Paper Citation Record · LEDGER

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference

As of 7 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2508.13439.

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

pith.paper-citation-record.v1
2508.13439 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:06:41.442311Z

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

verified exact2
verified fuzzy21
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 936649dc-d55c-40d7-8fbd-c6aa4954b01a · outbound

This paper cites Scenario Understanding of Traffic Scenes Through Large Visual Language Models.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Scenario Understanding of Traffic Scenes Through Large Visual Language Models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:45.207724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9366842e-7f78-4ba8-a8a1-f0bdb62c1076 · outbound

This paper cites Efficient Large Multi-modal Models via Visual Context Compression.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Efficient Large Multi-modal Models via Visual Context Compression

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T19:06:39.208373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eec74f74-9b2e-4857-b339-5f5a3564232d · outbound

This paper cites ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference ChatGPT is on the Horizon: Could a Large Language Model be Suitable for Intelligent Traffic Safety Research and Applications?

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T19:06:39.496604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1f62a71-9841-4d03-91dc-49584a31e9a4 · outbound

This paper cites A review of the effect of traffic and weather characteristics on road safety.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference A review of the effect of traffic and weather characteristics on road safety

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:45.029411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 185328ca-35d7-401e-988a-b2e7c93c4e9e · outbound

This paper cites Vision-Language Models for Vision Tasks: A Survey.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Vision-Language Models for Vision Tasks: A Survey

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:44.879107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation db72d94a-0012-4754-b855-0ed4acd11681 · outbound

This paper cites A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T19:06:39.724555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 102edaf9-45cd-429b-8cde-540c84fe98c7 · outbound

This paper cites A Survey on Multi-Agent Foundation Models: Progress and Challenges.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference A Survey on Multi-Agent Foundation Models: Progress and Challenges

Reference 7

Resolution: verified exact; raw_fallback, observed 2026-08-05T19:06:41.862078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2240394b-85ff-4ea9-8837-d951df6386bf · outbound

This paper cites Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:44.691821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c27416ce-9e68-408e-8dac-1e67add5d3dd · outbound

This paper cites ShareGPT4Video: Improving Video Understanding and Generation with Better Captions.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:44.506211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 210aebe7-a840-4270-a6d9-5fb78a97c384 · outbound

This paper cites Rehg, and Chao Zheng.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Rehg, and Chao Zheng

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:44.325010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61293e54-ebd2-473b-b829-9b9289335a06 · outbound

This paper cites Enhancing Vision-Language Models with Scene Graphs for Traffic Accident Understanding.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Enhancing Vision-Language Models with Scene Graphs for Traffic Accident Understanding

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:44.081026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 191c6cd9-36ea-4b95-93ac-8c395e2fa09b · outbound

This paper cites Ashqar, Taqwa I.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Ashqar, Taqwa I

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:43.922176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7e7c71b8-6d22-40d6-b23e-50790cd25da1 · outbound

This paper cites Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:43.621631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 52cb2594-0f0d-4415-83dd-264f15da2307 · outbound

This paper cites VideoMultiAgents: A Multi-Agent Framework for Video Question Answering.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference VideoMultiAgents: A Multi-Agent Framework for Video Question Answering

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:43.382989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4a308ec-3ab5-4107-ac8d-5d384646474a · outbound

This paper cites Shivakumar, Dan Roth, and Camillo J.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Shivakumar, Dan Roth, and Camillo J

Reference 15

Resolution: verified exact; raw_fallback, observed 2026-08-05T19:06:41.677649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a451852f-7e64-4a44-9354-189de1c1daf1 · outbound

This paper cites Bhooshan and K.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Bhooshan and K

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:43.298222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1d0490ce-e8e0-4708-9e02-6c41e0abed30 · outbound

This paper cites Vision-informed Safety and Transportation Assessment (VISTA) , 2025.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Vision-informed Safety and Transportation Assessment (VISTA) , 2025

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:43.232501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08b3c7a1-90ff-421f-9d2d-7f4f5907bf50 · outbound

This paper cites OpenAI (2023).

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference OpenAI (2023)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:43.051018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 556069e8-37be-4fe1-ad3a-2ce444c17227 · outbound

This paper cites an unresolved cited work.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-05T19:06:42.900037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 924a0206-15b3-45a8-aab1-216ae749bd55 · outbound

This paper cites ChatGPT (o3‑mini).

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference ChatGPT (o3‑mini)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.785064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 10fd8c9f-6c12-4ecd-85d9-65be8058da37 · outbound

This paper cites Qwen2.5-VL Technical Report.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Qwen2.5-VL Technical Report

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T19:06:40.884973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 698f4ccb-4363-45d8-9f24-fe68040a9ecd · outbound

This paper cites Bleu: A method for automatic evaluation of machine translation.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Bleu: A method for automatic evaluation of machine translation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.721109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6d50fed2-3efd-49df-a4e0-f5c7ec71a187 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with human judgments.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Meteor: An automatic metric for mt evaluation with improved correlation with human judgments

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.639493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 34dd9284-d219-4bfb-b362-95818545a3be · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Rouge: A package for automatic evaluation of summaries

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.527904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ecbbb065-be75-493d-a050-a56edc59ac59 · outbound

This paper cites Lawrence Zitnick, and Devi Parikh.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Lawrence Zitnick, and Devi Parikh

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.422274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 793b5bd7-7512-4156-aa6f-4f0a7727f25a · outbound

This paper cites CityLLaVA: Efficient Fine-Tuning for Vision-Language Models in City Scenario.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference CityLLaVA: Efficient Fine-Tuning for Vision-Language Models in City Scenario

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.321854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4ab90a6-e744-4a20-bd45-5181132b3f71 · outbound

This paper cites Parameter-efficient fine-tuning of pretrained language models: A survey.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Parameter-efficient fine-tuning of pretrained language models: A survey

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.197845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3a6c846b-46bb-4041-b21c-e2b167226b12 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen.

Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:06:42.053555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.