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Paper Citation Record · LEDGER

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

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 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 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:59:21.897702Z

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 61f4d454-c0f8-4dcd-98fa-f95375828d14 · inbound

Preserving Deep Representations In One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework cites this paper.

Preserving Deep Representations In One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T11:20:38.397528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T11:20:38.397528Z digest=sha256:3977f248bbf08e7f70b6a5da1d31a6cbde161ee0f0225d99b22e10e90bf307c1

Observation 42e2224b-2cea-473e-a876-be2a81e5587a · inbound

HASSLE-free: A unified Framework for Sparse plus Low-Rank Matrix Decomposition for LLMs cites this paper.

HASSLE-free: A unified Framework for Sparse plus Low-Rank Matrix Decomposition for LLMs ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T17:26:45.375949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:26:45.375949Z digest=sha256:dbe0757a6ea47213336a65b90c8b2fd105e394d9c3451ae862667466f75cfad1

Observation a9f57036-7d34-4bdf-9bb4-4c52de7322eb · inbound

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods cites this paper.

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T23:59:21.897702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:59:21.897702Z digest=sha256:5adb921c6c2f499349ed3da214b56ce7742116a0df49915b93214d03c9cac79f

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:c9cc32ac5763d193624324e3975ae0388320f75bb3efba6d507dad0b0a344da9

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-18T15:51:20.540625Z digest=sha256:c986a74c02a4e4ed327d97f51f2f39a925e9c9c094a7cf9d2ad87ef31556ec47