Paper Citation Record · LEDGER

Manifold Constrained Tabular Deep Neural Networks

As of 4 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.09710.

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

pith.paper-citation-record.v1
2607.09710 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T17:23:01.013162Z

measured 36 of 36 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 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

36 of 36 outbound references displayed

verified exact0
verified fuzzy0
unresolved36
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fc110fbe-98cf-44ee-bcdd-427a01b648c7 · outbound

This paper cites Deepfm: a factorization-machine based neural network for ctr prediction.

Manifold Constrained Tabular Deep Neural Networks Deepfm: a factorization-machine based neural network for ctr prediction

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75cf1c76-09c0-47cc-b509-b42d57929abd · outbound

This paper cites A survey of data mining and machine learning methods for cyber security intrusion detection.IEEE Communications surveys & tutorials, 18(2):1153–1176, 2015.

Manifold Constrained Tabular Deep Neural Networks A survey of data mining and machine learning methods for cyber security intrusion detection.IEEE Communications surveys & tutorials, 18(2):1153–1176, 2015

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation faa01297-2a7e-4205-a5f6-9b3c6333a277 · outbound

This paper cites Early prediction of circulatory failure in the intensive care unit using machine learning.Nature medicine, 26(3):364–373, 2020.

Manifold Constrained Tabular Deep Neural Networks Early prediction of circulatory failure in the intensive care unit using machine learning.Nature medicine, 26(3):364–373, 2020

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation 6f54946e-61b8-4ae9-9224-71357a2c8cba · outbound

This paper cites Talent: A tabular analytics and learning toolbox.Journal of Machine Learning Research, 26(226):1–16, 2025.

Manifold Constrained Tabular Deep Neural Networks Talent: A tabular analytics and learning toolbox.Journal of Machine Learning Research, 26(226):1–16, 2025

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation 05968c41-8b2a-4868-b897-fea581f680ed · outbound

This paper cites Xgboost: A scalable tree boosting system.Cornell University, 2016.

Manifold Constrained Tabular Deep Neural Networks Xgboost: A scalable tree boosting system.Cornell University, 2016

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation 9edc87fe-c70f-4db2-9cc2-6272caa8fa38 · outbound

This paper cites Catboost: unbiased boosting with categorical features.

Manifold Constrained Tabular Deep Neural Networks Catboost: unbiased boosting with categorical features

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

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Observation 326c80be-1554-4d5a-8002-6569aace8ea8 · outbound

This paper cites Wide & deep learning for recommender systems.

Manifold Constrained Tabular Deep Neural Networks Wide & deep learning for recommender systems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a40379bd-b6ba-43ee-887a-9a79950e52ff · outbound

This paper cites Deep & cross network for ad click predictions.

Manifold Constrained Tabular Deep Neural Networks Deep & cross network for ad click predictions

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

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Observation 3267d7bc-867d-4ed7-a48d-4d636c212371 · outbound

This paper cites Tabnet: Attentive interpretable tabular learning.

Manifold Constrained Tabular Deep Neural Networks Tabnet: Attentive interpretable tabular learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation 7f01bb39-70f9-40a7-bd78-f72e243c2c26 · outbound

This paper cites On embeddings for numer- ical features in tabular deep learning.Advances in Neural Information Processing Systems, 35:24991–25004, 2022.

Manifold Constrained Tabular Deep Neural Networks On embeddings for numer- ical features in tabular deep learning.Advances in Neural Information Processing Systems, 35:24991–25004, 2022

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2405c65-4c25-4858-b356-7ea2c33a5201 · outbound

This paper cites Realmlp: Advancing mlps and default parameters for tabular data.

Manifold Constrained Tabular Deep Neural Networks Realmlp: Advancing mlps and default parameters for tabular data

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation e0e61db4-e9c8-49d1-aa2e-973105e8d9d3 · outbound

This paper cites Autoint: Automatic feature interaction learning via self-attentive neural networks.

Manifold Constrained Tabular Deep Neural Networks Autoint: Automatic feature interaction learning via self-attentive neural networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation 0909011f-1a53-4c5c-89e9-06d4b0dcbb68 · outbound

This paper cites Re- visiting deep learning models for tabular data.Advances in neural information processing systems, 34:18932–18943, 2021.

Manifold Constrained Tabular Deep Neural Networks Re- visiting deep learning models for tabular data.Advances in neural information processing systems, 34:18932–18943, 2021

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation 7f92cedc-ed8a-47d1-9ff3-4e00ad06f9dd · outbound

This paper cites ExcelFormer: A neural network surpassing GBDTs on tabular data.

Manifold Constrained Tabular Deep Neural Networks ExcelFormer: A neural network surpassing GBDTs on tabular data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

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Observation 7c7aa0dd-da87-4e23-b615-c77158008c79 · outbound

This paper cites Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems.

Manifold Constrained Tabular Deep Neural Networks Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

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Observation 8dc8ff98-ea9a-4e91-bef1-1795bc625528 · outbound

This paper cites Poincaré embeddings for learning hier- archical representations.Advances in neural information processing systems, 30, 2017.

Manifold Constrained Tabular Deep Neural Networks Poincaré embeddings for learning hier- archical representations.Advances in neural information processing systems, 30, 2017

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation 8c1c0d77-3188-463e-93a1-f88a8fd09863 · outbound

This paper cites Hyperbolic deep neural networks: A survey.IEEE Transactions on pattern analysis and machine intelligence, 44(12):10023–10044, 2021.

Manifold Constrained Tabular Deep Neural Networks Hyperbolic deep neural networks: A survey.IEEE Transactions on pattern analysis and machine intelligence, 44(12):10023–10044, 2021

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation 27c109ed-f5b9-497a-9b3a-e027a224afe7 · outbound

This paper cites TabTransformer: Tabular Data Modeling Using Contextual Embeddings.

Manifold Constrained Tabular Deep Neural Networks TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 925874cd-3281-43fa-a7b2-290ea18ef59c · outbound

This paper cites Tabm: Advancing tabular deep learning with parameter-efficient ensembling.

Manifold Constrained Tabular Deep Neural Networks Tabm: Advancing tabular deep learning with parameter-efficient ensembling

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d44103ff-f25a-46e1-8804-aa90af67e306 · outbound

This paper cites Tabr: Tabular deep learning meets nearest neighbors.

Manifold Constrained Tabular Deep Neural Networks Tabr: Tabular deep learning meets nearest neighbors

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc5bd5b0-78bc-4f63-b25f-f763ede413ad · outbound

This paper cites Revisiting nearest neighbor for tabular data: A deep tabular baseline two decades later.

Manifold Constrained Tabular Deep Neural Networks Revisiting nearest neighbor for tabular data: A deep tabular baseline two decades later

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11929a4b-7615-4549-ad71-bd6711c93d21 · outbound

This paper cites TabPFN: A transformer that solves small tabular classification problems in a second.

Manifold Constrained Tabular Deep Neural Networks TabPFN: A transformer that solves small tabular classification problems in a second

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddc20a12-bef0-4693-9151-0fa738589aa3 · outbound

This paper cites Hyperbolic graph convolutional neural networks.Advances in neural information processing systems, 32, 2019.

Manifold Constrained Tabular Deep Neural Networks Hyperbolic graph convolutional neural networks.Advances in neural information processing systems, 32, 2019

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation b16a5fb8-8254-4d5c-bba2-d53cf709acf0 · outbound

This paper cites A hyperbolic-to-hyperbolic graph convolutional network.

Manifold Constrained Tabular Deep Neural Networks A hyperbolic-to-hyperbolic graph convolutional network

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 616b7341-600d-4465-b597-b2dbd29effe9 · outbound

This paper cites Fully hyperbolic convolutional neural networks.Research in the Mathematical Sciences, 9(4):60, 2022.

Manifold Constrained Tabular Deep Neural Networks Fully hyperbolic convolutional neural networks.Research in the Mathematical Sciences, 9(4):60, 2022

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0de85ef4-95a6-4557-8e9b-42e44fcc4046 · outbound

This paper cites Hyperbolic image-text representations.

Manifold Constrained Tabular Deep Neural Networks Hyperbolic image-text representations

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42408367-3c78-4161-8d2f-d528aa1d50b3 · outbound

This paper cites Fast hyperboloid decision tree algorithms.

Manifold Constrained Tabular Deep Neural Networks Fast hyperboloid decision tree algorithms

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation 074a4383-ba96-4b60-9e11-8a7c8786067c · outbound

This paper cites Euclidean and poincare space ensemble xgboost.Information Fusion, 115:102746, 2025.

Manifold Constrained Tabular Deep Neural Networks Euclidean and poincare space ensemble xgboost.Information Fusion, 115:102746, 2025

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation d957848a-a895-4b29-8350-b73acbb2454c · outbound

This paper cites World Scientific, 2008.

Manifold Constrained Tabular Deep Neural Networks World Scientific, 2008

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62c2fab0-8de1-4564-88ac-39dfd4479c91 · outbound

This paper cites Hyperbolic graph neural networks: A tutorial on methods and applications.

Manifold Constrained Tabular Deep Neural Networks Hyperbolic graph neural networks: A tutorial on methods and applications

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation 84878db2-9c03-4774-9f98-f068768a41af · outbound

This paper cites Hyperbolic neural networks.Advances in neural information processing systems, 31, 2018.

Manifold Constrained Tabular Deep Neural Networks Hyperbolic neural networks.Advances in neural information processing systems, 31, 2018

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

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Observation 940f5938-0736-461c-ae66-5025e7ad2ed6 · outbound

This paper cites Riemannian adaptive optimization methods.

Manifold Constrained Tabular Deep Neural Networks Riemannian adaptive optimization methods

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31bf69c1-04a6-4e3d-b43f-21e3f24ea511 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017.

Manifold Constrained Tabular Deep Neural Networks Lightgbm: A highly efficient gradient boosting decision tree.Advances in neural information processing systems, 30, 2017

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfea6a43-d4d0-49af-afbc-c9ab7b3b54d0 · outbound

This paper cites Better by default: Strong pre-tuned mlps and boosted trees on tabular data.Advances in Neural Information Processing Systems, 37:26577–26658, 2024.

Manifold Constrained Tabular Deep Neural Networks Better by default: Strong pre-tuned mlps and boosted trees on tabular data.Advances in Neural Information Processing Systems, 37:26577–26658, 2024

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Unavailable: canonical work link unavailable.

Observation 8802f0eb-7a06-4e0d-9417-86beb1fad616 · outbound

This paper cites Statistical comparisons of classifiers over multiple data sets.

Manifold Constrained Tabular Deep Neural Networks Statistical comparisons of classifiers over multiple data sets

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Observation c9d3c535-da51-40fd-8cf9-1b727f3a8987 · outbound

This paper cites Hyperbolic neural networks++.

Manifold Constrained Tabular Deep Neural Networks Hyperbolic neural networks++

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T17:23:01.013162Z

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Pith citing papers

No inbound Pith citation observations are available.