Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Review of the Challenges with Massive Web-mined Corpora Used in Large Language Models Pre-Training
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.07630.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:25:09.285880Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T21:01:13.212332Z
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 54b00524-b34d-4d69-adca-cee62e4d51be · inbound
On the Effectiveness of Large Language Models in Automating Categorization of Scientific Texts cites this paper.
On the Effectiveness of Large Language Models in Automating Categorization of Scientific Texts A Review of the Challenges with Massive Web-mined Corpora Used in Large Language Models Pre-Training
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:25:09.285880Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d03046c7-e487-4a43-bbcf-751fd20dece2 · inbound
Automating Categorization of Scientific Texts with In-Context Learning and Prompt-Chaining in Large Language Models cites this paper.
Automating Categorization of Scientific Texts with In-Context Learning and Prompt-Chaining in Large Language Models A Review of the Challenges with Massive Web-mined Corpora Used in Large Language Models Pre-Training
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:01:13.222759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.