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Paper Citation Record · LEDGER

Prompt Learning for News Recommendation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.05263.

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

pith.paper-citation-record.v1
2304.05263 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:06:56.936037Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T16:21:30.449267Z

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 581e8e47-3248-4a58-b2b6-91159daa9a10 · inbound

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis cites this paper.

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis Prompt Learning for News Recommendation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-11T21:06:56.936037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:06:56.936037Z digest=sha256:547ffd7b384da6b152895dc536bd7ec22b8d6b7879fcc5ec381e49fe8b7ec297

Observation 91f51e17-4904-467d-809b-0900901192ee · inbound

Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation cites this paper.

Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation Prompt Learning for News Recommendation

Reference 97

Resolution
verified exact
local_arxiv, observed 2026-08-10T16:21:30.453923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T16:21:30.395677Z digest=sha256:a5784056789f9cf84f77a38b16740ef7ce57b23ab38943c76995c5cce627b9e3