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Paper Citation Record · LEDGER

Improving Memory Efficiency for Training KANs via Meta Learning

As of 10 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2506.07549.

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

pith.paper-citation-record.v1
2506.07549 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:37:58.195179Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:35:36.825962Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:29:57.460485Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact3
  • verified fuzzy4
  • unresolved18
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b32ab69f-2176-437d-a870-18779ed84d2f · outbound

This paper cites rKAN: Rational Kolmogorov-Arnold Networks.

Improving Memory Efficiency for Training KANs via Meta Learning rKAN: Rational Kolmogorov-Arnold Networks

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:37:57.656869Z digest=sha256:4599d596cfd7a96a2dd0d96ad4ff3523bc4b2fdb58f0117b40fe653a4069d6ee

Observation f541081c-b408-4d22-87b3-01bb57994b1e · outbound

This paper cites an unresolved cited work.

Improving Memory Efficiency for Training KANs via Meta Learning Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d5c4f6af-9367-4412-9182-60f41967e8c1 · outbound

This paper cites KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning.

Improving Memory Efficiency for Training KANs via Meta Learning KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning

Reference 4

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source=pdf_text observed=2026-08-07T05:37:57.677191Z digest=sha256:643498f0da9c5506b666cb2038413bfc0e527098b3080b72b9b004bf977b1781

Observation 7588c063-0764-4005-9ae6-1fc903ab3248 · outbound

This paper cites B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Improving Memory Efficiency for Training KANs via Meta Learning B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:37:57.686264Z digest=sha256:990d27f4af493eb3f66e126d4b6a6ad131332052d545985376656ac2f9f7b298

Observation f517450f-e9d2-4844-bf2d-043ce0959e39 · outbound

This paper cites an unresolved cited work.

Improving Memory Efficiency for Training KANs via Meta Learning Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:37:58.160789Z digest=sha256:4c38ee67ec8b2289f08a2e58e7b934834b8ece90e4d1cbccaa98469d628c91b5

Observation ed14514b-bc32-4636-ac8c-d1b4e7cb684e · outbound

This paper cites TKAN: Temporal Kolmogorov-Arnold Networks.

Improving Memory Efficiency for Training KANs via Meta Learning TKAN: Temporal Kolmogorov-Arnold Networks

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:37:57.717609Z digest=sha256:f8c127669e60d80d10eb512db26befc3edd3b45167008329c26f20384be9f236

Observation 6bcf6fc1-fe3a-4055-ada9-211c917b2981 · outbound

This paper cites an unresolved cited work.

Improving Memory Efficiency for Training KANs via Meta Learning Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:37:58.008717Z digest=sha256:74bb830f13ef537b4b40a8dcffa86f1b6ad23f21d27d84eea6c496ea410f81a1

Observation 6c9c3a67-d668-4a29-a7f7-519f99f555a4 · outbound

This paper cites TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting.

Improving Memory Efficiency for Training KANs via Meta Learning TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting

Reference 10

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source=pdf_text observed=2026-08-07T05:37:57.731917Z digest=sha256:e0642d03964797f77d72e7167169e0f7b8c3b3395ce4b3220b1f3ee2fc4edf49

Observation 8c36cd2e-4360-457c-9204-e70d25caec1f · outbound

This paper cites U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation.

Improving Memory Efficiency for Training KANs via Meta Learning U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation

Reference 11

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source=pdf_text observed=2026-08-07T05:37:57.738769Z digest=sha256:9a233d5cf4d9e04d970ebd39f49ad36986ac60da5668d4e0b902902bb8e0e9b0

Observation 8e805651-baf8-42e3-a73f-bbd7c3cb51de · outbound

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

Improving Memory Efficiency for Training KANs via Meta Learning Kolmogorov-Arnold Networks are Radial Basis Function Networks

Reference 12

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source=pdf_text observed=2026-08-07T05:37:57.747416Z digest=sha256:a02c5ed0edaf579080f7b2f0bf657f216e9a42d800c1b1e7d3c6c8df51f0b865

Observation 64465cec-7880-429c-9366-ac07139d70fe · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Improving Memory Efficiency for Training KANs via Meta Learning KAN: Kolmogorov-Arnold Networks

Reference 13

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source=pdf_text observed=2026-08-07T05:37:57.756064Z digest=sha256:68be299b3a4072fe9bf40b24fd859ba3face9ed0fcd54a08fb026cfb31bb0b81

Observation 001f90e7-b466-44c1-a280-464ac4673ba7 · outbound

This paper cites On the expressiveness and spectral bias of KANs.

Improving Memory Efficiency for Training KANs via Meta Learning On the expressiveness and spectral bias of KANs

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:37:57.805040Z digest=sha256:5840854d3f1f4b46d71116a4cc47f7435127b3cbf8f69bd83c66dcda86a447a5

Observation fa65dc9d-6080-41f3-9282-417da9ceac2f · outbound

This paper cites Kolmogorov-Arnold Transformer.

Improving Memory Efficiency for Training KANs via Meta Learning Kolmogorov-Arnold Transformer

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:37:57.815243Z digest=sha256:0a715109cced10000416e526e5f5b84b1743cde9173d6509a7e252fb5e91787f

Observation 275382d6-f684-4bf7-b835-1e60e3a3e6cc · outbound

This paper cites doi: https://doi.org/10.1016/j.jcp.2022.111232.

Improving Memory Efficiency for Training KANs via Meta Learning doi: https://doi.org/10.1016/j.jcp.2022.111232

Reference 20

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source=pdf_text observed=2026-08-07T05:37:57.827974Z digest=sha256:737b6042b4ee544dca95f529a16f9bdc8df97a45d7d39917943445501de4f5ab

Observation d043c9e3-03a2-4fc3-a6ac-d593b1051ebc · outbound

This paper cites Meta-learning via hypernetworks.

Improving Memory Efficiency for Training KANs via Meta Learning Meta-learning via hypernetworks

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 87888f77-bd94-42d3-abf4-97b5307c04a1 · outbound

This paper cites Unlike conventional convolution kernels, Kolmogorov- Arnold (KA) kernels consist of a set of univariate non- linear learnable activation functions.

Improving Memory Efficiency for Training KANs via Meta Learning Unlike conventional convolution kernels, Kolmogorov- Arnold (KA) kernels consist of a set of univariate non- linear learnable activation functions

Reference 22

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raw_fallback, observed 2026-08-07T05:37:59.753837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0d58dda2-0762-4fc3-9ee9-42074f87e7ac · outbound

This paper cites an unresolved cited work.

Improving Memory Efficiency for Training KANs via Meta Learning Unresolved cited work

Reference 24

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verified exact
raw_fallback, observed 2026-08-07T05:37:58.664316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:37:58.071727Z digest=sha256:17868aebe2508d6aae1a97ee1520b7ee902a62f62a60a538fac5b667d8279da5

Observation 3d36ac2e-13c4-4465-a929-b7f2fc915dfb · outbound

This paper cites Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies.

Improving Memory Efficiency for Training KANs via Meta Learning Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies

Reference 1989

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source=pdf_text observed=2026-08-07T05:37:57.695872Z digest=sha256:2bb4dec3b8f1e5897b662806e9ec4de349e1aa5cc79059686b5598e4ddca988b

Observation a7e1789b-141f-41f3-9c47-06c58f652cef · outbound

This paper cites KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks.

Improving Memory Efficiency for Training KANs via Meta Learning KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks

Reference 1990

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local_arxiv, observed 2026-08-07T05:37:59.250896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:37:57.706103Z digest=sha256:64121e6bef80a028ad190d83131e7dee9c95d0504d00907e7f6b120e8065a563

Observation 62e7690d-5284-4d08-a059-aa4c1f9d84bc · outbound

This paper cites KAC: Kolmogorov-Arnold Classifier for Continual Learning.

Improving Memory Efficiency for Training KANs via Meta Learning KAC: Kolmogorov-Arnold Classifier for Continual Learning

Reference 1997

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source=pdf_text observed=2026-08-07T05:37:57.726888Z digest=sha256:7b9afeed87744770e611c5b93b2e8d708a936ca760353688b318e5f109a5fc68

Observation 0b49bbd5-a197-4775-b0ef-d2466032c049 · outbound

This paper cites Small Sample Learning in Big Data Era.

Improving Memory Efficiency for Training KANs via Meta Learning Small Sample Learning in Big Data Era

Reference 2019

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Observation 6afdd866-2898-45d0-b0cb-7b3aec543f79 · outbound

This paper cites F., and Sacra- mento, J.

Improving Memory Efficiency for Training KANs via Meta Learning F., and Sacra- mento, J

Reference 2020

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raw_fallback, observed 2026-08-07T05:38:00.048203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T05:37:57.792875Z digest=sha256:7318f8cd5d86db4a819e43ab78928bba457fddf8ccf84ac02917e8a995bb8666

Observation e8f4434e-9f78-4983-bd5e-b2d06d6308e1 · outbound

This paper cites Finding Local Diffusion Schr\"odinger Bridge using Kolmogorov-Arnold Network.

Improving Memory Efficiency for Training KANs via Meta Learning Finding Local Diffusion Schr\"odinger Bridge using Kolmogorov-Arnold Network

Reference 2021

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local_arxiv, observed 2026-08-07T05:37:58.959185Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3fc60028-e5e4-4e49-a828-79edc49b8e78 · outbound

This paper cites Convolutional Kolmogorov-Arnold Networks.

Improving Memory Efficiency for Training KANs via Meta Learning Convolutional Kolmogorov-Arnold Networks

Reference 2022

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:37:57.663779Z digest=sha256:f6040483de4fbe2be3a7444d8ce50a9129911dc79de9ba2390f74d7e7654877c

Observation b87d31c6-9673-4b3b-896f-2f7c55182e7b · outbound

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

Improving Memory Efficiency for Training KANs via Meta Learning Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation

Reference 2023

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source=pdf_text observed=2026-08-07T05:37:57.783908Z digest=sha256:6c0157e348d8f1aaa2e230a18b9d6e1d94d45e5ce26c23bb709ceaa4ac7f22e2

Observation cd81f216-6106-401e-8b95-2d85642ab59f · outbound

This paper cites Wav-KAN: Wavelet Kolmogorov-Arnold Networks.

Improving Memory Efficiency for Training KANs via Meta Learning Wav-KAN: Wavelet Kolmogorov-Arnold Networks

Reference 2024

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:37:57.669710Z digest=sha256:eada4d83c62d82fa9cef52afe510fdf6da5f72b4bca5e08b41227b5fc6d1f5a9

Pith citing papers

Observation 2a998cd9-59c3-43cc-ad23-2a7875a09237 · inbound

Structural Kolmogorov-Arnold Convolutions: Learnable Function on the Values or the Filter Shape as Parameter-Efficient Alternative to Per-Edge Convolutional KANs cites this paper.

Structural Kolmogorov-Arnold Convolutions: Learnable Function on the Values or the Filter Shape as Parameter-Efficient Alternative to Per-Edge Convolutional KANs Improving Memory Efficiency for Training KANs via Meta Learning

Reference 15

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arxiv_id, observed 2026-07-04T16:29:57.461978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T00:35:36.825962Z digest=sha256:087e5e7480999e5303394cf78cb84917c0dea2900cb7b80d86ee69447c4cb60d