Paper Citation Record · LEDGER

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol

As of 18 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 3 inbound Pith citation observations for arXiv:2506.13068.

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

pith.paper-citation-record.v1
2506.13068 v2

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:22.399701Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:26:39.618536Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T02:37:34.582129Z

Reference resolution

60 of 60 outbound references displayed

verified exact1
verified fuzzy24
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2284ccdc-720f-4bda-bc84-561b7c7977e3 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:31.571674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 57522c89-02c8-42a4-86eb-ecf3f3cf6baf · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:31.427553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ed0dc1fe-ce68-4c6f-b5d9-4a5e43fc9558 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:31.266655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e2cd9198-bfcc-4c78-9604-ab3ddf896dcc · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:31.018064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5dd42a6a-52c9-41b3-8218-1cd62c3761d2 · outbound

This paper cites and Macharis, C.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol and Macharis, C

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:30.752244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5f1f2414-6ace-4e78-b46c-830a8571e557 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:30.488003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 626fec08-1d7f-4c9d-8c7b-0b07572592e1 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol On the Opportunities and Risks of Foundation Models

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37501f18-fcec-4776-aac1-3fe5c1fea7ea · outbound

This paper cites C., Poschmann, P., Werner, J., and Zarnitz, S.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol C., Poschmann, P., Werner, J., and Zarnitz, S

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:30.249639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e60bd66a-8c50-444f-8b34-1dd3d55a87f7 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:29.926577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8cbdf526-237e-49f4-a938-0a27bad9f772 · outbound

This paper cites L., Jain, R., Emami, P., Wadsack, K., Ding, F., Sun, H., Gruchalla, K., Hong, J., Zhang, H., Zhu, X., and Kroposki, B.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol L., Jain, R., Emami, P., Wadsack, K., Ding, F., Sun, H., Gruchalla, K., Hong, J., Zhang, H., Zhu, X., and Kroposki, B

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:29.688161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 66364a53-920a-470c-868a-e9631f1238db · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:29.489787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fe4527af-1b9c-4586-a460-96449a832fd9 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:29.166609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e1391804-c642-4641-83aa-5c5a653afbb5 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:28.949920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7d410999-9b39-423f-90ba-2083442e5af1 · outbound

This paper cites and Sinha, D.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol and Sinha, D

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:28.733246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 02e1dfaa-7225-4e05-a3b4-1a59361fb742 · outbound

This paper cites J., Foropon, C., Tiwari, M., and Gunasekaran, A.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol J., Foropon, C., Tiwari, M., and Gunasekaran, A

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:28.477147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aff5b3b6-1196-4c35-8764-32f0b3207095 · outbound

This paper cites and Weiss, G.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol and Weiss, G

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:28.228862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 19081cda-92c0-4b07-ad95-58e06d9ad713 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:27.859228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63f82a3c-2890-49ea-8211-d5cd468b6fbc · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:27.530317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 91ef5012-67ee-464e-a4f4-e548e9641cac · outbound

This paper cites S., Jernegan, L.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol S., Jernegan, L

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:27.308908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ec1b5408-af2b-4905-9e49-391608b2d998 · outbound

This paper cites F., Connor, D., Fotheringham, A.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol F., Connor, D., Fotheringham, A

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:27.089131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 820cf74f-7836-4cf3-9d76-150417264cde · outbound

This paper cites From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol From Pixels to Insights: A Survey on Automatic Chart Understanding in the Era of Large Foundation Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:40:22.627390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 280abfe8-4ab9-452c-ba1d-17fd0ec054ef · outbound

This paper cites Parameter-efficient fine-tuning (peft) — hugging face documentation.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Parameter-efficient fine-tuning (peft) — hugging face documentation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:26.941169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0233b7cc-7477-421a-af16-367cf2ce3299 · outbound

This paper cites Supervised fine-tuning trainer — hugging face trl documentation.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Supervised fine-tuning trainer — hugging face trl documentation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:26.790725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8f0b810-ed04-478e-a9b7-44e8b6d6966d · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:26.661133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5f05f6cd-a565-4508-8016-f83b00ca330b · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:26.518755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 73cd4a34-ba39-4e2c-9868-f873f4f20f5a · outbound

This paper cites Advancing Multi-Agent Systems Through Model Context Protocol: Architecture, Implementation, and Applications.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Advancing Multi-Agent Systems Through Model Context Protocol: Architecture, Implementation, and Applications

Reference 26

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Source-reported events for the cited work

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Observation 774759bf-6ec7-42d5-8333-12ec04df5214 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:26.357042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f473c0de-8ae2-484c-95be-47aa06feafdb · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:26.195410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 88f356d8-c798-46d9-b3fb-a14f1367c319 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:26.069617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 96e7a52c-6851-4a3d-af1f-dc10fe32fae5 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:25.929551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6796ae1-569f-4a45-8b1a-65717f8fc8e9 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:25.815489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 94108e58-b19e-4ce1-960d-60a571f3633d · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:25.697766Z

Source-reported events for the cited work

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Observation 2530c08e-3c09-4c7a-88aa-a92988165f3e · outbound

This paper cites I., Sathvik, A.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol I., Sathvik, A

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:25.602111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6e2a2bd-af5e-4642-b880-868890f8f630 · outbound

This paper cites ClimaX: A foundation model for weather and climate.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol ClimaX: A foundation model for weather and climate

Reference 34

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Source-reported events for the cited work

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This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:25.507407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c8819070-b297-40e2-8786-d5cb06f47444 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:25.397199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1bab224f-ec04-4627-89d0-7dc4ea805e95 · outbound

This paper cites and Mac \'a rio, R.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol and Mac \'a rio, R

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:25.266211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6363a46c-09c3-4a02-bec3-9eca97f229ba · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:25.161623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 673537e4-9a9a-4a02-90ce-b2d0e1962e27 · outbound

This paper cites and Gecan, R.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol and Gecan, R

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:25.024516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation abba4fa2-db06-4db6-8bf9-e6dca4efe8c1 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:24.872839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 190a3df7-c4e6-49f4-8739-4f7ad9488ac7 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:24.717597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb28d2fe-a284-418f-a3d0-36b66630b495 · outbound

This paper cites C., et al.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol C., et al

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:24.512553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 426f5c5e-6c59-4e1e-ac51-4be73929158e · outbound

This paper cites A., Camur, M.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol A., Camur, M

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:24.396004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6a6a1919-44ff-45b2-8d43-3210c9da57d4 · outbound

This paper cites S., Iqbal Nur, H., and Pertiwi, A.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol S., Iqbal Nur, H., and Pertiwi, A

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:24.283259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f927117-563b-4add-a434-fdb2811a01c6 · outbound

This paper cites Department of Transportation , F.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Department of Transportation , F

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:24.145516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9498c0aa-a496-43ac-a169-095a617045a5 · outbound

This paper cites A., Gehlhoff, F., Dogan, A., and Fay, A.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol A., Gehlhoff, F., Dogan, A., and Fay, A

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:24.035833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4a830062-f6fb-43fd-9310-1d7e4194adae · outbound

This paper cites M., Glassy, E.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol M., Glassy, E

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:23.861376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 93ddd1c5-c56b-42cc-93df-9c251c299b4f · outbound

This paper cites V., Zhou, D., et al.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol V., Zhou, D., et al

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-07T00:40:21.448178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8463484-1be3-4c70-b0b2-8cc907f684e1 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:23.729744Z

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This paper cites A., Ravulaparthy, S.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol A., Ravulaparthy, S

Reference 50

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This paper cites B., Sorensen, H., Nugent, P.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol B., Sorensen, H., Nugent, P

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:23.447086Z

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Observation 01cfae1d-ed82-4548-9700-5d75cb497971 · outbound

This paper cites J., and Omitaomu, O.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol J., and Omitaomu, O

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:23.311110Z

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Observation 67f694e8-36cf-4f30-845b-338033a1029e · outbound

This paper cites Leveraging Generative AI for Urban Digital Twins: A Scoping Review on the Autonomous Generation of Urban Data, Scenarios, Designs, and 3D City Models for Smart City Advancement.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Leveraging Generative AI for Urban Digital Twins: A Scoping Review on the Autonomous Generation of Urban Data, Scenarios, Designs, and 3D City Models for Smart City Advancement

Reference 53

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Observation dcfd61fd-e594-4b12-bea1-2863cfd6ea32 · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:23.174688Z

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Observation 86bd9022-670d-4ad0-aecc-e59e2f22fd59 · outbound

This paper cites GenAI-powered Multi-Agent Paradigm for Smart Urban Mobility: Opportunities and Challenges for Integrating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with Intelligent Transportation Systems.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol GenAI-powered Multi-Agent Paradigm for Smart Urban Mobility: Opportunities and Challenges for Integrating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with Intelligent Transportation Systems

Reference 55

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This paper cites T., and Huang, G.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol T., and Huang, G

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:23.049198Z

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Observation d3d5afcf-68c0-4197-8519-1c0a8ef874ba · outbound

This paper cites C., Supriya, Y., Srivastava, G., Maddikunta, P.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol C., Supriya, Y., Srivastava, G., Maddikunta, P

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:40:22.918850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ff71a4f4-6420-43c0-820d-5a2fb1a02fe9 · outbound

This paper cites Scientific Large Language Models: A Survey on Biological & Chemical Domains.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Scientific Large Language Models: A Survey on Biological & Chemical Domains

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T00:40:22.334354Z

Source-reported events for the cited work

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Observation 5b4c6ae0-d287-439a-9d8e-6ce1e693383a · outbound

This paper cites an unresolved cited work.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-07T00:40:22.782857Z

Source-reported events for the cited work

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Observation 9529956f-d3cf-4215-939a-1a54c248b0e7 · outbound

This paper cites Data-Centric Foundation Models in Computational Healthcare: A Survey.

Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol Data-Centric Foundation Models in Computational Healthcare: A Survey

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T00:40:22.399701Z

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Pith citing papers

Observation 38959b42-05e9-4497-a149-5b58194f371f · inbound

Generative AI as a Pillar for Predicting 2D and 3D Wildfire Spread: Beyond Physics-Based Models and Traditional Deep Learning cites this paper.

Generative AI as a Pillar for Predicting 2D and 3D Wildfire Spread: Beyond Physics-Based Models and Traditional Deep Learning Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol

Reference 24

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Observation 1814dfb4-2ef3-4ae0-9d73-bbd9acba5854 · inbound

Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support cites this paper.

Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:14.232189Z

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Observation f189624c-aca9-4b9e-8d52-e28b7a7aad62 · inbound

Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering cites this paper.

Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering Towards the Autonomous Optimization of Urban Logistics: Training Generative AI with Scientific Tools via Agentic Digital Twins and Model Context Protocol

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T02:37:34.583750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.