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Paper Citation Record · LEDGER

Residual Algebra for Representation-Preserving Learning

As of 19 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2608.07349.

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

pith.paper-citation-record.v1
2608.07349 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:52:03.661039Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

38 of 38 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 688667a9-1834-4f77-bc71-3bb8f01ab8c1 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 1

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Observation 26175c00-926c-4a7a-9537-e81135741116 · outbound

This paper cites Arık and Tomas Pfister.

Residual Algebra for Representation-Preserving Learning Arık and Tomas Pfister

Reference 2

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Observation 60fe4220-fb75-437e-b0c5-ebee1882460c · outbound

This paper cites Bailey, Jonathan Borwein, Marcos L´opez de Prado, and Qiji Jim Zhu.

Residual Algebra for Representation-Preserving Learning Bailey, Jonathan Borwein, Marcos L´opez de Prado, and Qiji Jim Zhu

Reference 3

Resolution
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Source-reported events for the cited work

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Observation 63a84d6c-e86c-4b93-a817-ba9500a150b5 · outbound

This paper cites Deep neural networks and tabular data: A survey.IEEE Transactions on Neural Networks and Learning Systems, 35(6):7499–7519, 2024.

Residual Algebra for Representation-Preserving Learning Deep neural networks and tabular data: A survey.IEEE Transactions on Neural Networks and Learning Systems, 35(6):7499–7519, 2024

Reference 4

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Source-reported events for the cited work

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Observation 09b5bc44-a455-4f53-9f3d-fe25a99f57b6 · outbound

This paper cites Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission.

Residual Algebra for Representation-Preserving Learning Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission

Reference 5

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9ca6d69d-0134-4731-bec2-0014ad8b9d40 · outbound

This paper cites Factor Fields: A Unified Framework for Neural Fields and Beyond.

Residual Algebra for Representation-Preserving Learning Factor Fields: A Unified Framework for Neural Fields and Beyond

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7f53f4be-f80c-40ca-a594-69131018b387 · outbound

This paper cites XGBoost: A scalable tree boosting system.

Residual Algebra for Representation-Preserving Learning XGBoost: A scalable tree boosting system

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 6c4c0eb8-d676-4a55-82cb-14b000bfc639 · outbound

This paper cites Double/debiased machine learning for treatment and struc- tural parameters.The Econometrics Journal, 21(1):C1–C68, 2018.

Residual Algebra for Representation-Preserving Learning Double/debiased machine learning for treatment and struc- tural parameters.The Econometrics Journal, 21(1):C1–C68, 2018

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e603efb6-45a5-4cbd-9770-563b47c444cc · outbound

This paper cites Empirical properties of asset returns: Stylized facts and statistical issues.Quanti- tative Finance, 1(2):223–236, 2001.

Residual Algebra for Representation-Preserving Learning Empirical properties of asset returns: Stylized facts and statistical issues.Quanti- tative Finance, 1(2):223–236, 2001

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 936c3552-827c-437c-8c66-be0d5405f0d3 · outbound

This paper cites Friedman.

Residual Algebra for Representation-Preserving Learning Friedman

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 00a5f203-a008-419d-a111-62706e4f8697 · outbound

This paper cites A survey on concept drift adaptation.ACM Computing Surveys, 46(4):1–37, 2014.

Residual Algebra for Representation-Preserving Learning A survey on concept drift adaptation.ACM Computing Surveys, 46(4):1–37, 2014

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 01c12c28-9f7c-4149-8765-598cbdfde64e · outbound

This paper cites Revisiting deep learning models for tabular data.

Residual Algebra for Representation-Preserving Learning Revisiting deep learning models for tabular data

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 810d9e7d-4b6a-4108-8d68-487bbac088f1 · outbound

This paper cites On embeddings for numerical features in tabular deep learning.

Residual Algebra for Representation-Preserving Learning On embeddings for numerical features in tabular deep learning

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 2342ec1d-5911-4dd0-855c-cb0423594d87 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 14

Resolution
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9db6a023-889a-4c0e-a472-4ed2057848fd · outbound

This paper cites Empirical asset pricing via machine learning.

Residual Algebra for Representation-Preserving Learning Empirical asset pricing via machine learning

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation d53e7911-67d0-41e2-81e9-737708474657 · outbound

This paper cites Harvey, Yan Liu, and Heqing Zhu.

Residual Algebra for Representation-Preserving Learning Harvey, Yan Liu, and Heqing Zhu

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5e6b6d03-fd28-4638-8f95-bf42d7347d0e · outbound

This paper cites Accurate predictions on small data with a tabular foundation model.Nature, 637:319–326, 2025.

Residual Algebra for Representation-Preserving Learning Accurate predictions on small data with a tabular foundation model.Nature, 637:319–326, 2025

Reference 17

Resolution
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Source-reported events for the cited work

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Observation b27f1ca2-ad6d-4670-8eeb-9a89ca488542 · outbound

This paper cites Jacobs, Michael I.

Residual Algebra for Representation-Preserving Learning Jacobs, Michael I

Reference 18

Resolution
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Source-reported events for the cited work

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Observation 35e6b552-80fa-48b8-a132-3378050ca55a · outbound

This paper cites Jordan and Robert A.

Residual Algebra for Representation-Preserving Learning Jordan and Robert A

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 966529f4-cd5f-4c2b-a076-415985f49e7f · outbound

This paper cites LightGBM: A highly efficient gradient boosting decision tree.

Residual Algebra for Representation-Preserving Learning LightGBM: A highly efficient gradient boosting decision tree

Reference 20

Resolution
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Source-reported events for the cited work

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Observation d8fffda1-1926-4f13-9d2e-2daf0f168344 · outbound

This paper cites Kelly, Seth Pruitt, and Yinan Su.

Residual Algebra for Representation-Preserving Learning Kelly, Seth Pruitt, and Yinan Su

Reference 21

Resolution
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Source-reported events for the cited work

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Observation 8a478a00-fff3-4980-a7aa-d1340e7585d9 · outbound

This paper cites K ¨unsch.

Residual Algebra for Representation-Preserving Learning K ¨unsch

Reference 22

Resolution
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Source-reported events for the cited work

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Observation 3376bb3d-5559-4831-a2c6-bef2f03dba37 · outbound

This paper cites Machine learning in the Chinese stock mar- ket.Journal of Financial Economics, 145(2):64–82, 2022.

Residual Algebra for Representation-Preserving Learning Machine learning in the Chinese stock mar- ket.Journal of Financial Economics, 145(2):64–82, 2022

Reference 23

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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 2026-08-19T06:32:44.657259+00:00.

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Observation 326cbcb8-d9ab-4b0c-9918-caa3c47b44a7 · outbound

This paper cites John Wiley & Sons, 2018.

Residual Algebra for Representation-Preserving Learning John Wiley & Sons, 2018

Reference 24

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Source-reported events for the cited work

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Observation 24228d33-7662-4556-8442-f3b1b2020b04 · outbound

This paper cites Accurate intelligible models with pairwise interactions.

Residual Algebra for Representation-Preserving Learning Accurate intelligible models with pairwise interactions

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8bb79097-46e9-4953-8d50-8f507948a8a1 · outbound

This paper cites When do neural nets outperform boosted trees on tabular data? InAdvances in Neural Information Processing Systems, Datasets and Bench- marks Track, volume 36, 2023.

Residual Algebra for Representation-Preserving Learning When do neural nets outperform boosted trees on tabular data? InAdvances in Neural Information Processing Systems, Datasets and Bench- marks Track, volume 36, 2023

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 24d5f961-b6a0-42fe-9929-084c349f8204 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 27

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Observation a0ce8062-f56f-49f9-8797-c9d8e89cc09b · outbound

This paper cites Politis and Joseph P.

Residual Algebra for Representation-Preserving Learning Politis and Joseph P

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2df4b248-b291-4b65-b9d6-30d28fec809a · outbound

This paper cites CatBoost: Unbiased boosting with categorical features.

Residual Algebra for Representation-Preserving Learning CatBoost: Unbiased boosting with categorical features

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 800438b5-d2a6-4ce8-a0dd-f83283ce645f · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.

Residual Algebra for Representation-Preserving Learning Outrageously large neural networks: The sparsely-gated mixture-of-experts layer

Reference 30

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 565d010e-b64b-4af8-87e6-12bb65e8c0c1 · outbound

This paper cites Tabular data: Deep learning is not all you need.Infor- mation Fusion, 81:84–90, 2022.

Residual Algebra for Representation-Preserving Learning Tabular data: Deep learning is not all you need.Infor- mation Fusion, 81:84–90, 2022

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:52:03.819080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a141715e-848c-4997-857f-6b4cf209be62 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 32

Resolution
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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation dfefa0a8-0be5-4215-86d2-9ef6c0cfd565 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 33

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 75db3900-6635-4d93-aca7-435e6e724281 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 34

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4ab3db49-ac0d-48a6-b97d-10696d966c28 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b9d8b36c-c003-4327-aaf1-12089d247911 · outbound

This paper cites Lower is better.

Residual Algebra for Representation-Preserving Learning Lower is better

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:52:03.757039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T05:52:03.652709Z digest=sha256:5bd2d46ef8d41d4f5e7b690de276bca02deaa77ac7e7dec0765199ca7afc2c23

Observation df511206-c4bf-4451-9fcf-7e6106963443 · outbound

This paper cites No triple is refitted, reweighted, or re-scored after the evaluation window opens.

Residual Algebra for Representation-Preserving Learning No triple is refitted, reweighted, or re-scored after the evaluation window opens

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T05:52:03.743874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T05:52:03.656951Z digest=sha256:21bca3e81709e68c664d58c71b87014a5ba09ea51012a1e5a23642b65e26ea02

Observation 8999ff47-b44b-484a-8e48-3e02c8484aa2 · outbound

This paper cites an unresolved cited work.

Residual Algebra for Representation-Preserving Learning Unresolved cited work

Reference 2026

Resolution
unresolved
raw_fallback, observed 2026-08-10T05:52:03.731301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T05:52:03.661039Z digest=sha256:0e6615f92dce29ee771d924ffe2276a751ff6ffeffdee394436817fb1f024da0

Pith citing papers

No inbound Pith citation observations are available.