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Paper Citation Record · LEDGER

Evaluating Small Language Models for News Summarization: Implications and Factors Influencing Performance

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.00641.

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

pith.paper-citation-record.v1
2502.00641 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:52.679746Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T02:42:56.349654Z

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 aa2a1d2e-a869-4b36-a461-6ae4460f00cc · inbound

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications cites this paper.

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications Evaluating Small Language Models for News Summarization: Implications and Factors Influencing Performance

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T13:13:52.679746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:52.679746Z digest=sha256:27e14d426a6fc8f0f33d3a047da3f4f5c9b0584b192b93dcb98074ed69f16705

Observation 4d99ad0c-b765-4356-90b2-3c0f6082c539 · inbound

Fine-Tuning Code Language Models to Detect Cross-Language Bugs cites this paper.

Fine-Tuning Code Language Models to Detect Cross-Language Bugs Evaluating Small Language Models for News Summarization: Implications and Factors Influencing Performance

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-19T02:42:56.351643Z

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=2026-05-19T02:42:12.245477Z digest=sha256:27ddf324a2d6a37d9144bf8f1692700d38d1da492b01de2566af10e8486151b7