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Paper Citation Record · LEDGER

Low-Rank Prune-And-Factorize for Language Model Compression

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.14152.

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

pith.paper-citation-record.v1
2306.14152 v1

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:04:45.679663Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:52:35.842539Z

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 d5bde621-4b57-4d03-a51d-687dd0beeaa8 · inbound

Forget the Data and Fine-Tuning! Just Fold the Network to Compress cites this paper.

Forget the Data and Fine-Tuning! Just Fold the Network to Compress Low-Rank Prune-And-Factorize for Language Model Compression

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T19:04:45.679663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T19:04:45.679663Z digest=sha256:addc71f283d2370ab27326eb1d79c2b206f9f235d4b2ed799983170c03993a5d

Observation 6cc2ef41-5f7c-4614-af58-b1abd6d6fc14 · inbound

GradOT: Training-free Gradient-preserving Offsite-tuning for Large Language Models cites this paper.

GradOT: Training-free Gradient-preserving Offsite-tuning for Large Language Models Low-Rank Prune-And-Factorize for Language Model Compression

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:52:35.849855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:52:35.584322Z digest=sha256:9347c0eea4b3eb949ad165234756b87740756856b77c8412e0e2aeebd1a463e9