Paper Citation Record · LEDGER

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

As of 5 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 2 inbound Pith citation observations for arXiv:2603.25099.

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

pith.paper-citation-record.v1
2603.25099 v2

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T03:27:31.856474Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T03:27:34.687616Z

Reference resolution

74 of 74 outbound references displayed

verified exact43
verified fuzzy14
unresolved3
parse uncertain0
malformed identifier7
metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a0aef68f-e474-42e4-aee2-5baca0e23a56 · outbound

This paper cites Lazarov, and Ole Sigmund.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Lazarov, and Ole Sigmund

Reference 1

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.293504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f31bc5ae-3fdc-4364-9531-cf82a8f6bba8 · outbound

This paper cites Abueidda, Seid Koric, and Nahed A.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Abueidda, Seid Koric, and Nahed A

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:37:41.285660Z

Source-reported events for the cited work

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Observation cfcaab1b-ae14-49a3-95f5-2e02ed894b30 · outbound

This paper cites Automated dynamic algorithm configuration.Journal of Artificial Intelligence Research, 75:1633–1699.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Automated dynamic algorithm configuration.Journal of Artificial Intelligence Research, 75:1633–1699

Reference 3

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.326929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 775a23c3-1496-4de7-95a6-d10231721d81 · outbound

This paper cites S., Sigmund O.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization S., Sigmund O

Reference 4

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.272343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 646ee73f-8441-4df0-ae9e-02d7015481a8 · outbound

This paper cites The Claude model card and evaluations.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization The Claude model card and evaluations

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.129408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8af371a8-e7ef-4cfe-9d5c-85d2cd302629 · outbound

This paper cites Olson, Jacob Schroder, and Ben Southworth.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Olson, Jacob Schroder, and Ben Southworth

Reference 6

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.306172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 128a4a04-08e3-470b-a7cb-6401be966847 · outbound

This paper cites Optimalshapedesignasamaterialdistribution problem.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Optimalshapedesignasamaterialdistribution problem

Reference 7

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.275470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7d304654-b161-4913-85f0-71c82d3e8a3e · outbound

This paper cites Bendsøe and Noboru Kikuchi.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Bendsøe and Noboru Kikuchi

Reference 8

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.358198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 30895b2d-efcb-4e2a-bd84-3493086633db · outbound

This paper cites Bendsøe and Ole Sigmund.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Bendsøe and Ole Sigmund

Reference 9

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.304242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 309b74d4-e26a-492a-809f-78ee3dd02fe6 · outbound

This paper cites Curriculum learning, in: Proceedings of the 26th Annual International Conference on Machine Learning, Associa- tion for Computing Machinery, New York, NY, USA.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Curriculum learning, in: Proceedings of the 26th Annual International Conference on Machine Learning, Associa- tion for Computing Machinery, New York, NY, USA

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:37:41.332556Z

Source-reported events for the cited work

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Observation 51967e28-7d43-44f0-b5d3-7f6299291eea · outbound

This paper cites Bengio, A.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Bengio, A

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 03168328-2f8c-4d85-bc75-1041d4722d82 · outbound

This paper cites Algorithms for hyper- parameter optimization.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Algorithms for hyper- parameter optimization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.141072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2c37c2db-4588-4a72-9cf9-c0ea1392cfcf · outbound

This paper cites Furkan Bozkurt, Theresa Eimer, Frank Hutter, and Marius Lindauer.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Furkan Bozkurt, Theresa Eimer, Frank Hutter, and Marius Lindauer

Reference 13

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.297412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f9843956-50fe-4793-b51c-d16394beab3e · outbound

This paper cites Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.WIREs Data Mining and Knowledge Discovery, 13(2):e1484.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.WIREs Data Mining and Knowledge Discovery, 13(2):e1484

Reference 14

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T17:43:10.121687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 18a1e09d-bd36-401e-881d-14db7d0cf079 · outbound

This paper cites Gupta, Neereja Sundaresan, Thomas Alexander, Christopher J.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Gupta, Neereja Sundaresan, Thomas Alexander, Christopher J

Reference 15

Resolution: malformed identifier; doi_truncated, observed 2026-05-19T17:37:41.318717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 725bc35a-c18b-4368-b893-4cd1a1a5e9e3 · outbound

This paper cites Filters in topology optimization.International Journal for Numerical Methods in Engineering, 50(9):2143–2158.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Filters in topology optimization.International Journal for Numerical Methods in Engineering, 50(9):2143–2158

Reference 16

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.346261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b32b0797-a133-43ac-8a4e-67fe02842bf3 · outbound

This paper cites Brown, Anthony P.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Brown, Anthony P

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:37:41.289040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f5d19fe1-41d8-482c-9c43-253b38799439 · outbound

This paper cites an unresolved cited work.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-05-19T17:43:10.146802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9677f373-e4d2-4284-8356-170eafa02b99 · outbound

This paper cites an unresolved cited work.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Unresolved cited work

Reference 19

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.264082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 950ab73a-32da-4dbb-b961-e908a98ddbdd · outbound

This paper cites One-shot generation of near-optimal topology through theory-driven machine learning.Computer-Aided Design, 109:12–21.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization One-shot generation of near-optimal topology through theory-driven machine learning.Computer-Aided Design, 109:12–21

Reference 20

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T17:43:10.144945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5bf82b3f-6fc1-42f2-8b6b-59ba6ac89116 · outbound

This paper cites TOuNN: Topology optimization using neural networks.Structural and Multidisciplinary Optimization, 63(3):1135–1149.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization TOuNN: Topology optimization using neural networks.Structural and Multidisciplinary Optimization, 63(3):1135–1149

Reference 21

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T17:43:10.142871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4e0e1346-88f7-49fd-91d1-3983704ecf7e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Evaluating Large Language Models Trained on Code

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-19T17:37:41.759520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d41e4dc3-8be6-4bd4-b35f-b8a817b69ed6 · outbound

This paper cites Deaton and Ramana V.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Deaton and Ramana V

Reference 23

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.269992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c9c9ae48-a8ee-4f2c-b44c-dbc977bf68cd · outbound

This paper cites Self-directed online machine learning for topology optimization.Nature Communications, 13(1):388.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Self-directed online machine learning for topology optimization.Nature Communications, 13(1):388

Reference 24

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T17:43:10.140735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 59ce16e6-6fff-43eb-9b95-e58d1dd847eb · outbound

This paper cites an unresolved cited work.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-05-19T17:43:10.138205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d9b050f6-3edf-424d-880d-8227d426075f · outbound

This paper cites Automatic projection parameter increase for three-field density-based topology optimization.Structural and Multidisciplinary Optimization, 68(2):33.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Automatic projection parameter increase for three-field density-based topology optimization.Structural and Multidisciplinary Optimization, 68(2):33

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.136218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 08ae9371-10d7-4b35-84b4-f3a4c5f76fe2 · outbound

This paper cites an unresolved cited work.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Unresolved cited work

Reference 27

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.356026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 19383ba4-61ad-41cc-99a9-96293035d8e5 · outbound

This paper cites DACBench: A benchmark library for dynamic algorithm configuration.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization DACBench: A benchmark library for dynamic algorithm configuration

Reference 28

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.295518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8685e276-f029-414d-a670-8f399f45351a · outbound

This paper cites A new generation 99 line Matlab code for compliance topology optimization and its extension to 3D.Structural and Multidisciplinary Optimization, 62:2211–2228.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization A new generation 99 line Matlab code for compliance topology optimization and its extension to 3D.Structural and Multidisciplinary Optimization, 62:2211–2228

Reference 29

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.278444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6b3918f4-3540-47e5-9fbf-d87bba04853a · outbound

This paper cites K., Prévost, J.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization K., Prévost, J

Reference 30

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.316223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 124c5484-ba1e-4a38-ae4c-53f3518cf416 · outbound

This paper cites Guest, Alireza Asadpoure, and Seung-Hyun Ha.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Guest, Alireza Asadpoure, and Seung-Hyun Ha

Reference 31

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.344322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c06ec4a8-d2c2-4566-9c9e-77b089c00e81 · outbound

This paper cites Introducing Gemini 2.0: Our new AI model for the agentic era.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Introducing Gemini 2.0: Our new AI model for the agentic era

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.133865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 946b7be4-3e67-4051-97c0-c121941ecd7a · outbound

This paper cites Reinforcement learning and graph embedding for binary truss topology optimization under stress and displacement constraints.Frontiers in Built Environment, 6:59.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Reinforcement learning and graph embedding for binary truss topology optimization under stress and displacement constraints.Frontiers in Built Environment, 6:59

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:37:41.366121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a10dedb2-3c58-4284-b46d-a5a196cc06e5 · outbound

This paper cites Neural reparameterization improves structural optimization.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Neural reparameterization improves structural optimization

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:37:41.768368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 770b7b99-1044-4009-bc5a-395b5b486c98 · outbound

This paper cites Hutter, H.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Hutter, H

Reference 35

Resolution: metadata mismatch; doi, observed 2026-05-19T17:37:41.328945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b628f908-1fe7-415d-a31f-c8009c13dcca · outbound

This paper cites Springer, Cham.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Springer, Cham

Reference 36

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.255838Z

Source-reported events for the cited work

correction dated 2019-08-27. Source: crossref record 10.1007/978-3-030-05318-5_11->10.1007/978-3-030-05318-5:correction, observed 2026-07-11T03:07:51.298187+00:00. This notice travels one citation hop only.

Observation 7897219e-135a-45dd-a884-246c244f7bdf · outbound

This paper cites Population Based Training of Neural Networks.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Population Based Training of Neural Networks

Reference 37

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T17:37:41.756728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 395b8425-3264-457b-9275-468a0bafae03 · outbound

This paper cites Kallioras, Georgios Kazakis, and Nikos D.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Kallioras, Georgios Kazakis, and Nikos D

Reference 38

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.253371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e5d2a6af-c037-45ac-aa03-2f5ddd5cf166 · outbound

This paper cites Lazarov and Ole Sigmund.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Lazarov and Ole Sigmund

Reference 39

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.324692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b575947a-f9de-45c9-8971-93bc576dbf54 · outbound

This paper cites Lazarov, Fengwen Wang, and Ole Sigmund.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Lazarov, Fengwen Wang, and Ole Sigmund

Reference 40

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.280484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f802a4b5-10a5-4da0-b9df-8f1f217a24e9 · outbound

This paper cites Hy- perband: A novel bandit-based approach to hyperparameter optimization.Journal of Machine Learning Research, 18(185):1–52.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Hy- perband: A novel bandit-based approach to hyperparameter optimization.Journal of Machine Learning Research, 18(185):1–52

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.131572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fea00388-3c49-4a54-a8de-27045a80a375 · outbound

This paper cites Critical current of a Josephson junction containing a conical magnet.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Critical current of a Josephson junction containing a conical magnet

Reference 42

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T17:37:41.321708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7512fb8a-3d3b-4ec3-8a3d-8a9d09d70647 · outbound

This paper cites Self-Refine: Iterative refinement with self-feedback.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Self-Refine: Iterative refinement with self-feedback

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.127303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0cba75aa-1ec8-4c98-b5b7-6c5539227f7f · outbound

This paper cites Diffusion models beat GANs on topology optimization.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Diffusion models beat GANs on topology optimization

Reference 44

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.267482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cdb8fc63-9429-42ed-8095-bbcbf50b1f68 · outbound

This paper cites TopologyGAN: Topology optimization using generative adversarial networks based on physical fields over the initial domain.Journal of Mechanical Design, 143(3):031715.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization TopologyGAN: Topology optimization using generative adversarial networks based on physical fields over the initial domain.Journal of Mechanical Design, 143(3):031715

Reference 45

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.314255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1e22dafa-9896-4da9-a801-2bcf372e6349 · outbound

This paper cites GPT-4 Technical Report.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization GPT-4 Technical Report

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-05-19T17:37:41.762486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d0be39b4-b648-4295-96ab-e4a6257d01a6 · outbound

This paper cites Bernstein.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Bernstein

Reference 47

Resolution: malformed identifier; arxiv_id, observed 2026-05-19T17:37:41.765657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9f1a73eb-973e-470a-ba9c-4b8aa977f0a3 · outbound

This paper cites Critical current of a Josephson junction containing a conical magnet.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Critical current of a Josephson junction containing a conical magnet

Reference 48

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T17:37:41.259232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cb0aacab-e660-4716-aa72-0196b19cec70 · outbound

This paper cites Automatic penalty continuation in structural topology optimization.Structural and Multidisciplinary Optimization, 52(6):1205–1221.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Automatic penalty continuation in structural topology optimization.Structural and Multidisciplinary Optimization, 52(6):1205–1221

Reference 49

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.291523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e30289af-9e5c-45d1-8cd5-81a5074d5d6f · outbound

This paper cites doi: 10.1038/s41586-023-06924-6.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization doi: 10.1038/s41586-023-06924-6

Reference 50

Resolution: metadata mismatch; doi, observed 2026-05-19T17:37:41.312272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 290ee534-53d1-489f-a3a7-90840ff6288b · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Toolformer: Language models can teach themselves to use tools

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.146327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f6e0002d-e758-4f8f-b0e1-dc2d0b1c3a2a · outbound

This paper cites Taking the human out of the loop: A review of Bayesian optimization.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Taking the human out of the loop: A review of Bayesian optimization

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T17:37:41.353764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation eb9b77e1-80b5-4ff2-9acf-8be74d5f26a0 · outbound

This paper cites Learning step-size adaptation in CMA-ES.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Learning step-size adaptation in CMA-ES

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.143673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 931a7a91-3f8e-4774-bcd5-e8bf321c252d · outbound

This paper cites Topology optimization via machine learning and deep learning: a review.Journal of Computational Design and Engineering, 10(4):1736–1766.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Topology optimization via machine learning and deep learning: a review.Journal of Computational Design and Engineering, 10(4):1736–1766

Reference 54

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.340595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1a2226bf-79f1-46fb-baf9-1b4ceff64154 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Reflexion: Language agents with verbal reinforcement learning

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.137103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ea1b6ff3-1e38-4545-99d3-c1f3b5d14f55 · outbound

This paper cites A 99 line topology optimization code written in Matlab.Structural and Multidisciplinary Optimization, 21(2):120–127.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization A 99 line topology optimization code written in Matlab.Structural and Multidisciplinary Optimization, 21(2):120–127

Reference 56

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.299686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 37607787-cc82-4214-bfba-5da5eb00c20d · outbound

This paper cites Morphology-based black and white filters for topology optimization.Structural and Multidisciplinary Optimization, 33(4-5):401–424.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Morphology-based black and white filters for topology optimization.Structural and Multidisciplinary Optimization, 33(4-5):401–424

Reference 57

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.334721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a5af4afa-9a6a-4aa1-80dc-4c3529cfe6ed · outbound

This paper cites Topology optimization approaches.Structural and Multi- disciplinary Optimization, 48(6):1031–1055.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Topology optimization approaches.Structural and Multi- disciplinary Optimization, 48(6):1031–1055

Reference 58

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.360413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f92fee54-00d5-414d-84c8-ed0a3885fda4 · outbound

This paper cites Numerical instabilities in topology optimization: a survey on procedures dealing with checkerboards, mesh-dependencies and local minima.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Numerical instabilities in topology optimization: a survey on procedures dealing with checkerboards, mesh-dependencies and local minima

Reference 59

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.302070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f1141117-0480-4e3e-a568-c8194a4557f9 · outbound

This paper cites an unresolved cited work.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-05-19T17:43:10.134911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 02feaf99-2e7f-4303-9783-90387424a783 · outbound

This paper cites Neural networks for topology optimization.Russian Journal of Numerical Analysis and Mathematical Modelling, 34(4):215–223.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Neural networks for topology optimization.Russian Journal of Numerical Analysis and Mathematical Modelling, 34(4):215–223

Reference 61

Resolution: malformed identifier; doi_truncated, observed 2026-05-19T17:37:41.342503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fdc611c1-104d-4e80-b2ca-ed0f7d3f33ab · outbound

This paper cites On the trajectories of penalization methods for topol- ogy optimization.Structural and Multidisciplinary Optimization, 21(2):128–139.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization On the trajectories of penalization methods for topol- ogy optimization.Structural and Multidisciplinary Optimization, 21(2):128–139

Reference 62

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.261932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0bbff38b-1f0c-4a4a-bb0c-f3240422c37d · outbound

This paper cites Svanberg, ‘The method of moving asymptotes—a new method for structural optimization’, Numerical Meth En- gineering, vol.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Svanberg, ‘The method of moving asymptotes—a new method for structural optimization’, Numerical Meth En- gineering, vol

Reference 63

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.251203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 91db53bb-91ac-4ef2-befb-4a4623970b43 · outbound

This paper cites A class of globally convergent optimization methods based on conservative convex separable approximations.SIAM Journal on Optimization, 12(2):555–573.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization A class of globally convergent optimization methods based on conservative convex separable approximations.SIAM Journal on Optimization, 12(2):555–573

Reference 64

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.282584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4438080e-9d87-41c9-9e1f-0839021c01d4 · outbound

This paper cites Lazarov, and Ole Sigmund.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Lazarov, and Ole Sigmund

Reference 65

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.350082Z

Source-reported events for the cited work

correction dated 2022-09-17. Source: crossref record 10.1007/s00158-022-03326-6->10.1007/s00158-010-0602-y:correction, observed 2026-07-11T03:07:59.085142+00:00. This notice travels one citation hop only.

Observation 3d141e07-7e8b-4f00-8f1e-b2f6a5c7706b · outbound

This paper cites Voyager: An open-ended embodied agent with large lan- guage models.Transactions on Machine Learning Research, pages 1–27.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Voyager: An open-ended embodied agent with large lan- guage models.Transactions on Machine Learning Research, pages 1–27

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.130495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 374d1de5-a714-43a7-ade0-4a20bba6bd99 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Chain-of-thought prompting elicits reasoning in large language models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.127880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f18498b3-e40a-4105-af3e-e079cf7f0770 · outbound

This paper cites Woldseth, Niels Aage, Jakob Andreas Bærentzen, and Ole Sigmund.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Woldseth, Niels Aage, Jakob Andreas Bærentzen, and Ole Sigmund

Reference 68

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.248331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1ce0e0ea-56c1-4c2a-8d9e-6d156a6296be · outbound

This paper cites Evolutionary com- putation in the era of large language model: Survey and roadmap.IEEE Transactions on Evolutionary Computation, 29(2):534–554.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Evolutionary com- putation in the era of large language model: Survey and roadmap.IEEE Transactions on Evolutionary Computation, 29(2):534–554

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:37:41.309356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4bc14c02-77d3-4dc7-ac0d-1f96a8ef816b · outbound

This paper cites Le, Denny Zhou, and Xinyun Chen.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Le, Denny Zhou, and Xinyun Chen

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.125721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1cebd646-7d15-48b4-9403-fa92f1ea6d7c · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization ReAct: Synergizing reasoning and acting in language models

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.123893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6aae0428-206b-44a9-b106-259e3b91d2c7 · outbound

This paper cites ReEvo: Large language models as hyper-heuristics with reflective evolution.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization ReEvo: Large language models as hyper-heuristics with reflective evolution

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T17:43:10.120685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f0836fbb-9ebb-4a5a-97dc-ba657395fb0f · outbound

This paper cites Deep learning for determining a near-optimal topological design without any iteration.Structural and Multidisciplinary Optimization, 59(3):787–799.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Deep learning for determining a near-optimal topological design without any iteration.Structural and Multidisciplinary Optimization, 59(3):787–799

Reference 73

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.338572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a4146f04-6525-433f-bdff-3bd9bc758ae6 · outbound

This paper cites Zhou and G.

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization Zhou and G

Reference 74

Resolution: verified exact; doi, observed 2026-05-19T17:37:41.336719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

Observation be917ef0-b955-4a63-99a8-2a7041f29408 · inbound

IterSIMP-{\sigma}: Evaluating LLM-Assisted Spatial Interventions in Stress-Aware Topology Optimization cites this paper.

IterSIMP-{\sigma}: Evaluating LLM-Assisted Spatial Interventions in Stress-Aware Topology Optimization Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-05-20T07:33:07.434373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 249dd960-be0c-4f8d-8698-4002b19fe2f6 · inbound

TO-Master: an LLM-agent framework for automated topology optimization cites this paper.

TO-Master: an LLM-agent framework for automated topology optimization Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T03:27:34.689118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.