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Paper Citation Record · LEDGER

Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2109.05157.

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

pith.paper-citation-record.v1
2109.05157 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:09:02.724749Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T01:32:17.415101Z

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 13c3a41e-b0eb-4a32-9b3e-ca78dae60b5a · inbound

DCG-SQL: Enhancing In-Context Learning for Text-to-SQL with Deep Contextual Schema Link Graph cites this paper.

DCG-SQL: Enhancing In-Context Learning for Text-to-SQL with Deep Contextual Schema Link Graph Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:09:02.724749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:09:02.724749Z digest=sha256:22c5e684e9146a9aa2ee7964c783c4e3c61a48d348630c543825da9ebcf3d666

Observation e22de1e3-e354-49d5-a1ff-d51483e9da66 · inbound

MARS-SQL: A multi-agent reinforcement learning framework for Text-to-SQL cites this paper.

MARS-SQL: A multi-agent reinforcement learning framework for Text-to-SQL Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:32:17.417600Z

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.

source=pdf_text observed=2026-05-18T01:31:40.920567Z digest=sha256:941031c8a934a2c4a7971b25ae36004f0c65b4ad817b34bd37abc7932d827af5