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Paper Citation Record · LEDGER

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2606.25629.

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

pith.paper-citation-record.v1
2606.25629 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-25T20:56:50.013581Z

measured 24 of 24 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.

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

24 of 24 outbound references displayed

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  • verified fuzzy0
  • unresolved21
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23ec42ce-27f7-4ab9-bae4-5100a8bc7b5d · outbound

This paper cites Few-shot testing of autonomous vehicles with scenario similarity learning,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Few-shot testing of autonomous vehicles with scenario similarity learning,

Reference 1

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:a355e78d4c6a993b49d68b13506575e4770ae158ac0f48b1be9575a694ac2be6

Observation 3711876c-1a90-4bf4-9cea-816befbdb36b · outbound

This paper cites Lead: Learning-enhanced adaptive decision-making for autonomous driving in dynamic environments,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Lead: Learning-enhanced adaptive decision-making for autonomous driving in dynamic environments,

Reference 2

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:52fab47ac7867380eb3e147771a50e806b5c42932fad152eb86d7dd56b68a939

Observation 4a7c3c87-4a4f-4471-a522-bd7cd59cfa6d · outbound

This paper cites Openbench: A new benchmark and baseline for semantic navigation in smart logistics,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Openbench: A new benchmark and baseline for semantic navigation in smart logistics,

Reference 3

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Observation a5dea7ec-b1ff-44cb-b449-91b314e673a6 · outbound

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

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving

Reference 4

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arxiv_id, observed 2026-07-04T20:00:07.809385Z

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Observation 01e90f8e-1f8d-459d-bb41-20f70be7d04d · outbound

This paper cites Hey robot! personalizing robot navigation through model predictive control with a large language model,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Hey robot! personalizing robot navigation through model predictive control with a large language model,

Reference 5

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:d94fbd417fa2aab897c70fced366710ff37e36244aeeb17b6eb6a8093f09fa8c

Observation be909b68-23cf-41e5-8076-417750b5c50f · outbound

This paper cites Dilu: A knowledge-driven approach to autonomous driving with large language models,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Dilu: A knowledge-driven approach to autonomous driving with large language models,

Reference 6

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:a038836edee582c69afd13ff3a4bcf16fb9e37f56bdc42b236dcb212f42d7738

Observation 0119cd84-9b13-4b3e-9f42-27bf7316902f · outbound

This paper cites Rda: An accelerated collision free motion planner for autonomous navigation in cluttered environments,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Rda: An accelerated collision free motion planner for autonomous navigation in cluttered environments,

Reference 7

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:b167523a51e138f41b2ac08891d04537ce5dd2c3a013ed66c79937cf332b0cb8

Observation 623af93a-869c-4d44-86c2-00d95eb5af16 · outbound

This paper cites Model predic- tive control for autonomous ground vehicles: A review,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Model predic- tive control for autonomous ground vehicles: A review,

Reference 8

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:0ab18d942aa5fb760bf68daf06b5e5d786d4a852d389220b1daf917062cc9d1e

Observation 97a80ed3-6c8d-4900-9630-7833654abfa1 · outbound

This paper cites Drivegpt: Scaling autoregressive behavior models for driving,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Drivegpt: Scaling autoregressive behavior models for driving,

Reference 9

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:9cfb5d08deb613b6fb305f01bd3174fe9fd1da8848ad7c6985745a8209c76646

Observation fea87c73-55ec-4fec-bbd4-caa6757b2d04 · outbound

This paper cites Enhancing autonomous driving systems with on-board deployed large language models,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Enhancing autonomous driving systems with on-board deployed large language models,

Reference 10

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:520e2c5f49d4266c7fb17e75e8209c67005f06949ad68824a1e222a93145323e

Observation b5f31a7c-db71-4ee9-8f0c-d805dba5a4fe · outbound

This paper cites System-1.x: Learning to balance fast and slow planning with language models,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations System-1.x: Learning to balance fast and slow planning with language models,

Reference 11

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:b7c4ede73d3dab1209628208c377b274456826b79dc94ab772a54e37a97c07c3

Observation 2147368a-7ea5-438c-b698-631871075a16 · outbound

This paper cites Opportunistic collaborative planning with large vision model guided control and joint query-service optimization,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Opportunistic collaborative planning with large vision model guided control and joint query-service optimization,

Reference 12

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:3c1e72aa42b529bac308973042480c2bfa52cdfb5e9211e977602484056625ba

Observation 461b7e25-a597-4161-9c58-67ff6edd8b46 · outbound

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

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Carla: An open urban driving simulator,

Reference 13

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:8410955bbf60e3c1db40317787ab72c532845056ee049730a8e207d3c541b900

Observation 75206bf4-6aab-453b-8091-1b26e3cfb5d6 · outbound

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

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Lmdrive: Closed-loop end-to-end driving with large language models,

Reference 14

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:a302ffb9a08c6532eb427cf8a10893ccc894a3ba8a9f36b7d0c662af266ad95b

Observation cf063272-8f24-4192-b731-5512808e40aa · outbound

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

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Drivevlm: The convergence of autonomous driving and large vision-language models,

Reference 15

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:334bec590a4a2a3727ba02508e8084b39659ee9dc09c4880c1bcf634a3011f39

Observation 52235da0-aa98-411d-b088-d2d4a709cbf4 · outbound

This paper cites Rilaas: Robot inference and learning as a service,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Rilaas: Robot inference and learning as a service,

Reference 16

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:5fc5f257f2631c516c06206a3383d1ca892f8726dc27e3aa75876a8d157376ac

Observation 2a464e99-7d23-4a20-8790-ef8404adb904 · outbound

This paper cites Vlmpc: Vision-language model predictive control for robotic manipulation,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Vlmpc: Vision-language model predictive control for robotic manipulation,

Reference 17

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:807dfc5bbca40a97d494364fe552169729d41950037000c18b52457c1cdacdc4

Observation 3bb5100b-ffa2-4bf8-9976-6e785730d69c · outbound

This paper cites Adadrive: Self-adaptive slow-fast system for language-grounded autonomous driving,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Adadrive: Self-adaptive slow-fast system for language-grounded autonomous driving,

Reference 18

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:5b0874634e7386218f3a83abd5e66fdea5ef4f0419f723746154ca3dcdf10c12

Observation 523a77fe-a125-4c40-96f3-18b3555bc298 · outbound

This paper cites Beamvlm for low-altitude economy: Generative beam prediction via vision-language models,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Beamvlm for low-altitude economy: Generative beam prediction via vision-language models,

Reference 19

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arxiv_id, observed 2026-07-04T20:00:07.804918Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:3d7b48c57cf9ac0f221d3c594c0d2c7f8cafde0591c47575d85323c8e274aeba

Observation f63b9792-0bce-4835-b187-d70f41c3bf0e · outbound

This paper cites Epsilon: An efficient plan- ning system for automated vehicles in highly interactive environments,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Epsilon: An efficient plan- ning system for automated vehicles in highly interactive environments,

Reference 20

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Observation f24e60e3-fe8b-45a4-897b-228bfa2f9252 · outbound

This paper cites Planning- oriented autonomous driving,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Planning- oriented autonomous driving,

Reference 21

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source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:fb38fddd5ec3a373eb0a03c3ccdc71b056de8b611e9d12d52c0554f55e9fce30

Observation f5c6712f-2f5a-4be1-b5a9-8b7ab4201ca3 · outbound

This paper cites Rt-2: Vision- language-action models transfer web knowledge to robotic control,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Rt-2: Vision- language-action models transfer web knowledge to robotic control,

Reference 22

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Observation d30e808e-6182-416b-821b-4eb6e3815063 · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations LoRA: Low-rank adaptation of large language models,

Reference 23

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Observation 1f2de562-bf09-4ec7-bf7f-3be3a9eb6ca5 · outbound

This paper cites Qwen3-VL Technical Report.

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations Qwen3-VL Technical Report

Reference 24

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local_arxiv, observed 2026-07-04T20:00:07.812233Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-25T20:56:50.013581Z digest=sha256:077d5ccf55f2920c0937075955403ac62aa98ce4b75100975479c0eaaa462a30

Pith citing papers

No inbound Pith citation observations are available.