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Paper Citation Record · LEDGER

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video

As of 14 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.23132.

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

pith.paper-citation-record.v1
2607.23132 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T03:34:39.148497Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

28 of 28 outbound references displayed

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  • unresolved28
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aef5fec3-e958-4966-936f-b574824c3de7 · outbound

This paper cites Abductive ego-view accident video understanding for safe driving perception,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Abductive ego-view accident video understanding for safe driving perception,

Reference 1

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source=pdf_text observed=2026-08-01T03:34:38.196543Z digest=sha256:dc8d0f56d2cb39b4e4554cfbc61b3736e717286752e13b5c54e31e59a186d5a7

Observation 5f14f2b4-ec7a-4ecb-bb9e-438734aff810 · outbound

This paper cites an unresolved cited work.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-01T03:34:38.234450Z digest=sha256:4a250a9555ecaa2c720fee236c4eea1148c6e3f9308a103b52b411f4b72e753d

Observation a080c081-8c58-4056-847d-d5edef49d3fe · outbound

This paper cites Updated estimates of potential traffic fatality reductions with automatic collision notification,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Updated estimates of potential traffic fatality reductions with automatic collision notification,

Reference 3

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Observation 23641fe9-bab4-40e0-8db5-0a759e5c7c19 · outbound

This paper cites ScVLM: Enhancing vision-language model for safety- critical event understanding,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video ScVLM: Enhancing vision-language model for safety- critical event understanding,

Reference 4

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source=pdf_text observed=2026-08-01T03:34:38.301350Z digest=sha256:45036302b252719107bfc8ed4a7237e04a7726a144456db5f11bbe4ef080d166

Observation 197a92e4-ed9f-4dc9-a7bb-b37f7edcb2f0 · outbound

This paper cites SUTD-TrafficQA: A question answering benchmark and an efficient network for video reasoning over traffic events,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video SUTD-TrafficQA: A question answering benchmark and an efficient network for video reasoning over traffic events,

Reference 5

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source=pdf_text observed=2026-08-01T03:34:38.374269Z digest=sha256:d382f7d328f77a081f1e48f424718a6fd44b99d666a287c440779018afcaa870

Observation 44b2eac1-5033-48c7-94f0-49f9a3900d2c · outbound

This paper cites SafePLUG: Empowering multimodal llms with pixel- level insight and temporal grounding for traffic accident understand- ing,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video SafePLUG: Empowering multimodal llms with pixel- level insight and temporal grounding for traffic accident understand- ing,

Reference 6

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source=pdf_text observed=2026-08-01T03:34:38.401752Z digest=sha256:d2a012211187463f288ff89949359ac83f4e61a63d2413bfa2fb40958756eaa6

Observation 3a1899a3-8763-412f-9b45-a851e90c876c · outbound

This paper cites CrashSight: A phase-aware, infrastructure-centric video benchmark for traffic crash scene understanding and reasoning,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video CrashSight: A phase-aware, infrastructure-centric video benchmark for traffic crash scene understanding and reasoning,

Reference 7

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source=pdf_text observed=2026-08-01T03:34:38.438992Z digest=sha256:3181514e927ba863167c6371570e0f30e1966fc5eb9c380ee74fd2c302ab4d15

Observation ff7d0814-5739-4f94-9fb7-4b938ca6e9f0 · outbound

This paper cites EchoTraffic: Enhancing traffic anomaly understanding with audio-visual insights,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video EchoTraffic: Enhancing traffic anomaly understanding with audio-visual insights,

Reference 8

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Observation 8168e751-5304-42e9-9dac-f858a43032b7 · outbound

This paper cites Driving with Regulation: Trustworthy and interpretable decision-making for autonomous driving with retrieval-augmented rea- soning,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Driving with Regulation: Trustworthy and interpretable decision-making for autonomous driving with retrieval-augmented rea- soning,

Reference 9

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source=pdf_text observed=2026-08-01T03:34:38.495949Z digest=sha256:6dcd26554cced9a9e52b2da95f9dfd9b6181c2f79fb00860629626ea3fa2c8d4

Observation dac1a7db-4bf1-4598-a47c-454e0e9c477e · outbound

This paper cites VRU-Accident: A vision-language benchmark for video question answering and dense captioning for accident scene understanding,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video VRU-Accident: A vision-language benchmark for video question answering and dense captioning for accident scene understanding,

Reference 10

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source=pdf_text observed=2026-08-01T03:34:38.532283Z digest=sha256:dec72b6ee470a959198d6be81a5250a494a6e41e28702c63e160f7714d3f8f06

Observation 4bdf6b72-ccce-43af-a88c-b1f8609bb29e · outbound

This paper cites GPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video GPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events

Reference 11

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source=pdf_text observed=2026-08-01T03:34:38.573004Z digest=sha256:f1b4dd0f0686d2b02f6cb3dc2a8b2f5cccdae7bc0ed8c363b5a374b91aade70c

Observation 973275f7-e5fe-4cc8-b3d2-78e0ed60173f · outbound

This paper cites From Detection to Action: A multimodal ai framework for traffic incident response,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video From Detection to Action: A multimodal ai framework for traffic incident response,

Reference 12

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source=pdf_text observed=2026-08-01T03:34:38.618484Z digest=sha256:46ddea9eab41b0c445e6081efb4c89ce06a5b8670164a6d8ce026e845a65b151

Observation 5626f921-d042-4b0b-8a7e-57b758d2901c · outbound

This paper cites AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model

Reference 13

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source=pdf_text observed=2026-08-01T03:34:38.636028Z digest=sha256:6484b87c86560409e50cb9ff059f94ccfa5dc89e100d0e7f9237053f819b55c0

Observation a448bf2a-3444-413f-8af1-57d715edc85e · outbound

This paper cites Use of a large language model to assess clinical acuity of adults in the emergency department,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Use of a large language model to assess clinical acuity of adults in the emergency department,

Reference 14

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Observation 1a74b376-8691-4256-8344-21569a8b65de · outbound

This paper cites Use of a large language model (llm) for ambulance dispatch and triage,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Use of a large language model (llm) for ambulance dispatch and triage,

Reference 15

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Observation b59216a7-98a9-4f68-b1ec-765ad0b01e55 · outbound

This paper cites DispatchMAS: Fusing taxonomy and artificial intelligence agents for emergency medical services,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video DispatchMAS: Fusing taxonomy and artificial intelligence agents for emergency medical services,

Reference 16

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source=pdf_text observed=2026-08-01T03:34:38.737247Z digest=sha256:2684867554ce4dc9c42f5bdbb4985e2b1f6cb5499c0acc509412af4359b4c9c0

Observation d7266a0f-e9ba-4d62-a248-0eb656138ca9 · outbound

This paper cites 105 of 1960, e-Gov Law Search, Articles 71, 71-3, 72, 117.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video 105 of 1960, e-Gov Law Search, Articles 71, 71-3, 72, 117

Reference 17

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Observation 1233adcc-8941-4976-b590-8b2ec2d800b0 · outbound

This paper cites 89 of 1896, article 698 (emergency management of affairs), e-Gov Law Search, https : //laws.e-gov.go.jp/law/129AC0000000089, 1896.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video 89 of 1896, article 698 (emergency management of affairs), e-Gov Law Search, https : //laws.e-gov.go.jp/law/129AC0000000089, 1896

Reference 18

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Observation dd34072e-2988-4df7-b667-e8026122cf70 · outbound

This paper cites an unresolved cited work.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Unresolved cited work

Reference 19

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Observation 01b5a81d-2d85-4f15-9548-d4945576e96f · outbound

This paper cites 1 (119-ban Ts ¯uh¯o Purotokoru), Ministry of Internal Affairs and Communications, https://www.fdma.go.jp/singi kento/ kento/items/kento121 05 119banprotocolv1.pdf, 2021.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video 1 (119-ban Ts ¯uh¯o Purotokoru), Ministry of Internal Affairs and Communications, https://www.fdma.go.jp/singi kento/ kento/items/kento121 05 119banprotocolv1.pdf, 2021

Reference 20

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Observation 68fd3c30-ee28-46e6-aa74-c2cac305d559 · outbound

This paper cites an unresolved cited work.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Unresolved cited work

Reference 21

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Observation c8f92f3c-8589-47bb-a50b-a8f119277864 · outbound

This paper cites an unresolved cited work.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Unresolved cited work

Reference 22

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Observation 7ef5598b-fb9a-459c-95c0-5b8229e9ccb6 · outbound

This paper cites Precise zero-shot dense retrieval without relevance labels,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Precise zero-shot dense retrieval without relevance labels,

Reference 23

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Observation 695f0438-fcee-4900-8812-808ac29f5f82 · outbound

This paper cites M3- Embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation,.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video M3- Embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation,

Reference 24

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Observation 94475419-52c8-4759-abe2-9ea88369fdfd · outbound

This paper cites Qwen3-VL Technical Report.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Qwen3-VL Technical Report

Reference 25

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Observation 54f650c8-7d37-4f37-9a8d-e34dc4521af1 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 26

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source=pdf_text observed=2026-08-01T03:34:39.078305Z digest=sha256:05c1194d9b35e05ac21f440760c02b2260622af2c0519cd7c2a1eb553f151bf9

Observation f72573c8-5d44-4bcb-b352-de10b12f0c51 · outbound

This paper cites Qwen3 Technical Report.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Qwen3 Technical Report

Reference 27

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Observation fb8c46ae-c586-40b9-86fa-2bc3a90bd166 · outbound

This paper cites Robertson and H.

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video Robertson and H

Reference 28

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source=pdf_text observed=2026-08-01T03:34:39.148497Z digest=sha256:2f23692f069f0bb96ed39eacb0d6489b04a0408bcdb6be9137c64706c18f1d01

Pith citing papers

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