Paper Citation Record · LEDGER

Dynamic Sparse Training with Structured Sparsity

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2305.02299.

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

pith.paper-citation-record.v1
2305.02299 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:06:57.455589Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:29:16.384426Z

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 93ea14e3-4ca7-488c-9965-413f3bca0e8c · inbound

Symmetric Pruning of Large Language Models cites this paper.

Symmetric Pruning of Large Language Models Dynamic Sparse Training with Structured Sparsity

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T21:55:16.221690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3813647-2d1c-423c-a7f8-020091578e14 · inbound

Advancing Weight and Channel Sparsification with Enhanced Saliency cites this paper.

Advancing Weight and Channel Sparsification with Enhanced Saliency Dynamic Sparse Training with Structured Sparsity

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T04:15:29.137105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e89eb15-27bd-466c-b85e-f5053c0536e0 · inbound

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks cites this paper.

TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks Dynamic Sparse Training with Structured Sparsity

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:57.455589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c9d4b81-0a21-4600-a0c2-d683edb36dc6 · inbound

Dynamic Sparse Training of Diagonally Sparse Networks cites this paper.

Dynamic Sparse Training of Diagonally Sparse Networks Dynamic Sparse Training with Structured Sparsity

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T04:15:14.519561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7b40c06-87dc-442a-bb6b-4b288eb7b9b5 · inbound

Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization cites this paper.

Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization Dynamic Sparse Training with Structured Sparsity

Reference 124

Resolution: unresolved; no resolver link, observed 2026-08-04T21:06:26.280149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 793d3538-7bc2-47a3-9ea2-345dc87693cc · inbound

SHUFFLESPARSE: Learned Shuffles for Structured Sparse Networks cites this paper.

SHUFFLESPARSE: Learned Shuffles for Structured Sparse Networks Dynamic Sparse Training with Structured Sparsity

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T09:39:37.022959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 332e0b4b-4f00-447a-9c33-16a0d7616acd · inbound

On the Stability of Growth in Structural Plasticity cites this paper.

On the Stability of Growth in Structural Plasticity Dynamic Sparse Training with Structured Sparsity

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-19T15:42:38.747256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 58b31f89-bc9b-4323-b66d-b62abb2d35b5 · inbound

On the Stability of Growth in Structural Plasticity cites this paper.

On the Stability of Growth in Structural Plasticity Dynamic Sparse Training with Structured Sparsity

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-30T20:55:03.841324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e30b54d3-278f-4fe5-b3e1-d54f1913410f · inbound

HORST: Composing Optimizer Geometries for Sparse Transformer Training cites this paper.

HORST: Composing Optimizer Geometries for Sparse Transformer Training Dynamic Sparse Training with Structured Sparsity

Reference 148

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:29:42.144734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d39193be-3ec9-4edd-8988-1c3bfac3b7a4 · inbound

GrapNet: A Programmable Dynamic-Architecture Neural Graph Substrate cites this paper.

GrapNet: A Programmable Dynamic-Architecture Neural Graph Substrate Dynamic Sparse Training with Structured Sparsity

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:29:16.386598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ebd3c216-b495-4a92-bb44-6cd0934186f0 · inbound

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference cites this paper.

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference Dynamic Sparse Training with Structured Sparsity

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-01T17:12:35.883139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.