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Paper Citation Record · LEDGER

Rethinking Network Pruning -- under the Pre-train and Fine-tune Paradigm

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.08682.

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

pith.paper-citation-record.v1
2104.08682 v2

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:02:32.190370Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T06:34:01.050359Z

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 35855ee8-e80f-42ac-b12d-04bd5a91a277 · 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 Rethinking Network Pruning -- under the Pre-train and Fine-tune Paradigm

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:34:01.052778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-24T06:33:48.456209Z digest=sha256:349745b439b38427f4042da7e54fe1d1e52eddead73d158ea27ced3fa7a2e947

Observation 310fb90b-b517-46ec-b81a-2eb9f1beed01 · inbound

GraphTheft: Quantifying Privacy Risks in Graph Prompt Learning cites this paper.

GraphTheft: Quantifying Privacy Risks in Graph Prompt Learning Rethinking Network Pruning -- under the Pre-train and Fine-tune Paradigm

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T15:02:32.190370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:02:32.190370Z digest=sha256:b2fc87d65d93070fb1373d89976b782d0433c7f8967977104d96bfa983f4db77