Paper Citation Record · LEDGER

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference

As of 21 July 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2512.15742.

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

pith.paper-citation-record.v1
2512.15742 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T22:56:36.735630Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-21T06:31:05.380196+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

28 of 28 outbound references displayed

verified exact6
verified fuzzy22
unresolved0
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malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f1f1bcc0-e813-4035-9a8b-255d6494f355 · outbound

This paper cites Tvm: An automated end-to- end optimizing compiler for deep learning.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Tvm: An automated end-to- end optimizing compiler for deep learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T22:58:39.874013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 5daec7a2-cffc-41ba-8104-db30bfcbae73 · outbound

This paper cites The pascal visual object classes (voc) challenge.IJCV, 88(2):303–338.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference The pascal visual object classes (voc) challenge.IJCV, 88(2):303–338

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T22:58:39.876408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 28e9801f-fd4f-4c5c-a12f-ed7ceb39b6dc · outbound

This paper cites Shift-invariant attribute scoring for kolmogorov-arnold networks via shapley value.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Shift-invariant attribute scoring for kolmogorov-arnold networks via shapley value

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:58:38.756013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0574e722-43b6-41de-a3f6-a8124b7d3a8a · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.558679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 8b45803e-41aa-4147-b2eb-36dc4eee21eb · outbound

This paper cites Kluwer Aca- demic Publishers.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Kluwer Aca- demic Publishers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.546527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 008d6736-e415-4352-9f2f-4567c108f2a2 · outbound

This paper cites Compressing Deep Convolutional Networks using Vector Quantization.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Compressing Deep Convolutional Networks using Vector Quantization

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-16T22:58:38.768385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 932da980-3f65-473d-900f-d35951831ef0 · outbound

This paper cites Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.552395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 74960ad1-9675-4c8b-a557-2be3970b7ac1 · outbound

This paper cites Deep residual learning for image recognition.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Deep residual learning for image recognition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.561645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 47a1a5c9-2372-47df-9c0f-b98c6847e9e4 · outbound

This paper cites Amc: Automl for model compression and acceleration on mobile devices.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Amc: Automl for model compression and acceleration on mobile devices

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.543933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation eadfb692-6d01-4ff5-bfd5-bf20fb21caa6 · outbound

This paper cites 1.1 computing’s energy problem (and what we can do about it).

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference 1.1 computing’s energy problem (and what we can do about it)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.571260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 05e1fcd5-8277-4113-b13a-c635f66157a9 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic-only inference.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Quantization and training of neural networks for efficient integer-arithmetic-only inference

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.574754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d45d1886-485f-4a1c-8258-45b661e44b17 · outbound

This paper cites arXiv preprint arXiv:2512.05117 , year=.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference arXiv preprint arXiv:2512.05117 , year=

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:58:38.760121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation b443bb96-228b-414e-b7a0-09c1293fef68 · outbound

This paper cites General- ization bounds for kolmogorov-arnold networks (kans) and enhanced kans with lower lipschitz complexity.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference General- ization bounds for kolmogorov-arnold networks (kans) and enhanced kans with lower lipschitz complexity

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.540622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 47ab05ea-b040-4063-b153-39d502688510 · outbound

This paper cites LFM2 technical report.arXiv preprint arXiv:2511.23404.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference LFM2 technical report.arXiv preprint arXiv:2511.23404

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:58:38.764118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d5ff9231-7a79-4374-9a5d-cc92abc14d72 · outbound

This paper cites Learning efficient convolutional networks through network slimming.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Learning efficient convolutional networks through network slimming

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.514431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 33046691-b5e5-4c36-922a-197531312d5d · outbound

This paper cites Kan: Kolmogorov-arnold networks.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Kan: Kolmogorov-arnold networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.525562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 9ce46fc5-1e5c-4bbf-9142-1b28b148bf30 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.537335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation f3b199a0-d5e5-43e1-958f-4812e22955f2 · outbound

This paper cites Importance estimation for neural network pruning.CVPR.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Importance estimation for neural network pruning.CVPR

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.568204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3653bc27-3dc6-4878-bdf8-18841eae37a0 · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding.ACM Transactions on Graphics (ToG), 41 (4):1–15.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Instant neural graphics primitives with a multiresolution hash encoding.ACM Transactions on Graphics (ToG), 41 (4):1–15

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.528999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 6e8a8d21-58e1-4e96-86db-20ebfe32acd6 · outbound

This paper cites Holographic reduced representations.IEEE Transactions on Neural Networks, 6(3):623–641.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Holographic reduced representations.IEEE Transactions on Neural Networks, 6(3):623–641

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.534602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 3ae876f0-0ac2-45cd-b848-b123d0615374 · outbound

This paper cites Holographic storage.Computer, 31(2):52–60.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Holographic storage.Computer, 31(2):52–60

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.518334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d9bccde6-5b65-4666-8435-5942ec6d2091 · outbound

This paper cites Executorch: Enabling on-device ai across mobile and embedded devices.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Executorch: Enabling on-device ai across mobile and embedded devices

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.549252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation d532d22f-dceb-4887-8ddf-4acc1334f244 · outbound

This paper cites MetaCluster: Enabling Deep Compres- sion of Kolmogorov-Arnold Network.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference MetaCluster: Enabling Deep Compres- sion of Kolmogorov-Arnold Network

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:58:38.772612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 722bb729-8d06-4231-a592-8304347a136b · outbound

This paper cites Implicit neural representations with periodic activation functions.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Implicit neural representations with periodic activation functions

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.555459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation dc481de6-a58e-495b-b2c1-d22df0456065 · outbound

This paper cites And the bit goes down: Revisiting the quantization of neural networks.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference And the bit goes down: Revisiting the quantization of neural networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.531608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 0cee97b8-8ad9-43f0-9b46-b2c52a6c941f · outbound

This paper cites Efficient processing of deep neural networks: A tutorial and survey.Proceedings of the IEEE, 105(12):2295–2329.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Efficient processing of deep neural networks: A tutorial and survey.Proceedings of the IEEE, 105(12):2295–2329

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:01:21.564906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation 9504346b-80c6-469c-8793-8c90053a5f2c · outbound

This paper cites PRKAN: Parameter-Reduced Kolmogorov-Arnold Networks.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference PRKAN: Parameter-Reduced Kolmogorov-Arnold Networks

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:58:38.751089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Observation ece0ff0f-ec74-417d-bf02-226a8d139c52 · outbound

This paper cites Mnasnet: Platform-aware neural architecture search for mobile.

SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference Mnasnet: Platform-aware neural architecture search for mobile

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T22:58:39.878508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.

Pith citing papers

No inbound Pith citation observations are available.