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Paper Citation Record · LEDGER

Evaluating Cross-Domain Text-to-SQL Models and Benchmarks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.18538.

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

pith.paper-citation-record.v1
2310.18538 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:24:25.823326Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T00:05:47.449118Z

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 14b15248-f036-4653-b224-5333b5f1a569 · inbound

CHESS: Contextual Harnessing for Efficient SQL Synthesis cites this paper.

CHESS: Contextual Harnessing for Efficient SQL Synthesis Evaluating Cross-Domain Text-to-SQL Models and Benchmarks

Reference 49

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T11:24:22.901661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-19T11:24:22.789901Z digest=sha256:9ea33280b20325549747ccf0947c0b7b3d7a5106788902f4ede3d67775b8e1c2

Observation 29a6ea8e-5b76-4551-adf8-f53574288c4c · inbound

M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis cites this paper.

M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis Evaluating Cross-Domain Text-to-SQL Models and Benchmarks

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:05:47.452562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T00:05:21.750651Z digest=sha256:fb8c71c50bda14281fc7d994840dd520fa0727f17336a5d9498142bde559bdfa

Observation fba94f27-761d-4acd-a0d0-017ad16ac8c7 · inbound

Establishing Best Practices for Building Rigorous Agentic Benchmarks cites this paper.

Establishing Best Practices for Building Rigorous Agentic Benchmarks Evaluating Cross-Domain Text-to-SQL Models and Benchmarks

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T20:24:25.823326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:24:25.823326Z digest=sha256:cb5cccbe625f5f08deb03976538625f5960450f9dc93ff11852e1a3c34210845

Observation 268a1572-29af-4b83-b5fd-051b265a3c1b · inbound

RAG Strategies for Natural Language-Based SQL Query and REST API Call Generation cites this paper.

RAG Strategies for Natural Language-Based SQL Query and REST API Call Generation Evaluating Cross-Domain Text-to-SQL Models and Benchmarks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T06:09:52.044514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:09:52.044514Z digest=sha256:17e4b43dd2a2595a983065b70d050e734ae42f463714ebe388cc3158e1de4308