Paper Citation Record · LEDGER

PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2403.09732.

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

pith.paper-citation-record.v1
2403.09732 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:09:04.122733Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T16:15:49.723373Z

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 5fb0f1f0-476f-494f-8954-1adab94f939e · inbound

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

CHESS: Contextual Harnessing for Efficient SQL Synthesis PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-19T11:24:22.984285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1451f352-4625-4e75-a81b-9afa6126cdde · 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 PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:09:04.122733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f12833c8-9598-4aef-9bd1-ca58b901d297 · 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 PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T13:12:38.970876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61a5816f-ef18-4f49-abce-70901c034bc3 · inbound

Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task cites this paper.

Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T01:05:26.805058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ea313c-fa8c-4998-a9b3-c53fe4213f59 · inbound

XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL cites this paper.

XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T06:52:59.939124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbd4210a-f73c-479e-b313-7224d4fef36e · inbound

LLM-Based SQL Generation: Prompting, Self-Refinement, and Adaptive Weighted Majority Voting cites this paper.

LLM-Based SQL Generation: Prompting, Self-Refinement, and Adaptive Weighted Majority Voting PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-16T11:00:51.699489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7b01ae5-bb03-49d9-b8ad-7ff762b80274 · inbound

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs cites this paper.

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:45:59.763216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 247e79c8-0f14-4017-8c70-c5452ceb6a1a · inbound

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning cites this paper.

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 115

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:01:00.861330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96574c03-2c0e-4a13-9fd5-d8dca52fb108 · inbound

EXPO-SQL: Execution-based Clause-level Policy Optimization for Text-to-SQL cites this paper.

EXPO-SQL: Execution-based Clause-level Policy Optimization for Text-to-SQL PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:05:36.873932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1a854930-e209-491c-987a-1abbda36f576 · inbound

Database Context Compression for Text-to-SQL on Real-World Large Databases cites this paper.

Database Context Compression for Text-to-SQL on Real-World Large Databases PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T16:15:49.724862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.