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Paper Citation Record · LEDGER

S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.09099.

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

pith.paper-citation-record.v1
2409.09099 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:11:11.555199Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 638394ea-e553-4992-984f-ebbfa37df50e · inbound

Amber Pruner: Leveraging N:M Activation Sparsity for Efficient Prefill in Large Language Models cites this paper.

Amber Pruner: Leveraging N:M Activation Sparsity for Efficient Prefill in Large Language Models S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T05:11:11.555199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:11:11.555199Z digest=sha256:f4cad91e1e5acea45447126a7d3bde9f3fe3260694cc6984851c1a008d828f69

Observation dd3ad6f0-60bc-487b-9b72-cd531a3360b3 · inbound

Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression cites this paper.

Vanishing Contributions: A Unified Framework for Smooth and Iterative Model Compression S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:41:07.960703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T08:38:52.367887Z digest=sha256:f1aa0b28aa3cde52233630267522cbb7719df09ee9d26fd3b7d5fa4a29882bd0