Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Context Matters: A Strategy to Pre-train Language Model for Science Education
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2301.12031.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T18:44:39.796475Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T16:38:11.386667Z
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 aed4cc47-1967-4fd8-b40b-619b0a24c2bf · inbound
Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation cites this paper.
Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation Context Matters: A Strategy to Pre-train Language Model for Science Education
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T18:44:39.796475Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7bc7bf5-8ad1-4ab3-812c-35650ce7868a · inbound
Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research cites this paper.
Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research Context Matters: A Strategy to Pre-train Language Model for Science Education
Reference 83
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T16:38:11.389962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 30b2483d-9d72-4b24-9198-aefb2e0d0210 · inbound
Fine-tuning ChatGPT for Automatic Scoring of Written Scientific Explanations in Chinese cites this paper.
Fine-tuning ChatGPT for Automatic Scoring of Written Scientific Explanations in Chinese Context Matters: A Strategy to Pre-train Language Model for Science Education
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:59:51.424071Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.