Paper Citation Record · LEDGER

The Mathematics of Artificial Intelligence

As of 19 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 4 inbound Pith citation observations for arXiv:2501.10465.

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

pith.paper-citation-record.v1
2501.10465 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:21:15.310100Z

measured 32 of 32 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T02:20:39.109304Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

28 of 28 outbound references displayed

verified exact0
verified fuzzy24
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 8d6567a4-2d00-4de5-8bed-c439b2983910 · outbound

This paper cites Gradient ﬂows: in metric spaces and in the space of probability measures.

The Mathematics of Artificial Intelligence Gradient ﬂows: in metric spaces and in the space of probability measures

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T20:21:15.179737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d49bf90e-ca4c-4da2-be97-c3229dc84e3a · outbound

This paper cites Learning theory from ﬁrst principles.

The Mathematics of Artificial Intelligence Learning theory from ﬁrst principles

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.764433Z

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.

Observation d29181cd-04d2-4b58-a07e-4d922a18d576 · outbound

This paper cites Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport.

The Mathematics of Artificial Intelligence Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T20:21:15.190513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7676cb13-6cb1-4f80-9514-e91c10f16033 · outbound

This paper cites Universal approximation bounds for sup erpositions of a sigmoidal function.

The Mathematics of Artificial Intelligence Universal approximation bounds for sup erpositions of a sigmoidal function

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.748584Z

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.

Observation 6ba0910f-b6ed-40af-8241-c10ffa154698 · outbound

This paper cites Language models are few-shot learners.

The Mathematics of Artificial Intelligence Language models are few-shot learners

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.733703Z

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.

Observation b5c6d2db-2174-420c-9693-03da14af07e7 · outbound

This paper cites Neural ordinary diﬀerential equations.

The Mathematics of Artificial Intelligence Neural ordinary diﬀerential equations

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.718812Z

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.

Observation 3efa6a22-f766-476f-b22d-6c0a73aae652 · outbound

This paper cites On the global convergenc e of gradient descent for over-parameterized models using optimal transport.

The Mathematics of Artificial Intelligence On the global convergenc e of gradient descent for over-parameterized models using optimal transport

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.703464Z

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.

Observation 9ca4b9dc-3520-41e3-9c4e-619af23f7519 · outbound

This paper cites Approximation by superpositions of a si gmoidal function.

The Mathematics of Artificial Intelligence Approximation by superpositions of a si gmoidal function

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.687778Z

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.

Observation 1e3a788f-0dcf-459f-8baa-083fc75454f2 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

The Mathematics of Artificial Intelligence An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:21:15.221523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20f12e7b-ddff-4965-b6c0-54114b8ff045 · outbound

This paper cites Vaswani et al.

The Mathematics of Artificial Intelligence Vaswani et al

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.671476Z

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.

Observation 720b8d8f-2f5f-43a8-a36b-8b904119ff68 · outbound

This paper cites The emergence of clusters in self-attention dynamics.

The Mathematics of Artificial Intelligence The emergence of clusters in self-attention dynamics

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.656441Z

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.

Observation 1f77d621-dcae-4791-bd7e-c6cbd7e38c77 · outbound

This paper cites Generat ive adversarial networks.

The Mathematics of Artificial Intelligence Generat ive adversarial networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.641258Z

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.

Observation 05cecbc6-13e6-44be-abe6-9af425e8781a · outbound

This paper cites Evaluating derivatives: principles and tech- niques of algorithmic diﬀerentiation.

The Mathematics of Artificial Intelligence Evaluating derivatives: principles and tech- niques of algorithmic diﬀerentiation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.626029Z

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.

Observation f4cd5f09-f553-494b-8662-f34a7f2804d0 · outbound

This paper cites D eep residual learning for image recognition.

The Mathematics of Artificial Intelligence D eep residual learning for image recognition

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.608706Z

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.

Observation e90c6421-97b7-4520-a732-20955333d3bd · outbound

This paper cites M ultilayer feedforward networks are universal approximators.

The Mathematics of Artificial Intelligence M ultilayer feedforward networks are universal approximators

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.592807Z

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.

Observation b6db9a81-2a04-4a51-9b2d-33d1be7e4355 · outbound

This paper cites Th e variational formulation of the fokker–planck equation.

The Mathematics of Artificial Intelligence Th e variational formulation of the fokker–planck equation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.576879Z

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.

Observation 7bdcfe41-7e24-492d-b58e-1bd7c600d5ae · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural networks.

The Mathematics of Artificial Intelligence Imagenet classiﬁcation with deep convolutional neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.561011Z

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.

Observation 0665fe68-0438-4e3e-865b-fda4c37c6f4b · outbound

This paper cites Gradient-based learning applied to document recognition.

The Mathematics of Artificial Intelligence Gradient-based learning applied to document recognition

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.546332Z

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.

Observation 8653928c-7649-4f85-a3c3-7eb2692d2684 · outbound

This paper cites Flow matching for generative modeling.

The Mathematics of Artificial Intelligence Flow matching for generative modeling

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.530193Z

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.

Observation 3e1a7142-38a6-475c-8254-db5432b707af · outbound

This paper cites Implicit regular- ization of deep residual networks towards neural odes.

The Mathematics of Artificial Intelligence Implicit regular- ization of deep residual networks towards neural odes

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.513084Z

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.

Observation 0a1d2ff5-84d0-4ccd-9844-da6f25ee6294 · outbound

This paper cites Normalizing ﬂows for probabi listic modeling and inference.

The Mathematics of Artificial Intelligence Normalizing ﬂows for probabi listic modeling and inference

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.496412Z

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.

Observation c8361f63-273c-455d-b874-ff0e0613e45c · outbound

This paper cites Computational opti mal transport.

The Mathematics of Artificial Intelligence Computational opti mal transport

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.481114Z

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.

Observation 59958444-e869-4ddd-a0dc-6a4945c0931c · outbound

This paper cites A stochastic approxi mation method.

The Mathematics of Artificial Intelligence A stochastic approxi mation method

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.464997Z

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.

Observation 562098cf-267a-4723-8977-20a1ff63c152 · outbound

This paper cites U- net: Convolutional net- works for biomedical image segmentation.

The Mathematics of Artificial Intelligence U- net: Convolutional net- works for biomedical image segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.447633Z

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.

Observation 6f9e885a-c63a-4168-b9c1-35eee4231e77 · outbound

This paper cites The perceptron: a probabilistic mod el for information storage and organization in the brain.

The Mathematics of Artificial Intelligence The perceptron: a probabilistic mod el for information storage and organization in the brain

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.431325Z

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.

Observation ead74f51-fb34-4ace-a1d9-a2e46b9e290b · outbound

This paper cites Sinkform- ers: Transformers with doubly stochastic attention.

The Mathematics of Artificial Intelligence Sinkform- ers: Transformers with doubly stochastic attention

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.414612Z

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.

Observation b3f627d8-4fe4-41f2-b13c-84b745ba8ad2 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynami cs.

The Mathematics of Artificial Intelligence Deep unsupervised learning using nonequilibrium thermodynami cs

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:21:15.398888Z

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.

Observation 21142205-9378-4076-a6cf-26cfa9c2c679 · outbound

This paper cites an unresolved cited work.

The Mathematics of Artificial Intelligence Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:21:15.381440Z

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.

Pith citing papers

Observation f8bc77c1-ad73-47e4-a613-0dd19ed40706 · inbound

Explicit integral representations and quantitative bounds for two-layer ReLU networks cites this paper.

Explicit integral representations and quantitative bounds for two-layer ReLU networks The Mathematics of Artificial Intelligence

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:06:10.384355Z

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.

Observation ae10e5f0-bcaa-46a5-af7a-792cd3b50b65 · inbound

Explicit integral representations and quantitative bounds for two-layer ReLU networks cites this paper.

Explicit integral representations and quantitative bounds for two-layer ReLU networks The Mathematics of Artificial Intelligence

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:42:30.567947Z

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.

Observation f66e57be-b7be-4d66-b08a-e731dce6bf93 · inbound

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data The Mathematics of Artificial Intelligence

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:57:21.528204Z

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.

Observation 5e67144b-34fc-45fc-b2ff-58eec77cf98d · inbound

The physics of AI weather models cites this paper.

The physics of AI weather models The Mathematics of Artificial Intelligence

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-25T02:25:14.395775Z

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.