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Paper Citation Record · LEDGER

Harnessing Business and Media Insights with Large Language Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.06559.

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

pith.paper-citation-record.v1
2406.06559 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:48:51.979531Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T20:21:41.011375Z

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 1fdc6dce-ec65-49e7-af28-df532bd9c702 · inbound

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning cites this paper.

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning Harnessing Business and Media Insights with Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T20:48:51.979531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:48:51.979531Z digest=sha256:0d34d795bd52bd2a3d8a7fbfe4f841febb011ea10d0d3129c2c146b3e3f0d987

Observation 6cd35024-e9e8-46df-a7b3-5a203f871fbc · inbound

GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection cites this paper.

GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection Harnessing Business and Media Insights with Large Language Models

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-15T20:21:41.016965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:21:39.562410Z digest=sha256:b74d245c6249c0851fccbde9c85515338a1950d26567ca649a44243c435fdad4