Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.14568.
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 2026-08-07T13:12:47.365452Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T19:56:33.618271Z
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 b204ebae-214e-4b16-8742-8d86f59b3739 · inbound
Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities cites this paper.
Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy
Reference 159
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:12:47.365452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7fd1806-0e7f-4412-9a69-0bf63414d52a · inbound
SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes cites this paper.
SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:43:50.385334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f1086c1-fa24-42d6-b632-a9e0e8ff1c0f · inbound
Both Ends Count! Just How Good are LLM Agents at "Text-to-Big SQL"? cites this paper.
Both Ends Count! Just How Good are LLM Agents at "Text-to-Big SQL"? SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:56:33.621131Z
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.