Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.18812.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:25:09.218457Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T21:01:13.131227Z
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 7cdb4e3b-c661-47aa-b589-59e9c6351552 · 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 LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:25:09.218457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation abedef3f-27d3-4738-8f91-205dc5605373 · inbound
DTBench: A Synthetic Benchmark for Document-to-Table Extraction cites this paper.
DTBench: A Synthetic Benchmark for Document-to-Table Extraction LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:27:38.335219Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8214d901-3d1e-47bf-8210-77a789570c8d · 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 LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesis
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:01:13.139347Z
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.