59e9f6e6644fe3d768616c6f6ec46dd2534a9c02fd8b4f6c82976d708

Observation b0bbb771-66a6-4a8a-907a-eee50c28535e · outbound

This paper cites PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planning.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planning

Reference 80

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source=pdf_text observed=2026-08-07T14:02:58.045250Z digest=sha256:b65829a57fee4d71a685cc97c9d7d3358fef3ff803013cfb8ea4c90bb076336a

Observation 8009065f-c0b8-4d73-9b7e-edcfe63ef469 · outbound

This paper cites Making large language models better planners with reasoning-decision alignment,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Making large language models better planners with reasoning-decision alignment,

Reference 81

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source=pdf_text observed=2026-08-07T14:02:58.107465Z digest=sha256:d7e3fb6b119537850ef2e485ade704ff132cd40c2148580088444ad23b4b0235

Observation 5d983f1b-6112-4734-b754-ecf33dd94428 · outbound

This paper cites CALMM-Drive: Confidence-Aware Autonomous Driving with Large Multimodal Model.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects CALMM-Drive: Confidence-Aware Autonomous Driving with Large Multimodal Model

Reference 82

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source=pdf_text observed=2026-08-07T14:02:58.164947Z digest=sha256:f61f3ce2088cc699d30479e47c7e75dd2f6aab534d18c40e56be372a98391ce9

Observation 1342867e-698f-4a1b-af73-1e03b04330da · outbound

This paper cites LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving

Reference 83

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source=pdf_text observed=2026-08-07T14:02:58.221495Z digest=sha256:41dd7b08646b18b0bbfdb51c0e7e3631edec8c5472eddfabc08e4e5d44551120

Observation b8fd56e8-2f6b-4497-ba57-97ad5673dfd8 · outbound

This paper cites Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving,

Reference 84

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source=pdf_text observed=2026-08-07T14:02:58.300913Z digest=sha256:14fe8e39dfd76e6a299b4d0f23c0ea44b7223871f1e039589358a35f82303271

Observation e1944876-daab-4a24-9daa-0e3ff14e2be0 · outbound

This paper cites Receive, reason, and react: Drive as you say, with large language models in autonomous vehicles,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Receive, reason, and react: Drive as you say, with large language models in autonomous vehicles,

Reference 85

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source=pdf_text observed=2026-08-07T14:02:58.361861Z digest=sha256:00a6b9b9d7a4a67ac739b89e908c22085f585d6197cdcbff4d52cd10cf5a7436

Observation fe7aab82-47f1-43fc-860f-10d3ec8f08de · outbound

This paper cites SafeDrive: Knowledge- and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects SafeDrive: Knowledge- and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models

Reference 86

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source=pdf_text observed=2026-08-07T14:02:58.453995Z digest=sha256:efce57b9c53d5048d69e042ddaa195d0552b9349941b5b41bbc7e4c0e6ab3675

Observation b9147da6-92da-4b44-8d0a-d3684d266fae · outbound

This paper cites Koma: Knowledge-driven multi-agent framework for autonomous driving with large language models,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Koma: Knowledge-driven multi-agent framework for autonomous driving with large language models,

Reference 87

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source=pdf_text observed=2026-08-07T14:02:58.566560Z digest=sha256:0c44857dd7078658b57a32d25c723d5e4730da17fdd7095b40cad87acc1359ab

Observation 8398f75a-5361-42d9-9f88-f5c20e7560c5 · outbound

This paper cites LeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects LeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking

Reference 88

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source=pdf_text observed=2026-08-07T14:02:58.722975Z digest=sha256:6d7cb8c6f19eea17c6b62309339bbecf22dc4ed09c65ab5da63bd18a110b2092

Observation ace78cf1-4abb-475e-8bf7-299784da8b66 · outbound

This paper cites Towards interactive and learnable cooperative driving automation: a large language model-driven decision-making framework,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Towards interactive and learnable cooperative driving automation: a large language model-driven decision-making framework,

Reference 89

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source=pdf_text observed=2026-08-07T14:02:58.748016Z digest=sha256:afc8c64e8c4912138f8db8849caddfb1fd50062032336b4c730713e3fdf1ca4f

Observation 6028f8df-0b6f-4b2f-9eb4-e6768ccdc293 · outbound

This paper cites Interact, Instruct to Improve: A LLM-Driven Parallel Actor-Reasoner Framework for Enhancing Autonomous Vehicle Interactions.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Interact, Instruct to Improve: A LLM-Driven Parallel Actor-Reasoner Framework for Enhancing Autonomous Vehicle Interactions

Reference 90

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source=pdf_text observed=2026-08-07T14:02:58.819226Z digest=sha256:70b46a396765308094a0ad86f6aa4905741354c090d9206fb780256f6d6e2b2d

Observation c52f52a6-4f4a-4739-a517-96602ba5cd5c · outbound

This paper cites CoT-VLM4Tar: Chain-of-Thought Guided Vision-Language Models for Traffic Anomaly Resolution.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects CoT-VLM4Tar: Chain-of-Thought Guided Vision-Language Models for Traffic Anomaly Resolution

Reference 91

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source=pdf_text observed=2026-08-07T14:02:58.917418Z digest=sha256:3a033c081d5b0828a9b0b916befa7f7efc2edc49246b3b1907bd5b4d1fb4b632

Observation 1db9f38a-e9e0-456b-9d23-ddc32585e5f6 · outbound

This paper cites Driving with llms: Fusing object- level vector modality for explainable autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Driving with llms: Fusing object- level vector modality for explainable autonomous driving,

Reference 92

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source=pdf_text observed=2026-08-07T14:02:58.972761Z digest=sha256:e65625ffc0f90b4b155e7104919c13a0dbfcfdb23629341f790edb1238a99507

Observation 6112b04b-b21b-42c0-8343-41bf91c9b765 · outbound

This paper cites PKRD-CoT: A Unified Chain-of-thought Prompting for Multi-Modal Large Language Models in Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects PKRD-CoT: A Unified Chain-of-thought Prompting for Multi-Modal Large Language Models in Autonomous Driving

Reference 93

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source=pdf_text observed=2026-08-07T14:02:59.049315Z digest=sha256:c68bbfaff0dfd5b30730b6bc11be8a26282c9dfe87d1d0f47c2f9d82f83f7981

Observation e7b23de2-57a7-4eb0-94da-306427ab069e · outbound

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

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Lmdrive: Closed-loop end-to-end driving with large language models,

Reference 94

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source=pdf_text observed=2026-08-07T14:02:59.152728Z digest=sha256:f0aecc91b04a80351b213c9dfc62ff24d33c1e7e268af50462fbc93ae275264f

Observation c137c517-49d6-4c2a-b82a-2f60997cb992 · outbound

This paper cites Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving

Reference 95

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source=pdf_text observed=2026-08-07T14:02:59.214181Z digest=sha256:b0bbfad1740ed998079e1f3c743d44603cd1a4342c570590a146487124434d35

Observation 7f82752d-79ba-4596-89fc-f95505f91d93 · outbound

This paper cites EMMA: End-to-End Multimodal Model for Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects EMMA: End-to-End Multimodal Model for Autonomous Driving

Reference 96

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source=pdf_text observed=2026-08-07T14:02:59.268872Z digest=sha256:7f7545253d1b73062440f2f0ded6548c4a52b9bb953b2104e071afae752981a5

Observation 1d5bae29-817a-4688-a364-a03aa25759e7 · outbound

This paper cites Open- emma: Open-source multimodal model for end-to-end autonomous driving,.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Open- emma: Open-source multimodal model for end-to-end autonomous driving,

Reference 97

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source=pdf_text observed=2026-08-07T14:02:59.381192Z digest=sha256:3f66a681b5b777e4765f3c667c35a960a2ff3fd551b289801182a987a4610e7b

Observation 054ed74c-2592-442b-a7a7-93def5e3ff10 · outbound

This paper cites LightEMMA: Lightweight End-to-End Multimodal Model for Autonomous Driving.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects LightEMMA: Lightweight End-to-End Multimodal Model for Autonomous Driving

Reference 98

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source=pdf_text observed=2026-08-07T14:02:59.475959Z digest=sha256:bdc8b9ac610ecdff8d7fc93d2d7e086ae81323a7ed1d93e665b82f9bbbed3320

Observation e290753b-d5b2-4504-8224-24a145bc65f5 · outbound

This paper cites ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation

Reference 99

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source=pdf_text observed=2026-08-07T14:02:59.550521Z digest=sha256:048b20e036ceb62642b38a8ce257f9639db2cb83ab2c4d1ce8c33b4088181e0b

Observation 20fec2c5-d5fd-4d98-a4a5-3e9820e0e38a · outbound

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

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Drivelm: Driving with graph visual question answering,

Reference 100

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source=pdf_text observed=2026-08-07T14:02:59.625136Z digest=sha256:7e4476c8aafd77aeebca3bd0b4c95db27884a7a7565abe83e5e7484efe38e26f

Observation c61f6775-56e9-4bcb-a934-453ab960b3a5 · outbound

This paper cites Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning.

Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning

Reference 101

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Pith citing papers

Observation bb544cc9-b712-435f-b5f1-ee1b4e55acd0 · inbound

A Survey on Vision-Language-Action Models for Autonomous Driving cites this paper.

A Survey on Vision-Language-Action Models for Autonomous Driving Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects

Reference 23

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Observation 8d37abe9-23ac-4080-ad9d-a0f790a35bc1 · inbound

SwarmDrive: Semantic V2V Coordination for Latency-Constrained Cooperative Autonomous Driving cites this paper.

SwarmDrive: Semantic V2V Coordination for Latency-Constrained Cooperative Autonomous Driving Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects

Reference 7

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source=pdf_text observed=2026-05-10T00:38:30.267653Z digest=sha256:e70a167035c92367d1947fc27c4d277b00f4b4aa7cdb589a3d1f2d38b20148e7

Observation 856e9142-c5c8-474b-941e-52bcb2c35059 · inbound

C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving cites this paper.

C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects

Reference 11

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source=pdf_text observed=2026-05-12T04:09:34.785664Z digest=sha256:52bddd8a5e985faa198eb9f129b66ff150150a3f0136b48eef02842730481114