Paper Citation Record · LEDGER

MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.07930.

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

pith.paper-citation-record.v1
2408.07930 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:12:45.462728Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T19:56:33.673543Z

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 cafddf35-e084-499d-b5ca-4763cea20529 · 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 MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 139

Resolution: unresolved; no resolver link, observed 2026-08-07T13:12:45.462728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98d67c5e-3550-4ee1-a5cf-6b7af737efb7 · 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 MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:43:49.622152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 804794e9-d54a-41e2-aba3-db67f1985eb7 · inbound

Chatting with your ERP: A Recipe cites this paper.

Chatting with your ERP: A Recipe MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T10:47:55.110380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39057bcf-a540-4d92-bd83-d9855ac10dbd · inbound

APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQL cites this paper.

APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQL MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T01:04:46.388222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78b3a9d9-92f6-4942-9d25-a4971dd93b0a · 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"? MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:56:33.678224Z

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 bba7abbc-968d-4f4f-90a1-a0799baff0da · 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 MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 208

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:45:59.603474Z

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 44d3cd40-89d2-497e-836e-c17e9c488b7f · 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 MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 193

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:01:00.069423Z

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.