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Paper Citation Record · LEDGER

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework

As of 17 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2501.00051.

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

pith.paper-citation-record.v1
2501.00051 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:52:11.073449Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:15:57.359300Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T11:15:57.628744Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact1
  • verified fuzzy33
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6d67fca7-d279-4ddc-81ae-55f3ae0e90a2 · outbound

This paper cites Machine learning based digital twin framework for production optimization in petrochemical industry,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Machine learning based digital twin framework for production optimization in petrochemical industry,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.714684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.918974Z digest=sha256:aefd04f4e75e841d6c05cc8c65d2c3c1e677d9681070873bb78798d6a15c0ee6

Observation cf8e51be-ee71-45c1-b323-3a3be1d2de8f · outbound

This paper cites The convergence of digital twin, iot, and machine learning: transforming data into action,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework The convergence of digital twin, iot, and machine learning: transforming data into action,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.703395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.923434Z digest=sha256:3d19da5659b8ecf5c3ef82de04fe83b5df97cda15417278b579b5251755364aa

Observation 54e87b10-24c9-48e7-851e-b460d1cd5572 · outbound

This paper cites The role of ai, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework The role of ai, machine learning, and big data in digital twinning: A systematic literature review, challenges, and opportunities,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.691968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.927121Z digest=sha256:38124d3512adf9808a074969839d4bb68253f87c2d4f88c7cb7d71da41da4774

Observation 32c90539-a5bf-41de-afa1-4003f3a046be · outbound

This paper cites Developing Digital Twins for Earth Systems: Purpose, Requisites, and Benefits.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Developing Digital Twins for Earth Systems: Purpose, Requisites, and Benefits

Reference 4

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verified exact
local_arxiv, observed 2026-08-10T23:52:11.264949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.931160Z digest=sha256:64cf834fed47b3ea319645ab959b7af745347daeefa6bc30e426f08a6a23c180

Observation f408fb6d-2d60-4d74-9733-e29251731708 · outbound

This paper cites Review of digital twin applications in manufacturing,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Review of digital twin applications in manufacturing,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.679943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.935439Z digest=sha256:ad8c99a5d8356487983a95ecfbef2ee4c10fa8355bb71b7c1d33e71295e3587f

Observation e38a32b2-dc87-466c-b980-01f179a42910 · outbound

This paper cites The health digital twin: advancing precision cardiovascular medicine,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework The health digital twin: advancing precision cardiovascular medicine,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.668409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.939461Z digest=sha256:14295acb42f7bab1d99a140fd6e06569d7d1aa515e48380655cae275a5423d5f

Observation 57cfdfb1-9530-4ad8-8a0c-4c8b92694f06 · outbound

This paper cites Large language models are zero-shot time series forecasters,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Large language models are zero-shot time series forecasters,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:10.943727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:10.943727Z digest=sha256:d6d9d733b83fcfb3a8bfeff377d2c6d9e559765aa8f69e45845dad40d1380669

Observation 176802a3-45e5-4fba-9f07-79c32b89a72a · outbound

This paper cites The dynamic data driven applications systems (dddas) paradigm and emerging directions,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework The dynamic data driven applications systems (dddas) paradigm and emerging directions,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.647050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.947426Z digest=sha256:cd071c32371b57a92a70164a7807b13117061da6745813f13e95f74f61abed28

Observation 8d4dd216-18e9-4051-a059-21e2b330daa3 · outbound

This paper cites Dt4i4-secure: Digital twin framework for industry 4.0 systems security,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Dt4i4-secure: Digital twin framework for industry 4.0 systems security,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.634427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.951109Z digest=sha256:a52da769ec418eac6ee4385bd7416417a2a187ec68a5bf041ed18a309704906d

Observation 6ead1d2f-3489-46aa-9459-662a89aa7324 · outbound

This paper cites Respond to change with constancy: Instruction-tuning with llm for non-iid network traffic classification,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Respond to change with constancy: Instruction-tuning with llm for non-iid network traffic classification,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.621255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.954566Z digest=sha256:e60ef50e8c98491c822fd5e6b780254d2987a7d4705ad6ccc55f24c499663b2c

Observation f9c172e7-e10d-4e59-a906-e439970b25f8 · outbound

This paper cites Draft modeling, simulation, information technology & processing roadmap,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Draft modeling, simulation, information technology & processing roadmap,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.607514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.958114Z digest=sha256:2340172884ce621d457ad1e22705be5bbd40837eb9885e3ebe071c8a04178923

Observation e437a194-d285-4021-8b37-600037a1b2d4 · outbound

This paper cites Machine learning surrogates for surface complexation model of uranium sorption to oxides,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Machine learning surrogates for surface complexation model of uranium sorption to oxides,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.593476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.961823Z digest=sha256:ec88ba2c0c007706d832802751ca5de2633f2b1494cbaf34e3325cdd84261f06

Observation bf80728c-e9cc-4c62-91de-23259abe317a · outbound

This paper cites Lifetime extension approach based on the levenberg–marquardt neural network and power routing of dc–dc converters,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Lifetime extension approach based on the levenberg–marquardt neural network and power routing of dc–dc converters,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.579213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.965535Z digest=sha256:c77d21f91725ccdf9d08e465297dbde565f3ca7b113eee3dc8cc8f1c7683ec6c

Observation 7f5ee221-c748-4290-9f42-5ef938c930b8 · outbound

This paper cites Process monitoring for tower pumping units under variable operational conditions: From an integrated multitasking perspective,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Process monitoring for tower pumping units under variable operational conditions: From an integrated multitasking perspective,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.566421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.969136Z digest=sha256:976903f9a22f1e97d02695997b57c7671ffa7de7dd8aa9f6318541f636323928

Observation c53306c5-caa3-447c-b354-543fe0b887fa · outbound

This paper cites Digital twin: Values, challenges and enablers from a modeling perspective,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Digital twin: Values, challenges and enablers from a modeling perspective,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.552842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.972676Z digest=sha256:0c99aa3147c1b617ab5113a99f43a73a549f9e9515bd7e003e024c25bb435d3b

Observation b3781ab6-16bf-42b9-9480-95d5629c6884 · outbound

This paper cites Dynamic network-centric multi-cloud platform for real-time and data-intensive science workflows,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Dynamic network-centric multi-cloud platform for real-time and data-intensive science workflows,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.540038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.976277Z digest=sha256:6e07dc85dbb57fe7f00bb5c79194df5d5a0808b443b600e549e6c8b4c898ad6b

Observation 7ac93144-2650-4d12-a5cf-077a5ebc17c1 · outbound

This paper cites Generative ai,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Generative ai,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.527277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.979773Z digest=sha256:5709973421fde119b32a7a372e2c1c183fba13f2f9ee157a5234680b64471c72

Observation b105ae8f-d3c1-43f6-a87b-319e2f59382b · outbound

This paper cites Attention is all you need,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Attention is all you need,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:10.983247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:10.983247Z digest=sha256:e5b198a10534829436b56a5c8ca3a351fa0471fff0b48cd23cc37ee794a7907a

Observation 2e341e62-b0f9-4b39-8995-f12092b1e4a8 · outbound

This paper cites Chatgpt for good? on opportunities and challenges of large language models for education,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Chatgpt for good? on opportunities and challenges of large language models for education,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.506147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.986630Z digest=sha256:9ac568832be932e57a5e45bc09a83b101ac9375d6dce4da4d1ea4c5c4e780f0a

Observation 8ce6620f-3368-4987-b28c-a7353c2ddee1 · outbound

This paper cites Large language models are zero-shot reasoners,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Large language models are zero-shot reasoners,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:10.990072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:10.990072Z digest=sha256:5c2236ab70d6818edf3c576bbc603c7d084f470f3703fd2c646e2d705f6aaf09

Observation 8c25a7a4-9723-49cf-8b28-6d3b6d252757 · outbound

This paper cites Autonomous chemical research with large language models,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Autonomous chemical research with large language models,

Reference 21

Resolution
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no resolver link, observed 2026-08-10T23:52:10.993631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:10.993631Z digest=sha256:c4e9aff68a01df9ecde9b21887f1d6fdd468e9f1982d0a394c03fa8cd7e77a12

Observation 981c0952-29a6-49af-845d-3669079000f9 · outbound

This paper cites An llm-based approach for enabling seamless human-robot collaboration in assembly,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework An llm-based approach for enabling seamless human-robot collaboration in assembly,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.477087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:10.996939Z digest=sha256:48437d8cd799bab31ea445f7e8250ee263b913ecf032a46519faf077efdf9505

Observation 3c818c19-72e0-48d7-ac3d-8198153cc7e0 · outbound

This paper cites A large language model-based multi-agent manufacturing system for intelligent shopfloor,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework A large language model-based multi-agent manufacturing system for intelligent shopfloor,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:11.000282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:11.000282Z digest=sha256:5363fe1e5009f3026707e3b44bf98386d958b929a8b1ccaa5b94410b1690b837

Observation dcd4e21f-e347-484a-8a87-5f28853f0202 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:11.003748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:11.003748Z digest=sha256:4b82a6982e7dab46fcfe47a7bbfe3673d54dc29b9a430ec87170a1342a12ee68

Observation e05fb0aa-a27a-4ef5-83a6-67e717184454 · outbound

This paper cites Can LLMs Understand Time Series Anomalies?.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Can LLMs Understand Time Series Anomalies?

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:11.007583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:11.007583Z digest=sha256:8b355ac86d90e3d9bbaf2b5e10dbe9041407b75c9592544be23345b89757f588

Observation 9a3e0525-1255-4b51-8f8b-ab8e3a0d4224 · outbound

This paper cites TimeGPT-1.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework TimeGPT-1

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T23:52:11.011595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:52:11.011595Z digest=sha256:ad3bb5e4bce56458d78a7b19385d24bc260ea9218e7868f3716bc58d2e499c94

Observation 6faba5de-c1cb-4056-9a93-3d9f55974c72 · outbound

This paper cites Zero-shot forecasting of chaotic systems,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Zero-shot forecasting of chaotic systems,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.464097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.015430Z digest=sha256:9f0ec6d01c1850ca1d0ef87494bef8ac6611289351557be1ffc0a262fc591933

Observation 93a9fca2-8166-45c3-b852-27e78a218fc1 · outbound

This paper cites Digital twins: Universal interoperability for the digital age,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Digital twins: Universal interoperability for the digital age,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.438619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.023524Z digest=sha256:ce3729685c94e0c3c0bbffa46adff9db1035f0dd047f45afc1fe2f89c7ac94ce

Observation d203216b-3573-4710-9e4a-99ae12c6655a · outbound

This paper cites Real-time synchronized calibration and computing system with epics based distributed controls in the tps xbpm system,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Real-time synchronized calibration and computing system with epics based distributed controls in the tps xbpm system,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.425743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.027594Z digest=sha256:948321ed40e6449be0a751fc385bc80c386e5d3fb51e776516c78bd65519b0f9

Observation 7090d857-76e5-4642-b2e5-4e0f2405a1bc · outbound

This paper cites Constrained optimization of sensor placement for nuclear digital twins,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Constrained optimization of sensor placement for nuclear digital twins,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.413715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.031477Z digest=sha256:82401745f95543393d2980e9b914269bad4eb7220549f5f496ad5f2a1aa9a4da

Observation 9a631b38-0e09-48c1-ba0c-f8bd5fa07038 · outbound

This paper cites Ensuring safety, security, and sustainability of mission-critical cyber–physical systems,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Ensuring safety, security, and sustainability of mission-critical cyber–physical systems,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.401784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.035216Z digest=sha256:94e15c074f618a8f5a45cb13c7d3b072f51495e48d548b1ed6dc1f70d33f3c0c

Observation cc29f856-6d9d-4524-bca7-3722144e8efe · outbound

This paper cites Digital twin: A comprehensive survey of security threats,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Digital twin: A comprehensive survey of security threats,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.389610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.038782Z digest=sha256:50e6ebbd0058d5eea4f71bce8e2bba442dcf23e9be9e0527ebfbe116e37ba577

Observation 13cda589-9457-4d4f-b884-ef1115766e3c · outbound

This paper cites Wireless anomaly detection based on ieee 802.11 behavior analysis,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Wireless anomaly detection based on ieee 802.11 behavior analysis,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.377670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.042835Z digest=sha256:e5d578b5cf724ee03518da9861b9848065f0d58bf0a7d0597bfe7548a88a143f

Observation 4c2e793d-20b6-4054-b58d-d75da6ce7483 · outbound

This paper cites Federated cybersecurity testbed as a service (fctaas): A framework to federate cybersecurity testbeds,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Federated cybersecurity testbed as a service (fctaas): A framework to federate cybersecurity testbeds,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.365806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.047165Z digest=sha256:dd86c3550f45d712b530046ce7943491bac9f21af2579adc19585d1fca04bb76

Observation e7a0ed10-f8b1-41b5-8cfc-066dcd1468e9 · outbound

This paper cites Ccri: Planning-c: Federated cloud platform for networked cyber physical systems research,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Ccri: Planning-c: Federated cloud platform for networked cyber physical systems research,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.353262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.051354Z digest=sha256:699ca9c2b64083b00b2e14f24baa2fe205697cad131e4632d589be5ca541c4d0

Observation 4f68d48d-c9a0-4743-9786-fe0b484d15e5 · outbound

This paper cites Digital-twin-enabled intelligent distributed clock synchronization in industrial iot systems,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Digital-twin-enabled intelligent distributed clock synchronization in industrial iot systems,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.341517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.055060Z digest=sha256:6f22483117b548e45ca006a4dedc25135e797b0c5686e4152c8fd17180074fb1

Observation 9a246b06-a8cb-47d7-908e-bebdb2657a28 · outbound

This paper cites Digital twins’ maturity: The need for interoperability,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Digital twins’ maturity: The need for interoperability,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.328149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.058857Z digest=sha256:669f4030f43b64de5369edf65e1b5ea60fb21346e0294e71567002b4fb080830

Observation 2f0c9ced-200a-4ed8-b9b8-78db75b5d405 · outbound

This paper cites Improved multi-fidelity simulation-based optimisation: application in a digital twin shop floor,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Improved multi-fidelity simulation-based optimisation: application in a digital twin shop floor,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.315500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.062408Z digest=sha256:5a08793e94a098b776740cd877ec2d26052f8f0daaad3c8c7201b2ff9bf9f261

Observation 5892ef8f-a200-4cce-9159-e3fd0e273fde · outbound

This paper cites A review of bearing failure modes, mechanisms and causes,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework A review of bearing failure modes, mechanisms and causes,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.303330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.065997Z digest=sha256:aa34aef5957ec4e5c7ab79e31690fa3f6bf34b29f7e71cc180e39475cb477c83

Observation 7cfd76bc-6cb3-48d4-84af-03fbd6de23ab · outbound

This paper cites Real-time drill wear estimation based on spindle motor power,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Real-time drill wear estimation based on spindle motor power,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.290063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.069744Z digest=sha256:55df52a85b163db61c566d8df3c8201ecf2351f9aac5d4127a37437252a96af9

Observation 7c9f18ff-ce6e-4e1c-b0f6-04d797060ee9 · outbound

This paper cites Tool condition monitoring for form milling of large parts by combining spindle motor current and acoustic emission signals,.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Tool condition monitoring for form milling of large parts by combining spindle motor current and acoustic emission signals,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.277832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.073449Z digest=sha256:0e3935825af89f06a3945be039ec66d19bc6b95cf9a8663a911d1942575ca5d9

Observation cb435dcb-7c82-4235-8a6c-0537e206b985 · outbound

This paper cites Available: https://openreview.net/forum?id=TqYjhJrp9m.

DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework Available: https://openreview.net/forum?id=TqYjhJrp9m

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:52:11.451133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-10T23:52:11.019583Z digest=sha256:fe8148aaf8b2d501ae4e201401077e5e7e495f5096708a5bdda784dbe0b7adfe

Pith citing papers

Observation 1b549ea5-623b-4189-83c3-dfd067af86fe · inbound

Integrating Generative AI into Cybersecurity Education: A Study of OCR and Multimodal LLM-assisted Instruction cites this paper.

Integrating Generative AI into Cybersecurity Education: A Study of OCR and Multimodal LLM-assisted Instruction DDD-GenDT: Dynamic Data-driven Generative Digital Twin Framework

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T11:15:57.631736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-05T11:15:57.359300Z digest=sha256:77c6cf978fc978130363a7a982ff0b586f694b248b069836a994e0fe0569280f