Paper Citation Record · LEDGER

BASE-SQL: A powerful open source Text-To-SQL baseline approach

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2502.10739.

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

pith.paper-citation-record.v1
2502.10739 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 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T23:37:54.128572Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 57810ace-1acd-4445-8ea7-8fad6bffe400 · inbound

DeepEye-SQL: A Software-Engineering-Inspired Text-to-SQL Framework cites this paper.

DeepEye-SQL: A Software-Engineering-Inspired Text-to-SQL Framework BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:10:57.609174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0d4302d4-99cf-45b3-a099-2592051dee3e · 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 BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:45:59.216126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1d4f1e38-8f68-471d-8284-0c2c3be10068 · 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 BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:00:59.901816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 771fb237-5fe3-4d15-968c-4816724a9e44 · inbound

ACE-SQL: Adaptive Co-Optimization via Empirical Credit Assignment for Text-to-SQL cites this paper.

ACE-SQL: Adaptive Co-Optimization via Empirical Credit Assignment for Text-to-SQL BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:36:58.929523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a50aff78-e634-43df-80fc-6ac03f61de03 · inbound

SQLConductor: Search-to-Policy Learning for Step-wise Text-to-SQL Orchestration cites this paper.

SQLConductor: Search-to-Policy Learning for Step-wise Text-to-SQL Orchestration BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:39:49.609324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 23d30207-d284-4f7d-b7bf-3e8860d1d8b1 · inbound

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL cites this paper.

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL BASE-SQL: A powerful open source Text-To-SQL baseline approach

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-11T23:37:54.128572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.