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Paper Citation Record · LEDGER

ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.07831.

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

pith.paper-citation-record.v1
2406.07831 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:46:45.664416Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T15:51:33.819365Z

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 7cf6acc1-50d5-41c6-8c1c-8dec0d2ee065 · 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 ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:45.664416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:46:45.664416Z digest=sha256:8c089f716ff60f4b56b894b2ef1ee298323e8920819fa9a9ae9e9d857b3dbaf4

Observation 0b3804b2-3c01-4010-a449-1184cb4973fd · inbound

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction cites this paper.

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-18T15:51:33.822053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-18T15:51:20.540625Z digest=sha256:24a21d057f78f709a3d2bbf0d13ee0e5247da27e5bd61ec8dcf96e5378ba448d