Paper Citation Record · LEDGER

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.22527.

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

pith.paper-citation-record.v1
2507.22527 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:40:30.951592Z

measured 30 of 30 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 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

30 of 30 outbound references displayed

verified exact2
verified fuzzy17
unresolved4
parse uncertain0
malformed identifier1
metadata mismatch6

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98f06d3e-7f3d-4cd1-b3aa-f51ed3bd1fd2 · outbound

This paper cites write newline.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T11:40:30.868128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1b5e12c-f332-4ce9-8123-9f762d202d59 · outbound

This paper cites Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:40:31.465860Z

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.

Observation 31c2bfc0-1f9d-4d2b-9293-0a18349f5168 · outbound

This paper cites L., Zaremba, W., Bruna, J., LeCun, Y., and Fergus, R.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression L., Zaremba, W., Bruna, J., LeCun, Y., and Fergus, R

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.617843Z

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.

Observation 2ede70e9-039f-42a8-aabc-f5b7fcbe6b86 · outbound

This paper cites and Carbin, M.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression and Carbin, M

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T11:40:30.878421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 035681fe-d31a-4eb2-a31b-9733218e1a12 · outbound

This paper cites and Woods, R.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression and Woods, R

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.604112Z

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.

Observation 54d87b9b-79d3-4e8d-b97a-400b126e194a · outbound

This paper cites Compact model training by low-rank projection with energy transfer.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Compact model training by low-rank projection with energy transfer

Reference 6

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T11:40:31.453562Z

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.

Observation b564b2f0-c85d-44ea-b2c6-755acb209e59 · outbound

This paper cites Learning both weights and connections for efficient neural network.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Learning both weights and connections for efficient neural network

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.596369Z

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.

Observation f85e88e5-5b09-4eaf-930c-80f94f1b778e · outbound

This paper cites Deep residual learning for image recognition.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Deep residual learning for image recognition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.588212Z

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.

Observation 57112cf7-aa09-4e42-bb2a-832a48536989 · outbound

This paper cites A simple and flexible modification of gr \"u nwald--letnikov fractional derivative in image processing.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression A simple and flexible modification of gr \"u nwald--letnikov fractional derivative in image processing

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.579295Z

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.

Observation 071224eb-12ea-43aa-bc32-8e19c6cda3a0 · outbound

This paper cites Design of an image edge detection filter using the sobel operator.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Design of an image edge detection filter using the sobel operator

Reference 10

Resolution: malformed identifier; doi_truncated, observed 2026-08-06T11:40:30.988605Z

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.

Observation 8dd1c134-8b67-4793-af59-5c789496b9c3 · outbound

This paper cites Heuristic rank selection with progressively searching tensor ring network.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Heuristic rank selection with progressively searching tensor ring network

Reference 11

Resolution: verified exact; doi, observed 2026-08-06T11:40:30.979431Z

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.

Observation 06d5af69-d609-4d39-889e-dba4779ea3a6 · outbound

This paper cites Group sparsity: The hinge between filter pruning and decomposition for network compression.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Group sparsity: The hinge between filter pruning and decomposition for network compression

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.570605Z

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.

Observation 13c3575f-1f64-4514-8b6a-20d08fe04c76 · outbound

This paper cites Towards compact cnns via collaborative compression.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Towards compact cnns via collaborative compression

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.562362Z

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.

Observation 2987f876-f894-4d15-96cd-c56f65c025aa · outbound

This paper cites Tdlc: Tensor decomposition-based direct learning-compression algorithm for dnn model compression.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Tdlc: Tensor decomposition-based direct learning-compression algorithm for dnn model compression

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.553870Z

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.

Observation 4b23104a-f60a-4e5d-b13f-409bef04ae7d · outbound

This paper cites E., Shvai, N., and Nakib, A.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression E., Shvai, N., and Nakib, A

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.545134Z

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.

Observation 9f2de872-9bcb-4d7c-b835-a03aa274a0af · outbound

This paper cites T., Zniyed, Y., and Nguyen, T.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression T., Zniyed, Y., and Nguyen, T

Reference 16

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T11:40:31.388065Z

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.

Observation 4b113926-0f88-4e96-a876-1fa7cd2267df · outbound

This paper cites T., Zniyed, Y., and Nguyen, T.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression T., Zniyed, Y., and Nguyen, T

Reference 17

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T11:40:31.307975Z

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.

Observation 268cc147-4ec4-4291-84d9-08d0dc7dd3dd · outbound

This paper cites Stable low-rank tensor decomposition for compression of convolutional neural network.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Stable low-rank tensor decomposition for compression of convolutional neural network

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.536236Z

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.

Observation db60c274-964b-4e12-8ab7-22a024f1d7a1 · outbound

This paper cites Edp: An efficient decomposition and pruning scheme for convolutional neural network compression.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Edp: An efficient decomposition and pruning scheme for convolutional neural network compression

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T11:40:30.921353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc71710b-b2d1-4f85-a42a-832f88ad42a0 · outbound

This paper cites L., Tang, Y., and Huang, J.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression L., Tang, Y., and Huang, J

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.527861Z

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.

Observation 345c33b4-d012-4372-b412-c71e11877baa · outbound

This paper cites ELRT: Efficient Low-Rank Training for Compact Convolutional Neural Networks.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression ELRT: Efficient Low-Rank Training for Compact Convolutional Neural Networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T11:40:30.926660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a51946-4394-4a7f-927e-ed2230a8a5b3 · outbound

This paper cites Scop: Scientific control for reliable neural network pruning.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Scop: Scientific control for reliable neural network pruning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.517043Z

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.

Observation f4d2245d-d2e6-4231-ad4a-ae4073c01ea4 · outbound

This paper cites All-in-one hardware-oriented model compression for efficient multi-hardware deployment.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression All-in-one hardware-oriented model compression for efficient multi-hardware deployment

Reference 23

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T11:40:31.184271Z

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.

Observation 4e5876e3-2f50-43a2-8580-346bb0b9e3be · outbound

This paper cites Soft independence guided filter pruning.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Soft independence guided filter pruning

Reference 24

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T11:40:31.112216Z

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.

Observation 7dcf1bea-b397-49aa-8071-719bbb337b7c · outbound

This paper cites Arpruning: An automatic channel pruning based on attention map ranking.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Arpruning: An automatic channel pruning based on attention map ranking

Reference 25

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T11:40:31.046152Z

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.

Observation 9ffe4378-18f5-4c68-bb27-7ffe31fd0b38 · outbound

This paper cites Growing efficient deep networks by structured continuous sparsification.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Growing efficient deep networks by structured continuous sparsification

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.508773Z

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.

Observation 65ef9bfa-60da-4455-bb1d-4f73a8632343 · outbound

This paper cites and Komodakis, N.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression and Komodakis, N

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.500677Z

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.

Observation 16f8b767-bf23-4ea8-bacf-5cc784c40e41 · outbound

This paper cites A., Rhodes, A., Nachman, L., and Sundararajan, N.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression A., Rhodes, A., Nachman, L., and Sundararajan, N

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.492004Z

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.

Observation 6b09a2ad-464e-469e-9587-a642cd6c80c5 · outbound

This paper cites A systematic dnn weight pruning framework using alternating direction method of multipliers.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression A systematic dnn weight pruning framework using alternating direction method of multipliers

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.483097Z

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.

Observation 4ecf4bdc-1fee-4c93-a101-4ab0650c7813 · outbound

This paper cites Efficient neural network training via forward and backward propagation sparsification.

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression Efficient neural network training via forward and backward propagation sparsification

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:40:31.474314Z

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.

Pith citing papers

No inbound Pith citation observations are available.