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Paper Citation Record · LEDGER

Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2411.06727.

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

pith.paper-citation-record.v1
2411.06727 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:41:33.769478Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:29:57.474992Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3ae60d8e-80e1-4839-8c79-64d232e126ed · inbound

Leveraging KANs for Expedient Training of Multichannel MLPs via Preconditioning and Geometric Refinement cites this paper.

Leveraging KANs for Expedient Training of Multichannel MLPs via Preconditioning and Geometric Refinement Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:41:33.769478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:41:33.769478Z digest=sha256:8121549194e0bd0ada6015ba3b470f02f4a36260c5eff26c0e3d779c9a9af344

Observation 79c2ef4f-be83-47c7-b08e-9865e85b5a3d · inbound

KANs need curvature: penalties for compositional smoothness cites this paper.

KANs need curvature: penalties for compositional smoothness Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:05:36.439280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T18:55:16.460190Z digest=sha256:916c118293ce89759ce62e07d4904802838a7a06d7c9ea72d82e3303613fae3a

Observation d677a6df-6c71-4e3f-aca6-74d926a75f27 · inbound

KAN Text to Vision? The Exploration of Kolmogorov-Arnold Networks for Multi-Scale Sequence-Based Pose Animation from Sign Language Notation cites this paper.

KAN Text to Vision? The Exploration of Kolmogorov-Arnold Networks for Multi-Scale Sequence-Based Pose Animation from Sign Language Notation Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:56:29.222219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T03:47:58.527417Z digest=sha256:64956d2ffebc0ffabb1e34205c8165bbddb13a71b8da54f008d8cc13a6f8622f

Observation 4425f20c-15ee-4c53-b4f6-c3ea94c9391b · inbound

KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition cites this paper.

KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:38:12.434911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T10:36:27.993163Z digest=sha256:f947b2163d4483cd5d040b5b660ada567fe1240c210b3771a958604c86bd864c

Observation 87e31936-ed1e-45f6-ba5c-2b13748c4b4b · inbound

KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition cites this paper.

KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-06-30T18:14:59.268710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T18:14:45.068438Z digest=sha256:a056001c1a55ec23536390959ceffb8630bff9d6ce150c619abe3bef2c63ef81

Observation 78e0d283-3a8d-4640-86df-9e1c55c26008 · inbound

Interpretable Kolmogorov-Arnold Network with Feature-Isolated Temporal Attention Mechanism for Electricity Load Forecasting cites this paper.

Interpretable Kolmogorov-Arnold Network with Feature-Isolated Temporal Attention Mechanism for Electricity Load Forecasting Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:39:45.792068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T08:35:56.106473Z digest=sha256:30122ad0af3f846feb1d39ae2e431b5594001e2c6d733d8bf449ea661e929cf7

Observation 6a1db7a3-1279-4a3f-8b22-7c540d169cc8 · 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 Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:29:57.476680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T00:35:36.825962Z digest=sha256:a7f04d764aac821cd2adf6504903151cb8431544288dea25ed4fcba9d2137233