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Paper Citation Record · LEDGER

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony

As of 8 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2506.03302.

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

pith.paper-citation-record.v1
2506.03302 v2

Coverage vector

measured 62 of 62 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

62 of 62 outbound references displayed

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External citation measurements

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Outbound references

Observation 8e55ec2e-027c-4482-b7cd-65b2eea4dcbf · outbound

This paper cites Machine learning and the physical sciences,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Machine learning and the physical sciences,

Reference 1

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This paper cites Explainable machine learning for scientific insights and discoveries,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Explainable machine learning for scientific insights and discoveries,

Reference 2

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Observation 31283614-6d88-4cf5-a8c2-4730ee447e5b · outbound

This paper cites Artificial intelligence: A powerful paradigm for scientific research,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Artificial intelligence: A powerful paradigm for scientific research,

Reference 3

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This paper cites Scientific discovery in the age of artificial intelligence,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Scientific discovery in the age of artificial intelligence,

Reference 4

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Observation c15756ab-0f8d-4014-a7cb-fe81678f7f51 · outbound

This paper cites Physics-informed machine learning,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Physics-informed machine learning,

Reference 5

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Observation ee9221ce-cf79-4146-8cb0-c639ef77f53c · outbound

This paper cites Physics-informed machine learning: case studies for weather and climate modelling,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Physics-informed machine learning: case studies for weather and climate modelling,

Reference 6

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Observation cd527ed0-addb-4e82-91b3-5021815bd754 · outbound

This paper cites Learning skillful medium-range global weather forecasting,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Learning skillful medium-range global weather forecasting,

Reference 7

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Observation 2beef697-6a0b-4b71-ba20-5a581c97966b · outbound

This paper cites Highly accurate protein structure prediction with al- phafold,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Highly accurate protein structure prediction with al- phafold,

Reference 8

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This paper cites Data-driven modeling and learning in science and engineering,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Data-driven modeling and learning in science and engineering,

Reference 9

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This paper cites Perspectives on the integration between first-principles and data-driven modeling,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Perspectives on the integration between first-principles and data-driven modeling,

Reference 10

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This paper cites It’s just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony It’s just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy,

Reference 11

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Observation d931b1c3-17df-4d5f-919e-ff4b68b50f96 · outbound

This paper cites How explainability contributes to trust in ai,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony How explainability contributes to trust in ai,

Reference 12

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This paper cites Ai and science: what 1,600 researchers think,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Ai and science: what 1,600 researchers think,

Reference 13

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Can we open the black box of AI?,

Reference 14

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Observation 926da584-8810-4236-abe3-279fbd666b2f · outbound

This paper cites KAN: Kolmogorov–Arnold net- works,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony KAN: Kolmogorov–Arnold net- works,

Reference 15

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Observation b96a922c-c25a-49e1-8072-6e48999ef913 · outbound

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony KAN 2.0: Kolmogorov-Arnold Networks Meet Science

Reference 16

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Observation 6b61f538-80bf-407d-92f1-4a5cbba4a339 · outbound

This paper cites From PINNs to PIKANs: Recent advances in physics-informed machine learning,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony From PINNs to PIKANs: Recent advances in physics-informed machine learning,

Reference 17

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony KAN-ODEs: Kolmogorov– Arnold network ordinary differential equations for learning dynamical systems and hidden physics,

Reference 18

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This paper cites Data-driven model discovery with Kolmogorov–Arnold networks,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Data-driven model discovery with Kolmogorov–Arnold networks,

Reference 19

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Neural architecture search: A survey,

Reference 20

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Deeply- supervised nets,

Reference 21

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This paper cites BranchyNet: Fast inference via early exiting from deep neural networks,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony BranchyNet: Fast inference via early exiting from deep neural networks,

Reference 22

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Conditional deep learning for energy-efficient and enhanced pattern recognition,

Reference 23

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Why should we add early exits to neural networks?,

Reference 24

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Deep residual learning for image recognition,

Reference 25

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This paper cites Multilayer feedfor- ward networks are universal approximators,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Multilayer feedfor- ward networks are universal approximators,

Reference 26

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Unresolved cited work

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony On functions of three variables,

Reference 28

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony On the representations of continuous functions of many variables by superposition of continuous functions of one variable and addition,

Reference 29

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This paper cites Kolmogorov-Arnold Networks are Radial Basis Function Networks.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Kolmogorov-Arnold Networks are Radial Basis Function Networks

Reference 30

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Observation 6e65e441-ed16-407b-8c18-bba1e230aa9d · outbound

This paper cites Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation

Reference 31

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This paper cites SineKAN: Kolmogorov–Arnold networks using sinusoidal activation func- tions,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony SineKAN: Kolmogorov–Arnold networks using sinusoidal activation func- tions,

Reference 32

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This paper cites Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation

Reference 33

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Observation 51e77322-7eba-492d-8a77-6c44101394db · outbound

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Wav-KAN: Wavelet Kolmogorov-Arnold Networks

Reference 34

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Observation 98bdef8e-7d07-48e5-ad45-93630334a05a · outbound

This paper cites On the limited memory BFGS method for large scale optimization,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony On the limited memory BFGS method for large scale optimization,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.359005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.930681Z digest=sha256:d783f13f9d1e950fa153c28bb6e8c19a4fbff07e90f548daedd13c2a92b00df1

Observation b5680a6b-8cd5-4b90-b31d-df6e9fcac213 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Adam: A Method for Stochastic Optimization

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T11:11:03.933945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:11:03.933945Z digest=sha256:cd3a8099a6e8cb83cee12aef34ba33f473c9db93bcd728bbdf15f575e64e398c

Observation 68043b85-e019-43fe-a1fa-39e6bc658b78 · outbound

This paper cites Bert loses patience: Fast and robust inference with early exit,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Bert loses patience: Fast and robust inference with early exit,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.349754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.937192Z digest=sha256:cd183daf42f541e8ff5780b6813ad56940fad34d0174e80e06e2e698d5dbb8b6

Observation 385e5b8e-f6fe-4c1a-ae1f-12556b207e91 · outbound

This paper cites BERxiT: Early exiting for BERT with better fine-tuning and extension to regression,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony BERxiT: Early exiting for BERT with better fine-tuning and extension to regression,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.341403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.940503Z digest=sha256:c152ac81381891cc9cc2fd7486f9e0b93f29523e487418a761a2a3e541c3eae2

Observation 94d2fd23-3c22-4bfe-b48e-4b50da188693 · outbound

This paper cites Adaptive inference through early-exit networks: Design, challenges and directions,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Adaptive inference through early-exit networks: Design, challenges and directions,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.333226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.943420Z digest=sha256:5b63d26a00aad72ed9bebd8bde6eb0e07f3b277380f55c4ac823400cccd855ef

Observation 1dd4fd41-df39-4e05-a2ff-7d7d164fadec · outbound

This paper cites Early-exit deep neural network - a comprehensive survey,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Early-exit deep neural network - a comprehensive survey,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.325314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.946073Z digest=sha256:bf5273a43a67421d5e11226c544dff95699e23ff71daa6102bf4660b0bc15124

Observation 4cf6d31c-d0f2-443c-9a19-949d81af7070 · outbound

This paper cites Densely connected convolutional networks,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Densely connected convolutional networks,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.317923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.949539Z digest=sha256:1d7d64f8a6e14b2f466ed71cffccd7f548c26e0da55642fc7b80bec165ce9f16

Observation 06d65c58-dab0-4f3b-9c41-07010dcd5352 · outbound

This paper cites AI Feynman: A physics- inspired method for symbolic regression,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony AI Feynman: A physics- inspired method for symbolic regression,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.310432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.953311Z digest=sha256:5fa6255530be5d0ea0b93ff767a4ef4dc8b8bb3df73b5cbe26583b17e61c9c31

Observation aaeb8390-a965-4dbb-aeaa-7ff8fc9100b8 · outbound

This paper cites AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.291866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.956184Z digest=sha256:16d6f4e4e8b29c69d9ae719e00a50ad9e8a376f4a874cd3654e07c048b4f9687

Observation d75531c1-e74d-4025-8833-9dba91627539 · outbound

This paper cites Multiple-valued stationary state and its instabil- ity of the transmitted light by a ring cavity system,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Multiple-valued stationary state and its instabil- ity of the transmitted light by a ring cavity system,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.281858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.959091Z digest=sha256:341bd2d1953e6e050e92238fa422206342bd21f2c410c5dca2e1683bfb0898d5

Observation 1002d8dd-f733-4bb4-957c-e0ce8e067651 · outbound

This paper cites Global dynamical behavior of the optical field in a ring cavity,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Global dynamical behavior of the optical field in a ring cavity,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.270974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.962251Z digest=sha256:d6a166022ebc8e15b6d2d87b6d803db9dfc319b4a348544dde7fa59064707c8c

Observation 5a5edae7-640d-4c32-910e-00a0878257c8 · outbound

This paper cites Nonlinear dynamics and population disappearances,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Nonlinear dynamics and population disappearances,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.260579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.965310Z digest=sha256:2b18368fe5ffbd5c134a0449bbd539621d8e60f10aeb89ac41ac06a4f10c1290

Observation 97c78513-78a8-420a-aaee-d43056fb5b97 · outbound

This paper cites Distal Interference: Exploring the Limits of Model-Based Continual Learning.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Distal Interference: Exploring the Limits of Model-Based Continual Learning

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:11:04.089123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.968149Z digest=sha256:eafc5a77239cfbe99a2938e02f61d7c2b7f3475e8ddb097b69d7172a7c379a7c

Observation 3a146412-c1d8-450f-a830-c8b893fa13d7 · outbound

This paper cites Airfoil self-noise and prediction,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Airfoil self-noise and prediction,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.248578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.971258Z digest=sha256:30eb3cc304124aae4072e2fcac2ae2c0575713aedbf1589bc39d8957df83ab9b

Observation de75c24a-b017-42a4-98b6-d34321a68c68 · outbound

This paper cites Local and global learning methods for predicting power of a combined gas & steam turbine,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Local and global learning methods for predicting power of a combined gas & steam turbine,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.238091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.974245Z digest=sha256:493b469a0ef740a9f04a6e1a23ece905b43dc627d32b17e784abb8e21a1a67f0

Observation 289d3b0c-8fea-4261-ae1b-8254fe77b1c7 · outbound

This paper cites Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.228227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.978383Z digest=sha256:fbfd360bbea07afb1373487a713abb63310f34da7ba6a3d7ab16cf2baba68e4d

Observation 00f4535d-7a27-4029-a5ce-3d445dfff0d1 · outbound

This paper cites A data-driven statistical model for predicting the critical temperature of a superconductor,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony A data-driven statistical model for predicting the critical temperature of a superconductor,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.218427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.982525Z digest=sha256:0a53dd41a596dd0fe5cce232cf98b2488590d29267d212ba99328bd067afacb4

Observation 3a85051a-a598-4eb7-838c-b131538967d5 · outbound

This paper cites MDR SuperCon datasheet ver.240322.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony MDR SuperCon datasheet ver.240322

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.209685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.986639Z digest=sha256:5ac34223f5cf2d72d00d3d30cacae1b6c3f4be3b0b1ea08ea8f96178c8cbe9cd

Observation fbcf101c-116a-4ecb-84a2-ad4164faddfe · outbound

This paper cites The UCI machine learning repository,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony The UCI machine learning repository,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.199821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.990390Z digest=sha256:da26dcfeea4e40d9c32ac4ab970d39005a67f6301f38c34e9ea513f210e221e7

Observation e20767f5-769a-4e5d-8b6b-6a4a6f52fcff · outbound

This paper cites Ensemble learning: A survey,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Ensemble learning: A survey,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.188606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.993182Z digest=sha256:341b0160d9bb4949b8d9d4a220afc2dd27c20a44aad13d213df537dfaf3599b5

Observation e26ed2e8-3947-45e2-94fd-071c86dd3933 · outbound

This paper cites an unresolved cited work.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:11:04.178603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.996159Z digest=sha256:87d1bbcf437578ef6112b5ca371acd66a0eaf815d07e59ccb9b09655fba38501

Observation 437801d0-adf3-438f-a590-bb4e26e9f10b · outbound

This paper cites A review of uncertainty quantification in deep learning: Techniques, applications and challenges,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony A review of uncertainty quantification in deep learning: Techniques, applications and challenges,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.168395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.999130Z digest=sha256:d0e3277e96f33a79c0254aee1a454ead8c14703ace49bc9c80fb4a76d0ec2bef

Observation 7da88c25-96a6-4719-950d-576277de856a · outbound

This paper cites Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretability.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretability

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:11:04.074657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:04.002076Z digest=sha256:79c060ae4ce80a02afea765f16edcfa365ac4d339df4002b203e91d569dd5082

Observation 8fe07d64-d00a-4e4e-93d1-bd0e265e4d30 · outbound

This paper cites Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:11:04.060284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:04.005789Z digest=sha256:fc9204b38164c75547c14e99557878b8d22cf201ba7d6bffb2dcb7814aec9e76

Observation 10818575-a76b-4cbf-b03d-185ec90eef80 · outbound

This paper cites DARTS: Differentiable architecture search,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony DARTS: Differentiable architecture search,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.157665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:04.009557Z digest=sha256:c5946610afc5d77d03b76863a039bc92debb3bd022e5690c369b1b91b0b5042d

Observation 1a8d1f55-150f-4610-a6d2-3ae8ba5af3d8 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T11:11:04.013104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:11:04.013104Z digest=sha256:e23f8275ffea9870fe6380be42dea731db33e8752b7a3fc14d7c4e61a94e6fed

Observation a6bf706a-2ba8-4db8-913c-d608809319a9 · outbound

This paper cites FourierKAN.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony FourierKAN

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:11:04.147300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:04.016511Z digest=sha256:93de504dbca288f720d47e5f8319e5c226f9533700d1934cc00ea053a8681fee

Observation be778af0-1bb9-4976-b331-5b1bcfcba2f7 · outbound

This paper cites an unresolved cited work.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Unresolved cited work

Reference 2019

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:11:04.551086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:11:03.836890Z digest=sha256:fd5b5ba4b8381852460eae78556ec7cbaab17190ff3bab769dcc3e559464e93b

Pith citing papers

No inbound Pith citation observations are available.