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Paper Citation Record · LEDGER

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2102.04010.

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

pith.paper-citation-record.v1
2102.04010 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:06:30.316475Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T06:34:01.034658Z

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 2eb4cea4-d1d4-4d0e-89b8-4300a3c03aaf · inbound

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs cites this paper.

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:34:01.037932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-24T06:33:48.456209Z digest=sha256:2290d82e7cf01dc58c25128b8d955d00b74c04061e918db1e6d1b0b2ba6ed8da

Observation 811baf5b-cbc8-40a8-b6b8-58e74ad81a01 · inbound

How to keep pushing ML accelerator performance? Know your rooflines! cites this paper.

How to keep pushing ML accelerator performance? Know your rooflines! Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T15:06:30.316475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:06:30.316475Z digest=sha256:35ad01ea3d489c5205258c31af2a21c2d4e9a1664c2c8fdfe8c13b830461c540

Observation fe987263-940b-4fa5-962d-91ebb5ad712a · inbound

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks cites this paper.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:47.171415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:46:47.171415Z digest=sha256:908a9a5c748ba4db0d4a6ec0da6d8ae8722fb060e4fac9685cf6bcac6c40e02a

Observation 8b521e1b-059c-4494-a251-aecb8bbc2a7a · inbound

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs cites this paper.

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:02:14.545469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T09:01:16.991413Z digest=sha256:16d3b80b5f9af7b824cbeada92b257473fe4a6dbbca66baffc96a004b463ad23

Observation 6a6063fa-63d9-4afe-b7a1-8ee8e0902e99 · inbound

Efficient Column-Wise N:M Pruning on RISC-V CPU cites this paper.

Efficient Column-Wise N:M Pruning on RISC-V CPU Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T14:55:28.444237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:55:28.444237Z digest=sha256:b30b48b43d84267e3c93944fdc62d63194f519b8ca6211d9cc980ba748811de4

Observation 1ac0b910-f407-4dcc-9bd2-73a951e8c40c · inbound

LExI: Layer-Adaptive Active Experts for Efficient MoE Model Inference cites this paper.

LExI: Layer-Adaptive Active Experts for Efficient MoE Model Inference Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T11:30:14.452931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:30:14.452931Z digest=sha256:4c9c85ccaa8b285008a89a677327db5affec92cb6fd350ad8d7d8fba708461ea

Observation cf8dcdbf-1288-4bc8-b510-bc5988b2f6d7 · 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 Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 253

Resolution
unresolved
no resolver link, observed 2026-08-04T21:06:27.057540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T21:06:27.057540Z digest=sha256:db998871d638c050f672acca3d6b860dec41093bd1d319284f3ddc8be9949660

Observation e51e2663-dd8c-4d78-980c-0339895f5b27 · inbound

ELAS: Efficient Pre-Training of Low-Rank Large Language Models via 2:4 Activation Sparsity cites this paper.

ELAS: Efficient Pre-Training of Low-Rank Large Language Models via 2:4 Activation Sparsity Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:26:12.755806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T17:07:18.278784Z digest=sha256:c29f85fd26c3f9e634cdf91fcc273a04acd7a4fd291af7b11f3e63ff92cdb4d8