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Paper Citation Record · LEDGER

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2504.14452.

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

pith.paper-citation-record.v1
2504.14452 v2

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

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:08:57.322125Z

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 3142da95-84b7-45da-9503-ac79ab796a6d · inbound

A Lightweight Method to Disrupt Memorized Sequences in LLM cites this paper.

A Lightweight Method to Disrupt Memorized Sequences in LLM ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T20:08:57.322125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:08:57.322125Z digest=sha256:797bc4b6ddf8deb9cb431433c8d15a3016b23d7df66692e0bdb5f7b2a82e53c5

Observation 44529817-3cf0-42c8-885c-76b44e28e9f8 · inbound

GhazalBench: Evaluating LLM Understanding and Canonical Surface-Form Access in Persian Ghazals cites this paper.

GhazalBench: Evaluating LLM Understanding and Canonical Surface-Form Access in Persian Ghazals ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-03T03:53:36.446835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:53:36.446835Z digest=sha256:a0168b517451680008f9b80e92d50d2ae41881f7d3dc49c26f9fabacdfe44790

Observation 2e023a48-09fe-455b-8c18-fe298c8a7bdb · inbound

Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs cites this paper.

Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:06:01.925289Z

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=pdf_text observed=2026-05-10T04:14:03.015540Z digest=sha256:dcfcc7ad47de8d196389023f820a3b11a81c1e21695393d40aacc56992994dd8

Observation db03da17-49ad-4312-aa6a-6a7725f487ac · inbound

Prompt Governance? On Governing Technologies Governed by Natural Language cites this paper.

Prompt Governance? On Governing Technologies Governed by Natural Language ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T08:25:32.770331Z

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=pdf_text observed=2026-07-01T08:17:10.481202Z digest=sha256:0e6705d5939c0f58f3889b9e483ec603f353b0b68ce0c4e9320ed84d5fec028f

Observation e348474e-c286-4a39-bdd6-f989b6efd401 · inbound

Output Vector Editing for Memorization Mitigation in Large Language Models cites this paper.

Output Vector Editing for Memorization Mitigation in Large Language Models ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-06-26T21:30:02.972376Z

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=2026-06-26T21:23:26.901877Z digest=sha256:bf09cbdf65942e3aa6442bdf0602a7619e5249a762ca831757a5de2b4e858e86