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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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=sha256:929966f48d7b99c4b942344e7d6f701ddb7a8c5ea2a1103b66ce24aecd55fb9c

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=sha256:8c0f3d541f6097fb04685fd26f4911d81834a62cb728922525952f836789a823

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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source=pdf_text observed=2026-08-01T03:34:38.260251Z digest=sha256:15e3cf7a6ba19bb4276df4509284073fe4aa1f9a6bcd16b835d42f2d3fb3d9cd

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:ee6af7c31808e4d4c21492ed155c2710eebec669d6c7d02342390826cac17729

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=sha256:8e81c439f525b13e71d695be75588beb6d204645843c7f6f6e95589e6d967e83

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:da97d536a4c261bb62ac5dc21ea4b6309a0232241db2750d5a03e6cab0038f17

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=sha256:3e3e3c20154fe3d62ec7dbce0cc26953e8990f3975ed21b5d76df35b13610f0b

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:f01e5d74f5d069703f5c9d8d1838f27a37a7aaece57c7e9cdd5e2d1f12885477

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=sha256:209907981352244a8f848adc30d4b229f2962a86faa3d25126bd35bbdbd58528

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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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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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=sha256:1b7f53aaf23b3fc460a7fc68ea1ef57ad135e4a90b40fd5c21aec4f588b57532

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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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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source=pdf_text observed=2026-08-01T03:34:39.042577Z digest=sha256:45dedbd6fca3cc582dbfc45d14b6e37ed6bc392d3e7737ca866d4a9e6c307058

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=sha256:8011773fc64e5917e618321e6b48c1608e10a3a59556d2b3995a6041612c7924

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=sha256:941f2227c1b606ceb8d8f367ab9fd5fdf2c43ae9827373ed871698f1c8d90115

Pith citing papers

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