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Paper Citation Record · LEDGER

Physics-Audited Agentic Discovery in Scientific Machine Learning

As of 22 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2607.07379.

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

pith.paper-citation-record.v1
2607.07379 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T12:49:30.003524Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

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  • verified fuzzy44
  • unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0da40c8c-ade1-4fc8-82f8-759d0b43d40a · outbound

This paper cites Raissi, P.

Physics-Audited Agentic Discovery in Scientific Machine Learning Raissi, P

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f31be7e0-9cfd-4200-bd8d-d071a69d744f · outbound

This paper cites Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang.

Physics-Audited Agentic Discovery in Scientific Machine Learning Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang

Reference 2

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:3894a5af0c344452ab5183fe0b18bd8336e48cf7621819f4efffc9507053fd13

Observation 5474797a-e53e-4387-a7d2-94ee56accb14 · outbound

This paper cites Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators.Nature Machine Intelligence, 3(3): 218–229, 2021.

Physics-Audited Agentic Discovery in Scientific Machine Learning Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators.Nature Machine Intelligence, 3(3): 218–229, 2021

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 46fbadd3-02e4-450f-9ba9-64502072e5cf · outbound

This paper cites Fourier neural operator for parametric partial differential equations.

Physics-Audited Agentic Discovery in Scientific Machine Learning Fourier neural operator for parametric partial differential equations

Reference 4

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verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.529940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:7b8e0b298d466c0782390f6df843b3d6ffc4a668c19ab69e3953e31c34ad54f2

Observation 736c3bea-6de1-48ef-a0aa-592963620256 · outbound

This paper cites an unresolved cited work.

Physics-Audited Agentic Discovery in Scientific Machine Learning Unresolved cited work

Reference 5

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raw_fallback, observed 2026-07-09T12:56:15.532540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:e73df513c4987c4864545bbfa3b30e607749c42ab76c98a3813184f4d10edeb6

Observation dce0b0a8-5a71-4f08-9d62-d902b445cb88 · outbound

This paper cites PDE-Agents: An LLM-Orchestrated Multi-Agent Framework for Automated Finite Element Simulations with Knowledge Graph-Augmented Reasoning.

Physics-Audited Agentic Discovery in Scientific Machine Learning PDE-Agents: An LLM-Orchestrated Multi-Agent Framework for Automated Finite Element Simulations with Knowledge Graph-Augmented Reasoning

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-07-09T12:56:14.907197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:7252cc5d2dda8461d016b45492bb249725bd544aa7a792b4095424d1c5bce6a0

Observation a6d972b1-a345-4702-a2f1-de44e61620f3 · outbound

This paper cites ALL-FEM: Agentic large language models fine-tuned for finite element methods.Computer Methods in Applied Mechanics and Engineering, 457:118985, 2026.

Physics-Audited Agentic Discovery in Scientific Machine Learning ALL-FEM: Agentic large language models fine-tuned for finite element methods.Computer Methods in Applied Mechanics and Engineering, 457:118985, 2026

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.555651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:8b6b61c7f1d945861f67830cb1733f4fc5d069f475780f81afb6463b789e0be5

Observation 3ae52164-4517-46e8-ade2-4a1141737475 · outbound

This paper cites OpenFOAMGPT: A retrieval-augmented large language model (LLM) agent for OpenFOAM-based computational fluid dynamics.Physics of Fluids, 37(3):035120, 2025.

Physics-Audited Agentic Discovery in Scientific Machine Learning OpenFOAMGPT: A retrieval-augmented large language model (LLM) agent for OpenFOAM-based computational fluid dynamics.Physics of Fluids, 37(3):035120, 2025

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.527285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:719ccc433a042e564b120c03ff764013b3e1bae15a4382d919b6b23652dd9752

Observation 7f996639-dc02-416d-b8a0-405bf8d942e3 · outbound

This paper cites Kumar, G.

Physics-Audited Agentic Discovery in Scientific Machine Learning Kumar, G

Reference 9

Resolution
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arxiv_id, observed 2026-07-09T12:56:14.900855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:2e48ed6c3296153cdae910d5ddb08dc7924de8e3040134ade1592c3ac834ea29

Observation 0baaa853-8792-412d-91f4-89b41549b83a · outbound

This paper cites AgenticSciML: collaborative multi-agent systems for emergent discovery in scientific machine learning.npj Artificial Intelligence, 2026.

Physics-Audited Agentic Discovery in Scientific Machine Learning AgenticSciML: collaborative multi-agent systems for emergent discovery in scientific machine learning.npj Artificial Intelligence, 2026

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.537198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:b26c614f187ca08f195cb1898a5d561c0afc4e9ce1ad0f26772f02f3f12061a0

Observation 5e279cf2-126a-4ce1-b8a3-59a9e0873bf2 · outbound

This paper cites ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms.

Physics-Audited Agentic Discovery in Scientific Machine Learning ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-07-09T12:56:14.905383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:d3876196deb224bc8f775fa301ce17d269f8e42425d8e3cbb0960995631d5da5

Observation 4f6a87fc-9a40-449c-815c-c3ce4a69c9e8 · outbound

This paper cites GRAFT-ATHENA: Self-Improving Agentic Teams for Autonomous Discovery and Evolutionary Numerical Algorithms.

Physics-Audited Agentic Discovery in Scientific Machine Learning GRAFT-ATHENA: Self-Improving Agentic Teams for Autonomous Discovery and Evolutionary Numerical Algorithms

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-07-09T12:56:14.912252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:8933b27736811f3ce96f013fb3373139b8757ae86cc30074e55d398271449552

Observation 6eb37f72-c743-4980-8f65-01786a438971 · outbound

This paper cites PINNsAgent: Automated PDE surrogation with large language models.

Physics-Audited Agentic Discovery in Scientific Machine Learning PINNsAgent: Automated PDE surrogation with large language models

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:48a62bb35aa45838363512361950aac2aa2ee14c91767823ead6d6be73d81118

Observation 2992c467-e0e3-4d93-8b78-7384783f603e · outbound

This paper cites Lang-PINN: From language to physics-informed neural networks via a multi-agent framework.

Physics-Audited Agentic Discovery in Scientific Machine Learning Lang-PINN: From language to physics-informed neural networks via a multi-agent framework

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-09T12:56:14.911700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:b7d882abe0ea4c895cdd57fc074b1cec692191d89e1930816277e46ee5fe643a

Observation 5bdf03c5-3c26-4aad-b8ca-f4a3e8f92433 · outbound

This paper cites an unresolved cited work.

Physics-Audited Agentic Discovery in Scientific Machine Learning Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-07-09T12:56:15.519526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:12e5a1d4d4bf85a5a2b8d7f0e7f63aa8cb2c5e2f28181b88741779b3effe77d7

Observation 1728eec4-afa2-43a0-a5c5-e4a34ff47e49 · outbound

This paper cites Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs.

Physics-Audited Agentic Discovery in Scientific Machine Learning Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:ee6c707c4ea24b23450502900be6a0a527d39f2bdc9350ee7d99dcea928c16ba

Observation 2f08c88e-22f3-4918-8904-e447f5020aff · outbound

This paper cites Karniadakis.

Physics-Audited Agentic Discovery in Scientific Machine Learning Karniadakis

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.508062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:476c6cfd4ae14c37c40edaa5a75c954ea94210ec4b754cf8fb638424f25161a9

Observation ea7cec9f-1159-437d-807f-afea8c81a465 · outbound

This paper cites Learning the solution operator of parametric partial differential equations with physics-informed DeepONets.Science Advances, 7(40), 2021.

Physics-Audited Agentic Discovery in Scientific Machine Learning Learning the solution operator of parametric partial differential equations with physics-informed DeepONets.Science Advances, 7(40), 2021

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.553547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:884f07e46a98ebd97d279e367b5244b1b8b62218be174e2fb5c000d2c2e9ef47

Observation c5298ca9-ff44-4bf4-a4cd-e3c68e3855eb · outbound

This paper cites Physics-Informed Neural Operator for Learning Partial Differential Equations.ACM/IMS Journal of Data Science, 1(3):1–27, 2024.

Physics-Audited Agentic Discovery in Scientific Machine Learning Physics-Informed Neural Operator for Learning Partial Differential Equations.ACM/IMS Journal of Data Science, 1(3):1–27, 2024

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.555503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:3961e34335004fdc8b3b85ffab6ee76972230ec5bf4f37b55f771a1d9b035f01

Observation a91d0b89-ca42-43cd-a464-e615a473c03e · outbound

This paper cites MIONet: Learning multiple-input operators via tensor product.SIAM Journal on Scientific Computing, 44(6):A3490–A3514.

Physics-Audited Agentic Discovery in Scientific Machine Learning MIONet: Learning multiple-input operators via tensor product.SIAM Journal on Scientific Computing, 44(6):A3490–A3514

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.507147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:7944fda2a9656035e394bb408dca0bf666b4537d6cc00f4b0530d648b6b0d50e

Observation 2e9a1997-77f8-4f8f-b88c-fb95d19c7017 · outbound

This paper cites A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data.Computer Methods in Applied Mechanics and Engineering, 393, 2022.

Physics-Audited Agentic Discovery in Scientific Machine Learning A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data.Computer Methods in Applied Mechanics and Engineering, 393, 2022

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.505933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:a6fe0a6b3542cc42e028d2a51b69b0517ba43164ef76bad5e57cc83f413ca9bf

Observation 6fa654a5-d333-4023-9294-4af61e489c96 · outbound

This paper cites Fourier Neural Operator with Learned Deformations for PDEs on General Geometries.Journal of Machine Learning Research, 24(388):1–26, 2023.

Physics-Audited Agentic Discovery in Scientific Machine Learning Fourier Neural Operator with Learned Deformations for PDEs on General Geometries.Journal of Machine Learning Research, 24(388):1–26, 2023

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:ae9d41c13c9486947aeeb3323c8a2e1fc9ec0ab04c5f30ee7972bfa12bcb9127

Observation ac6103ac-4ee5-4982-94dc-81af35dd2fb3 · outbound

This paper cites an unresolved cited work.

Physics-Audited Agentic Discovery in Scientific Machine Learning Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-07-09T12:56:15.557452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:3dd3e72e6cf974f12929007e2737eddf668599d0029bc1e0dbaa355e844def08

Observation ed41c800-8d7b-48af-abd3-73826a993294 · outbound

This paper cites Abueidda, Seid Koric, Nahil A.

Physics-Audited Agentic Discovery in Scientific Machine Learning Abueidda, Seid Koric, Nahil A

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.517848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:137020c4cd2bb22c738de098caeda09d8ffa746e925c1cb02a341688a325bd0a

Observation f93d7f6f-3cef-4755-82b7-115b137e1b0e · outbound

This paper cites Abueidda, Syed Bahauddin Alam, and Seid Koric.

Physics-Audited Agentic Discovery in Scientific Machine Learning Abueidda, Syed Bahauddin Alam, and Seid Koric

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.495588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:efadb43c09fc1ac9f3cbe3563bbb65db7568cd6b9fa21bd246458da75066d9a5

Observation 9acd9d1a-54cf-4432-96a9-d69fb97780a3 · outbound

This paper cites Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks.Journal of Computing and Information Science in Engineering, 20(1), 2020.

Physics-Audited Agentic Discovery in Scientific Machine Learning Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks.Journal of Computing and Information Science in Engineering, 20(1), 2020

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.501574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:408e8a51a626a7aad36d30d612c0cfca6dc7fc82d9cebd7b825f90aa25d4e3c7

Observation baa3c6a0-d0ee-4aad-a25f-9870f53190df · outbound

This paper cites A deep energy method for finite deformation hyperelasticity.European Journal of Mechanics - A/Solids, 80, 2020.

Physics-Audited Agentic Discovery in Scientific Machine Learning A deep energy method for finite deformation hyperelasticity.European Journal of Mechanics - A/Solids, 80, 2020

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.592228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:7616633043bbdd40af9d3787db1672cf8fda054e2150ca906d84e3d072f19f55

Observation c92a2d31-ab15-4c3b-96e8-3d7ef2fe59a7 · outbound

This paper cites A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials.Computer Methods in Applied Mechanics and Engineering, 391, 2022.

Physics-Audited Agentic Discovery in Scientific Machine Learning A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials.Computer Methods in Applied Mechanics and Engineering, 391, 2022

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.491238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:f3585ca80b4669031e0dce1f0be7b6fb2148b35b80af355ec579a3203563255a

Observation 7627bb7e-8a44-4d60-b97c-f92a45052db8 · outbound

This paper cites Kovachki, and Andrew M.

Physics-Audited Agentic Discovery in Scientific Machine Learning Kovachki, and Andrew M

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.584335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:37d88e76ba1d4a7136ba5fd0f37804958b4453185dd0cca110e00b2e3afbceb7

Observation a0879c56-6b88-4e0b-aea8-7c128201e656 · outbound

This paper cites Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network.Journal of Computational Physics, 469, 2022.

Physics-Audited Agentic Discovery in Scientific Machine Learning Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network.Journal of Computational Physics, 469, 2022

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.493425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:492488778f5b805c9f0b453ffe4bd3691e6b71cd051e99ff3dc102624b4148fa

Observation 1b54cbed-d497-486d-8631-51fd82a1c451 · outbound

This paper cites Abueidda, Mbebo Nonna, Panos Pantidis, and Mostafa E.

Physics-Audited Agentic Discovery in Scientific Machine Learning Abueidda, Mbebo Nonna, Panos Pantidis, and Mostafa E

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.494296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:f370085e9730ce943a2a506a254149f1da13b7d0fa898744b4ec8ce5ff5cdd58

Observation 34b77dae-5af4-4686-b18c-678144f8b737 · outbound

This paper cites Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries.Computer Methods in Applied Mechanics and Engineering, 429, 2024.

Physics-Audited Agentic Discovery in Scientific Machine Learning Geom-DeepONet: A point-cloud-based deep operator network for field predictions on 3D parameterized geometries.Computer Methods in Applied Mechanics and Engineering, 429, 2024

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.492164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:5fb88d4671da660d0d9a8c7895b6e05e7590c5aa1e57f08b3c7181d503da77b4

Observation 7a77b233-771a-4f18-88c6-d6d0353671d3 · outbound

This paper cites Mobasher.

Physics-Audited Agentic Discovery in Scientific Machine Learning Mobasher

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.484356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:c636491bc24782b30b6603a0ab533ecabbb4e046f58e34e30987689ff21bd2a0

Observation 9b339723-0da2-46ed-bcff-14459c7a2ad1 · outbound

This paper cites Amin, Diab W.

Physics-Audited Agentic Discovery in Scientific Machine Learning Amin, Diab W

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.541756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:893f18126019c20fe433f55e66a3fbc5f8e6e71783e52c60a9b6fe8004a4fad9

Observation daa28b8f-676a-481d-ae3f-9323a3973c2d · outbound

This paper cites Bock, Roland C.

Physics-Audited Agentic Discovery in Scientific Machine Learning Bock, Roland C

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.586311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:59e344dd544d7dab460832cb96f489ee6e308938e6189cafd3613db537cc7f41

Observation e0287d7c-4c0c-4b63-b969-f0e0eff96efc · outbound

This paper cites Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture.

Physics-Audited Agentic Discovery in Scientific Machine Learning Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture

Reference 36

Resolution
metadata mismatch
local_arxiv, observed 2026-07-09T12:56:14.902611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:8b0693fb4a4d242b279ac885e97ea219ac1435a6c19346c9638c8135cd47b5d9

Observation cb4e742e-aa6e-4b1d-abf3-a0fe92a25ebb · outbound

This paper cites Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes.

Physics-Audited Agentic Discovery in Scientific Machine Learning Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.578805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:0c53c04c513e008ad81a2212aa04f8d1ba7fca1b79db944b5661ba373621f0f9

Observation 92783dfe-4c61-44a1-865b-6b4a67e860ba · outbound

This paper cites Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D.

Physics-Audited Agentic Discovery in Scientific Machine Learning Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.580547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:f657e97ce3162f660bb8e52fc58205ce1146c6a8ff3141a9ddc786bdfd901150

Observation 056db3f4-27f1-4e9a-b2d9-1bb2244ceab9 · outbound

This paper cites Towards end-to-end automation of AI research.Nature, 651(8107):914–919, 2026.

Physics-Audited Agentic Discovery in Scientific Machine Learning Towards end-to-end automation of AI research.Nature, 651(8107):914–919, 2026

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.577360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:35287c054ec1bb490e0f9e067264b655be9e5c92bce578ddcf4ac8aa036c4589

Observation 8797bd21-79c3-4c83-8fc3-dfa4bf4cf3ea · outbound

This paper cites Narasimhan, and Yuan Cao.

Physics-Audited Agentic Discovery in Scientific Machine Learning Narasimhan, and Yuan Cao

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.580964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:844cadd56171b0a6b32792e02b87f94df61c7cbda0495272123ab89c0ba96e26

Observation 55d6bd8c-d080-4085-85c7-04119a751d6e · outbound

This paper cites Tenenbaum, and Igor Mordatch.

Physics-Audited Agentic Discovery in Scientific Machine Learning Tenenbaum, and Igor Mordatch

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.576876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:50b4c7b53dea88f490aea13ed6be08ade19aacd3624fcaafc8a898d3f312dbcf

Observation 06560ad4-fb81-4019-80ed-ab6faee9bbeb · outbound

This paper cites CAMEL: Communicative Agents for “Mind” Exploration of Large Language Model Society.

Physics-Audited Agentic Discovery in Scientific Machine Learning CAMEL: Communicative Agents for “Mind” Exploration of Large Language Model Society

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.582572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:543425200fb34d59d61a949e8ba9c361026ef358f7b129917e9b19174d6924cd

Observation ff4da646-694d-496e-9177-8fe223a38472 · outbound

This paper cites White, Doug Burger, and Chi Wang.

Physics-Audited Agentic Discovery in Scientific Machine Learning White, Doug Burger, and Chi Wang

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.590289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:7d3d911bfc662df61105d19514b28eff52df88a10a7b1b2d81e0d47385595740

Observation 0cfb1d8f-7efe-4e9b-8921-c87a1d2f08c4 · outbound

This paper cites MetaGPT: Meta programming for A multi-agent collaborative framework.

Physics-Audited Agentic Discovery in Scientific Machine Learning MetaGPT: Meta programming for A multi-agent collaborative framework

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.588454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:9021612953afa6c128f104b630fd922d0be105170ecfaa5259580359d9924821

Observation f879cbd7-f6c7-45e3-86f8-ac7827d9c00a · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Physics-Audited Agentic Discovery in Scientific Machine Learning Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.569953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:532ed6a195bc87f7443a16e5086b428d433823de76a379543321c9bdec3ac482

Observation 39b3ab21-3061-4e2a-97f5-72dd21058a85 · outbound

This paper cites Xing, Hao Zhang, Joseph E.

Physics-Audited Agentic Discovery in Scientific Machine Learning Xing, Hao Zhang, Joseph E

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.553063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:7e328c38effbc285a091bca889b0895aa6354024a52476088f440803eb2a5b00

Observation ec3eddfb-7890-415b-b108-faa969c8a5fc · outbound

This paper cites Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data.Journal of Computational Physics, 394:56–81, 2019.

Physics-Audited Agentic Discovery in Scientific Machine Learning Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data.Journal of Computational Physics, 394:56–81, 2019

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.551080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:4ec4fbec25d923346356371f9e19a8786a0e3f2a99f6fa7c2b751107596daec4

Observation b7bfc75a-4978-49f9-b27d-07d3da064f1b · outbound

This paper cites an unresolved cited work.

Physics-Audited Agentic Discovery in Scientific Machine Learning Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-07-09T12:56:15.558019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:3fa2a9e30deeb56d4b307893b59ccef3d28084c07ffa9d3d6b438b72ff42f020

Observation 0ce5ea3f-5e2e-4544-9fc0-ae413003d1ba · outbound

This paper cites Enforcing Analytic Constraints in Neural Networks Emulating Physical Systems.Physical Review Letters, 126(9), 2021.

Physics-Audited Agentic Discovery in Scientific Machine Learning Enforcing Analytic Constraints in Neural Networks Emulating Physical Systems.Physical Review Letters, 126(9), 2021

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.560033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:0e21f12770c5decac27dfb1e2dde85da58d142fc1e6ce39a0292a8eb1a4e0926

Observation 69527554-d3a2-4d25-ac12-c4cec909b320 · outbound

This paper cites Dill, Kyle Julian, and Mykel J.

Physics-Audited Agentic Discovery in Scientific Machine Learning Dill, Kyle Julian, and Mykel J

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.562004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:66e33657d9164278f67a6192a755dda5638d9bbf4682a0ae495b40c8c8d76985

Observation 02d8a2fd-ae9c-413a-9955-3165738c27f4 · outbound

This paper cites Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zelji´c, David L.

Physics-Audited Agentic Discovery in Scientific Machine Learning Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zelji´c, David L

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.563939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:4e4e187a16bdf4af531644810c5a232b51dcd3cd5185ca253855ebc41332c550

Observation ec733d48-60d6-472c-b509-9983aca885e8 · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

Physics-Audited Agentic Discovery in Scientific Machine Learning Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.568112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:71fd904460accfa7122bf24c7df2b3cb610953c6aa7d34043260cfe3609e5ce2

Observation 3ab8a687-6fde-4a67-b7bd-3166a16be060 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Physics-Audited Agentic Discovery in Scientific Machine Learning Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.544361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:ce0ea21cf318329800ff5564abd4d44dcb580257c796b306399c6812ab2bf1cb

Observation 8355f79e-de74-47b9-8367-3f9a74a81c91 · outbound

This paper cites Psaros, Xuhui Meng, Zongren Zou, Ling Guo, and George Em Karniadakis.

Physics-Audited Agentic Discovery in Scientific Machine Learning Psaros, Xuhui Meng, Zongren Zou, Ling Guo, and George Em Karniadakis

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T12:56:15.548879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-09T12:49:30.003524Z digest=sha256:a8bf5c4780f604828d6f895800bd01977989ac5884f87c2bfd92701da1140ab7

Pith citing papers

No inbound Pith citation observations are available.