Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PTD-SQL: Partitioning and Targeted Drilling with LLMs in Text-to-SQL
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.14082.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:12:39.455565Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T08:01:00.051713Z
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 5cb1daa1-aa14-4e93-9152-4a52e51dac85 · 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 PTD-SQL: Partitioning and Targeted Drilling with LLMs in Text-to-SQL
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:12:39.455565Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a1054a3-29e4-4e21-be47-9557ae4337b7 · 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 PTD-SQL: Partitioning and Targeted Drilling with LLMs in Text-to-SQL
Reference 289
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:45:59.376103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation dd336a83-2b99-4cd4-a384-fd0fbea81039 · 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 PTD-SQL: Partitioning and Targeted Drilling with LLMs in Text-to-SQL
Reference 274
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T08:01:00.054847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.