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Paper Citation Record · LEDGER

Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.15592.

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

pith.paper-citation-record.v1
2502.15592 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 2026-08-04T06:34:03.388597+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T13:56:04.958254Z

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 311d2ac5-0746-400f-b894-7c9bc126f68b · inbound

Adam's Law: Textual Frequency Law on Large Language Models cites this paper.

Adam's Law: Textual Frequency Law on Large Language Models Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-13T21:58:19.759275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-13T21:54:30.638392Z digest=sha256:e4d0d596216a600f6797e3387a87e1f25c971ad0048fcdb2f6c57911a89b48e4

Observation 47b2401e-63b7-4f4d-8ce8-cc5c25201214 · inbound

Adam's Law: Textual Frequency Law on Large Language Models cites this paper.

Adam's Law: Textual Frequency Law on Large Language Models Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning

Reference 5

Resolution
malformed identifier
no resolver link, observed 2026-07-13T13:56:04.958254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T13:56:04.958254Z digest=sha256:a9e66db757cfa8e32900acc1f031ac0bbf0c4d17a8b9883549cd5e0f1ce825cc