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Paper Citation Record · LEDGER

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions

As of 15 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2512.01558.

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

pith.paper-citation-record.v1
2512.01558 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T19:15:42.926692Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:28:15.612179Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier1
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External citation measurements

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Outbound references

Observation f98d4312-53b9-433a-82d2-ba2f6c9a6cc0 · outbound

This paper cites This provides a controlled comparison: identical architecture, identical training protocol, but learning the full signal rather than the correction.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions This provides a controlled comparison: identical architecture, identical training protocol, but learning the full signal rather than the correction

Reference 1

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Observation 7e9e840e-38c0-4464-9141-8bf2d8be81ef · outbound

This paper cites The total parameter count for sequential 2×2×32 corrections (2,372 parameters) is compared against single-stage 3×64 networks (8,578 parameters).

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions The total parameter count for sequential 2×2×32 corrections (2,372 parameters) is compared against single-stage 3×64 networks (8,578 parameters)

Reference 2

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Observation a9a68e85-860b-46ed-8982-b9bbd21b45ac · outbound

This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 3

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Observation 599c208c-135d-4b4e-8f70-7ba1cc462716 · outbound

This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 4

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Observation dabb6af4-338c-4a5f-b78b-92c627a02727 · outbound

This paper cites Greydanus, M.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Greydanus, M

Reference 5

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Observation b9272f4c-8599-4444-9c6c-2b4ba6bc076b · outbound

This paper cites Cranmer, S.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Cranmer, S

Reference 6

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This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 7

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This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 8

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Observation 9d75043d-48ca-4f5c-acff-c1e1da001875 · outbound

This paper cites Illarionov, S.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Illarionov, S

Reference 9

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Observation 5cafde04-0189-4f18-a0a5-17d0e27a6e92 · outbound

This paper cites Poincar´ e, Acta Mathematica13, 1 (1890).

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Poincar´ e, Acta Mathematica13, 1 (1890)

Reference 10

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Observation 1867b71b-12ec-415d-94ec-d341313b5192 · outbound

This paper cites Laskar, Nature338, 237 (1989).

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Laskar, Nature338, 237 (1989)

Reference 11

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This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 12

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Observation 985a6400-f33c-4e44-9641-8da012482414 · outbound

This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 13

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Observation c6f89b98-425d-4712-abcb-e6e1c20df5a7 · outbound

This paper cites Sanchez-Gonzalez, J.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Sanchez-Gonzalez, J

Reference 14

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 15

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Observation 8b2dca90-ea00-481a-86c6-3f921cbff639 · outbound

This paper cites Batzner, A.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Batzner, A

Reference 16

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Observation 6003d59b-ed51-4f94-877a-dc838c4d7a68 · outbound

This paper cites Kondor, Proceedings of the National Academy of Sci- ences122(2025), in press.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Kondor, Proceedings of the National Academy of Sci- ences122(2025), in press

Reference 17

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Observation d2a57f05-1716-4006-972f-ed618f536afe · outbound

This paper cites Raissi, P.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Raissi, P

Reference 18

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 19

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Observation fa96da00-8993-4765-b1e8-2b4c0d8ff9b8 · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 20

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Observation d988ddc2-2522-413b-a6f1-91302857affa · outbound

This paper cites Hairer, C.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Hairer, C

Reference 21

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Observation 474f4b3c-d4d4-4b9b-ba22-d65e8cd0efd1 · outbound

This paper cites Elfwing, E.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Elfwing, E

Reference 22

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Adam: A Method for Stochastic Optimization

Reference 23

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Observation 1df14e4b-e7d6-457f-9e45-ab66df873e87 · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 24

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Observation dbbcd02f-0c68-484d-aa2a-5cbe4a91e330 · outbound

This paper cites an unresolved cited work.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 25

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Observation 015b9e9c-bfc0-416a-8b4d-f07d6643a8ed · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 26

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Observation 121df10b-3951-4df9-9364-37d3cc344adf · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 27

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Observation 0e8fd4ec-67fb-4127-ae8f-83cdf7e74a70 · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Reichstein, G

Reference 28

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Observation 14bf2961-cde0-4269-86fc-a367eeea6c41 · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 29

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Observation 81a75bb1-7c18-4a22-bb4b-b82d2c2153f6 · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Lecar, F

Reference 30

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This paper cites Kevorkian and J.

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Kevorkian and J

Reference 31

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 32

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Observation 056d13de-8971-4aff-b5d0-5a1f14e606a6 · outbound

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Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Unresolved cited work

Reference 33

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Observation ea21e919-1085-43da-9456-fcc62df29f22 · outbound

This paper cites Talagrand,What Is a Quantum Field Theory?(Cam- bridge University Press, 2022).

Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions Talagrand,What Is a Quantum Field Theory?(Cam- bridge University Press, 2022)

Reference 34

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Pith citing papers

Observation 41f4a61a-1124-4123-9b29-871bb7e5c91b · inbound

Dynamical and Optimization Trade-offs of Levi--Civita Coordinates for Learned Close-Encounter Dynamics cites this paper.

Dynamical and Optimization Trade-offs of Levi--Civita Coordinates for Learned Close-Encounter Dynamics Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions

Reference 14

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