Paper Citation Record · LEDGER

Information Consistent Pruning: How to Efficiently Search for Sparse Networks?

As of 15 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2501.15592.

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

pith.paper-citation-record.v1
2501.15592 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:14:41.917317Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

44 of 44 outbound references displayed

verified exact1
verified fuzzy18
unresolved21
parse uncertain0
malformed identifier1
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d86cfb94-f928-4f50-9229-e893565ae128 · outbound

This paper cites How Can We Be So Dense? The Benefits of Using Highly Sparse Representations.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? How Can We Be So Dense? The Benefits of Using Highly Sparse Representations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.671237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79fb29c4-be13-4873-adde-033444bdba0b · outbound

This paper cites an unresolved cited work.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Unresolved cited work

Reference 2

Resolution: malformed identifier; no resolver link, observed 2026-08-10T14:14:41.682383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eb8acca-dd5d-43d7-8137-013280b0dc96 · outbound

This paper cites Advances in Neural Information Processing Systems34, 19637–19651 (2021).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Advances in Neural Information Processing Systems34, 19637–19651 (2021)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.721652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9008071f-4e7b-498e-8bfd-f0c8b0ffe98d · outbound

This paper cites IEEE Signal Processing Magazine29(6), 141–142 (2012).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? IEEE Signal Processing Magazine29(6), 141–142 (2012)

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.698975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20890308-6464-4983-8af3-e444ac135180 · outbound

This paper cites Sparse Networks from Scratch: Faster Training without Losing Performance.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Sparse Networks from Scratch: Faster Training without Losing Performance

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.703667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a808a61-2155-46df-a9fb-9df43832a2c8 · outbound

This paper cites CoRR (2023),http://arxiv.org/abs/2302.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? CoRR (2023),http://arxiv.org/abs/2302

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.696109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1d8a9ba1-7d3d-41a4-83ec-8726862da192 · outbound

This paper cites In: International conference on machine learning.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: International conference on machine learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.682619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e05af6bf-f0e5-4b58-9203-d886588d78c3 · outbound

This paper cites an unresolved cited work.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:14:42.667816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8ce4464d-4b79-4143-8af3-973b624a61f1 · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.729887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59c3dad0-9344-4760-831a-c0a1eb763254 · outbound

This paper cites Linear Mode Connectivity and the Lottery Ticket Hypothesis.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Linear Mode Connectivity and the Lottery Ticket Hypothesis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.734315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7c07022-b667-42f4-b4d3-d615600de1fe · outbound

This paper cites Stabilizing the Lottery Ticket Hypothesis.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Stabilizing the Lottery Ticket Hypothesis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.740219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79597dd2-7dd2-436b-863d-f9f9e51eca27 · outbound

This paper cites Slimming Neural Networks using Adaptive Connectivity Scores.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Slimming Neural Networks using Adaptive Connectivity Scores

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-10T14:14:42.207689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e6a83215-894b-4fea-a389-56e57aae7b08 · outbound

This paper cites IEEE Transactions on Neural Networks and Learning Systems (2022).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? IEEE Transactions on Neural Networks and Learning Systems (2022)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.648280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3c7a43d4-b3f7-4044-a0d0-47ba0360ac96 · outbound

This paper cites IEEE transactions on neural networks and learning systems 35(3), 3794–3808 (2024).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? IEEE transactions on neural networks and learning systems 35(3), 3794–3808 (2024)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.630214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1afd29d7-d38e-436c-980c-0c9a90718e02 · outbound

This paper cites In: 2020 25th International Conference on Pattern Recognition (ICPR).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: 2020 25th International Conference on Pattern Recognition (ICPR)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.615578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2f8900ae-59ee-43d4-b744-5b3c276ac4d7 · outbound

This paper cites Comprehensive Online Network Pruning via Learnable Scaling Factors.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Comprehensive Online Network Pruning via Learnable Scaling Factors

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:14:42.182137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1f7e0f5a-52c3-4548-9a3b-934f024b581a · outbound

This paper cites Learning both Weights and Connections for Efficient Neural Networks.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Learning both Weights and Connections for Efficient Neural Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.768916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c71893c-9364-4699-9402-695064cfabef · outbound

This paper cites an unresolved cited work.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.773797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbeee569-0da4-4b80-8a78-5d734a258731 · outbound

This paper cites IEEE Signal processing magazine29(6), 82–97 (2012).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? IEEE Signal processing magazine29(6), 82–97 (2012)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.587673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 22a78d37-02c9-47b7-8fd7-17370f138684 · outbound

This paper cites Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Network Trimming: A Data-Driven Neuron Pruning Approach towards Efficient Deep Architectures

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.784950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 000a4cba-1e97-4d0b-9a5b-29fc7a9ea5d9 · outbound

This paper cites In: International conference on machine learning.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: International conference on machine learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.789553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4016c478-e03a-4b7e-91e1-92b619fb592d · outbound

This paper cites How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:14:42.110669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c988738d-c705-4980-bc8c-0b8226983511 · outbound

This paper cites Un- published manuscript 40(7), 1–9 (2010).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Un- published manuscript 40(7), 1–9 (2010)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.562162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 697ec7b9-5b50-42e2-9540-939117c8853c · outbound

This paper cites Advances in neural information processing systems25 (2012).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Advances in neural information processing systems25 (2012)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.808736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6caceb81-9ce1-43b4-b176-643e99b07a64 · outbound

This paper cites Advances in neural infor- mation processing systems2 (1989).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Advances in neural infor- mation processing systems2 (1989)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.536046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aa772f36-0610-408d-9648-43d8afd6f307 · outbound

This paper cites SNIP: Single-shot Network Pruning based on Connection Sensitivity.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? SNIP: Single-shot Network Pruning based on Connection Sensitivity

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.817461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d17056c-e9b7-40d8-9364-c9808e03bf15 · outbound

This paper cites In: IJCAI.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: IJCAI

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.519303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3703edf7-73a4-4808-9bc1-d45107e277db · outbound

This paper cites In: Proceedings of the IEEE international conference on computer vision.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: Proceedings of the IEEE international conference on computer vision

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.499970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d14f04f5-0371-4ddb-996a-03ea1b0eee1c · outbound

This paper cites In: International Conference on Machine Learning.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: International Conference on Machine Learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.483133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd16c98f-01b5-4b5e-a92c-ba3597103b8f · outbound

This paper cites Advances in neural information processing systems32 (2019).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Advances in neural information processing systems32 (2019)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.459050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b82482f4-e3b5-40ff-a753-3195faac4919 · outbound

This paper cites Ad- vances in Neural Information Processing Systems33, 2925–2934 (2020).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Ad- vances in Neural Information Processing Systems33, 2925–2934 (2020)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.441155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation da416211-5a88-4971-9e24-fec52dd4ee66 · outbound

This paper cites IEEE transactions on neural networks and learning systems 32(2), 604–624 (2020).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? IEEE transactions on neural networks and learning systems 32(2), 604–624 (2020)

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.849465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69cf4818-a6b8-4f1f-a044-a1af72c3d0e7 · outbound

This paper cites ACM Computing Surveys (CSUR)51(5), 1–36 (2018).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? ACM Computing Surveys (CSUR)51(5), 1–36 (2018)

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.854532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc671022-2c47-41fc-99fc-cee947c10876 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.860185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0cdbe8c-088f-4d91-b666-70b0d298d103 · outbound

This paper cites The journal of machine learning research15(1), 1929–1958 (2014).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? The journal of machine learning research15(1), 1929–1958 (2014)

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.867360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f3c01de-6374-4e6e-8bbf-be6e6a525491 · outbound

This paper cites Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization

Reference 36

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T14:14:42.036156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7a7bac84-90d2-4f1c-9123-aa1d518af1f6 · outbound

This paper cites Picking Winning Tickets Before Training by Preserving Gradient Flow.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Picking Winning Tickets Before Training by Preserving Gradient Flow

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.883552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ed4389a-0450-483d-888c-64d9f636e7ca · outbound

This paper cites Advances in neural information processing systems29 (2016) 20 S.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Advances in neural information processing systems29 (2016) 20 S

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.391023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9170412d-a7ec-4d47-881d-e4fb5129ad3f · outbound

This paper cites In: 2021 IEEE Information Theory Workshop (ITW).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: 2021 IEEE Information Theory Workshop (ITW)

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.373528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 50562adc-06fe-417f-ae6a-1aad32016149 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.897223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a7ee426-8947-4888-abde-50c45dcf8a78 · outbound

This paper cites Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Drawing Early-Bird Tickets: Towards More Efficient Training of Deep Networks

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T14:14:41.902656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc98238a-15d2-44b2-8890-6e18ab5504c5 · outbound

This paper cites Advances in neural information processing systems32 (2019).

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Advances in neural information processing systems32 (2019)

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.360654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4b7b4bc2-8869-42e4-84f2-c4a93aee5f10 · outbound

This paper cites an unresolved cited work.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-10T14:14:42.339755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d12e00c7-82a5-4baf-8318-d1fe013ae7a4 · outbound

This paper cites In: 202025thInternationalConferenceonPatternRecognition(ICPR).pp.3868–3875.

Information Consistent Pruning: How to Efficiently Search for Sparse Networks? In: 202025thInternationalConferenceonPatternRecognition(ICPR).pp.3868–3875

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:14:42.315835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.