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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 7 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 2 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 62 of 62 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T17:35:21.127740Z

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:16.942543Z digest=sha256:35f06bc36341ff20badacf90a2c01aaeac55906b2fa9c80ad6f87eadc577e9dd

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.022364Z digest=sha256:2724e56cdd9eb03454f33a2ef1ee7986cdf32598fc72a19aee5ccba45a7e4750

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.111543Z digest=sha256:9bfc67cb6b2b29b9d0cf84d718303e6c6f63a433bd9aa52c999bdf50864f98ba

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.218704Z digest=sha256:97c73d81e4571c24b1b2e712bd5b26495a9700f86f63ec1ad76501c1b9fbec94

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.330657Z digest=sha256:46cfc88bc2e028d45cbcc439968e1ab81760da8c42f700abc2e9b3d49d69b98e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.437683Z digest=sha256:08524c2594d2ea538c12139c122f6ca45e1f958a4af6be37a9e6a899d5bccdb0

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

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:17.517015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:17.517015Z digest=sha256:a1b9d5ad389de726992a765667494e1399038c5b2b195a376f7d213da78f463e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.600523Z digest=sha256:7be20a714ef38232537674cb15a293e0a4a3ab9976715b8a5481859981448d3f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.689392Z digest=sha256:c4a5389d963b5e2857a23f304578aa21bff8e6944e2af45efc300676e7d4305f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.800982Z digest=sha256:cb41b05936647369348628799e1ecd3ea3a66402bf8702c94d723849b9a25a9f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:17.909996Z digest=sha256:5dddc2ae3a298227aee6ed753d9329dcf953259dd6f034b39d34025659398f5c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.022005Z digest=sha256:d3f532da5180aa19ff5ea6c8a82669bcf984938552cce7c65b29317fb8d913e9

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.125064Z digest=sha256:ff3a3d9de7c273130aec53b6b03c13ad428a44b13b8daa302d50505035192db6

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.186770Z digest=sha256:2e6f1979d26dcbeb85e1ef955e2fa6ad8fb8e80652d43a1f25a6e1dc50ff8da5

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.272753Z digest=sha256:e4ff8640e289678ef04d08c95888a2a4201a518e971e86227483751ded0aa373

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.348432Z digest=sha256:aa8d9c0ee0f26d030dc2eb5370a48fb924d5195c0553ba60f39a715a6df4f06b

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.425591Z digest=sha256:13687fef8012b905208914eefaabd2a37aacd8fbce8d47a1b2da049677ebc0d7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.548662Z digest=sha256:225da0f0c268c39193acd174e365d89b3e5ed7dcbc8980ddedb70f44043bdbe1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.636237Z digest=sha256:e62a10de6dafd62f9041364bdc920002db0ed3fc91d33fb9f9f943e3d062de24

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.710504Z digest=sha256:d6d9c7201c6b8f0ffc01cb9e2a881b086d958882c95a5dcc1a93c1c0344a68fd

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.798889Z digest=sha256:fb9f24dc78c8b93d8ed6c2198284ecde9f2f93c033c6248c69b78df4e71067ee

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.911341Z digest=sha256:13afb75684be8f92648d14f5b9b9b3b9dc28b01e7a9732d4a1b76c3fea4c4fe2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:18.993981Z digest=sha256:fd83ae239c5a980abb940987df18edd1e4bf45de7bb79ceae53d2a2c7c450a51

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.052543Z digest=sha256:fb073e805252c07c73995a9fbf5391cbcf0bf832e08d461f3e55924195ea8a1c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.128073Z digest=sha256:e866ed0853e8814ec7f471d26f1330c0d3ed979fa8675a7e83e82ec7e1e9c9e3

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

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:19.247609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:19.247609Z digest=sha256:0bd1c3257a21338e1326c6127c4437bdb46b9193b2e932195a99d673d8413534

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.364244Z digest=sha256:edd4c842b29f43166a6516a08c9af8c11300d71bb6e264ecd13b4663a4d5ffc4

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.516224Z digest=sha256:80beba3f3c4b099325eeec3a1ab9a95c5c0557f3cc901103e448e7965823dcd9

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.606333Z digest=sha256:9161f77efb0b40ddfd732bf2f248462c582cfa7787c74fabaf0096159fd0acdc

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.720139Z digest=sha256:54a66c51e4d4fe66e61362ecd5477e35738dd5e344c7f0e392bea7067d4043b3

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:19.922706Z digest=sha256:85c28177426410ba65476fcc2ba131f7d72a10ec8e3055c108813deba83be49d

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

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

source=arxiv_source observed=2026-08-07T00:40:20.061102Z digest=sha256:84c5debaaff8a35b4df035fd6798cf739d3ae961bb51ff76c7df76ed489e159e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.196513Z digest=sha256:59a34ccb0e40247be05c35b10c555cd5efe40ceb1f6c65d20faf9bdbac37cdf4

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

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:20.308443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:20.308443Z digest=sha256:4e978a1845c226557a99125298c3115ab3b230a14b3c5427b77be772563a7989

Observation 52eff9a0-fe42-449c-a5e9-e74d19d18e67 · 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 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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.476535Z digest=sha256:44ba56b047c8d3a43b10ffd263270fc53d755b73148e46c487e20579b927ea22

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.613765Z digest=sha256:81e22264baa762d6400e1051755ae2b992cc300f30a357c5692c2af238020014

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.679222Z digest=sha256:11d1d78bcac36c59349242c1cbf6f2602546e3c2918d27b6db39f152ae4c9ed1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.749446Z digest=sha256:7b8812da2281150d9cd3a1224c56757987f152d68803ce872fd561aee447a05f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.782562Z digest=sha256:ba287f9627f977743b4acd0c85c2236ec7b38daf57a348f3366491d9d38d4303

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.831740Z digest=sha256:641cd791680e2a347c98548bdf93c05de2cec1913c9c4c4800857afa78994333

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.887357Z digest=sha256:9b6164ccb14b069074917dd9491d9f06c450c8bd47c646cc8bf1d782cc7c70e2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:20.951704Z digest=sha256:62bfafd956505b3e86e2fa1709cb69b190300bc3abc299de5644cdd3f5f85d3a

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:21.048210Z digest=sha256:13eb49f6e294e34dcf7e8831ed6d5e838cc60bb148f70c4f3261073d11b7676d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:21.129195Z digest=sha256:c258a64ff84d0cc6241a6d65988eb84aac4bfd9c5e2ea33be4b14627ed58c56e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:21.198401Z digest=sha256:b28e8d1d28824ca5c3e9cf2b36532b50abbb2943bce7ce927f9a1db134684935

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:21.272736Z digest=sha256:65ad59b7e6a4320a26bf9cf9bf3025a6a6b887cd6385d4a8bb05187f7e1b3507

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:21.346121Z digest=sha256:66e0d3c466d39046b4df29627c930e59b3e250f18a2c5e0898e0a314464793f1

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.

source=arxiv_source observed=2026-08-07T00:40:21.448178Z digest=sha256:70b0aea2d2783e0fa090336685946e602eeb0359e1446bce6b086e516f25e6f7

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

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.

source=arxiv_source observed=2026-08-07T00:40:21.580845Z digest=sha256:3338f923f2955b3b1c650aafcfd494cebb9c78e796cdb0729b5032826d4f20ee

Observation e94af15b-1f73-4d30-9e12-64b78bb516a0 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:40:23.600015Z

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.

source=arxiv_source observed=2026-08-07T00:40:21.681019Z digest=sha256:cde935e6a670e6a775396392b4b5a05b71a46456365a610e3f1926c6615b83da

Observation c99d7f94-67c8-4ae7-a494-9ab5bb9aa5db · outbound

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

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.

source=arxiv_source observed=2026-08-07T00:40:21.847369Z digest=sha256:ce252ad0a05f7ff97ede0a707b6e33aad52c23e09f4e5a6ca3595dab1dc05bc3

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

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.

source=arxiv_source observed=2026-08-07T00:40:22.015176Z digest=sha256:e8bf1d5fe4f4ad2784f8498cd3d4d9c456e5a075ce3a0c324f76481bc117e952

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

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:22.025168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:22.025168Z digest=sha256:281d8474aa4d3504a3836033633821203f2c91bf13fbbd9909b626528125700e

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

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.

source=arxiv_source observed=2026-08-07T00:40:22.074566Z digest=sha256:ad3eca1455776f545585aec2637f31461adbd201c4f26d4fb269d0b4eed270a4

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

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:22.191430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:22.191430Z digest=sha256:f2df3aeb23f3d6204507e598a59c4e93eb3851b0fb8d9302c383943cf9b89407

Observation ac6af2dd-7905-4793-b791-1cf873b1cb59 · outbound

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

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.

source=arxiv_source observed=2026-08-07T00:40:22.248540Z digest=sha256:bb45dd170c4f1a8c298c2cb078b75ab79c46804c30e808cb01d1757028c725e6

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T00:40:22.280043Z digest=sha256:fcf10fb7265133258a6960de8e697ff7fb03eecfcc4b64b1ad64dc02a266d8e7

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

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:22.334354Z digest=sha256:05ae56d594026cfec277f04ff024c4b885fc45f828a2bc8f6f0c693af414102e

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

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

source=arxiv_source observed=2026-08-07T00:40:22.369967Z digest=sha256:19eb173c7b2f19c4cc27e29bfb3531e918d5c51841b5ebe11d46e10814549f27

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:40:22.399701Z digest=sha256:39fee62ce7f612b347ff878b57e57a2854c02bf94b0d91a278e606bafa5c9a41

Pith citing papers

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

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.

source=pdf_text observed=2026-06-28T17:35:21.127740Z digest=sha256:2991014c17905dc13038d283ad6daa348062e7cb080d2ae056acffb6dd740c72

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T15:48:39.837630Z digest=sha256:6b5ab60ec91da9cc29a7b5ed391534ef68c1de18a517bffbf4dceb7a734dac84