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Paper Citation Record · LEDGER

Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.06674.

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

pith.paper-citation-record.v1
2405.06674 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:12:33.906884Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T08:01:00.514885Z

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 db7eaebb-8fb7-4498-a03e-ec7771dcaa4d · 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 Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T13:12:33.906884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:12:33.906884Z digest=sha256:bc3ae52349a2b26373882945b327e50c36aeb1f07520c45854c90c7a0f5dcdc5

Observation e09d43cc-907d-48a4-add6-bf6d58e59244 · 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 Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:45.716773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:45.716773Z digest=sha256:5cb422913f9ea40dfe768658906f3e9c1a06a04120689ad96940cf79f593ef9c

Observation c76a87aa-7006-4d29-8924-a53f8b9bfd34 · 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 Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T01:05:26.711952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:05:26.711952Z digest=sha256:ba154ab48d6927aba1cc7583bf72f5ec43e2aec0e6073d44f4163855390db9b4

Observation 3bb638ba-08e1-4846-9cb9-e1712782d29a · 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 Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 185

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:45:59.768655Z

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.

source=arxiv_source observed=2026-05-10T16:58:10.013475Z digest=sha256:976646d6d931a231d4c164b3aa79023b4dc53710bc0caf00250fa13aaf2b3ea2

Observation 0252cebd-654b-4e19-9bcc-967059230655 · 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 Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 170

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:01:00.518117Z

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.

source=arxiv_source observed=2026-05-10T16:51:19.555272Z digest=sha256:d28caaf6bf8c9383f34fc6192d7f86c6f6309a4ceaa495986ae77d30930b4c13

Observation 4067ad5c-d708-44a0-a910-8671edcdf643 · inbound

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation cites this paper.

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T03:25:58.148648Z

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.

source=arxiv_source observed=2026-05-11T02:28:20.366674Z digest=sha256:4c84574515d4bd4fbba006995e2492ff97895b42fd494f3d53c9dcb37d0e8d11