Paper Citation Record · LEDGER

Evaluating the Text-to-SQL Capabilities of Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2204.00498.

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

pith.paper-citation-record.v1
2204.00498 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:26:56.416525Z

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
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malformed identifier0
metadata mismatch0

External citation measurements

52
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 d4a53423-3bfd-4d2c-9684-568f42e472d4 · inbound

Teaching Large Language Models to Self-Debug cites this paper.

Teaching Large Language Models to Self-Debug Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 118

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:24:24.778269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 945b1584-be55-4a36-be76-040d74428e56 · inbound

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

CHESS: Contextual Harnessing for Efficient SQL Synthesis Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 63

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T11:24:22.953133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d69d6c50-9d2c-465b-a596-1a0b10a9f990 · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 223

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:18:06.605100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 396b0b7f-9e44-48c4-bede-0a342854d372 · inbound

Meta-aware Learning in text-to-SQL Large Language Model cites this paper.

Meta-aware Learning in text-to-SQL Large Language Model Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:56.416525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ace4dee5-8977-4ffd-a42d-35bccbcc9a0c · 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 Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:09:05.116964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 658d5135-92e4-48ff-8857-4d3e09a3b923 · inbound

Knowledge Base Construction for Knowledge-Augmented Text-to-SQL cites this paper.

Knowledge Base Construction for Knowledge-Augmented Text-to-SQL Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:19:33.724722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2c8f63d-1657-4f8c-ae6f-cf35abf3ffc3 · 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 Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T13:12:41.751820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 945c6340-81d4-4bf9-9f21-aa6e50f21575 · inbound

LLM Inference Enhanced by External Knowledge: A Survey cites this paper.

LLM Inference Enhanced by External Knowledge: A Survey Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:21.816296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c73f30ac-9cb6-4c0b-8076-737b163ac0eb · 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 Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:43:48.389620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 344a51c8-b1be-408e-a170-db11b4d564f3 · inbound

Interactive Text-to-SQL via Expected Information Gain for Disambiguation cites this paper.

Interactive Text-to-SQL via Expected Information Gain for Disambiguation Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T19:17:17.049468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe1ec869-6da7-4ad6-bd34-6128832cb6b2 · inbound

THOR: Transformer Heuristics for On-Demand Retrieval cites this paper.

THOR: Transformer Heuristics for On-Demand Retrieval Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:56:02.615069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fbc4086-c485-4fa7-b5c0-81805e3b3b8a · inbound

SQLord: A Robust Enterprise Text-to-SQL Solution via Reverse Data Generation and Workflow Decomposition cites this paper.

SQLord: A Robust Enterprise Text-to-SQL Solution via Reverse Data Generation and Workflow Decomposition Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:45:57.655906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41f38542-63c2-486c-892d-88a15587d34f · inbound

Chatting with your ERP: A Recipe cites this paper.

Chatting with your ERP: A Recipe Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T10:47:55.105731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1fcd107-6815-47b9-a4b6-7596f5af3af5 · inbound

Confidence Estimation for Text-to-SQL in Large Language Models cites this paper.

Confidence Estimation for Text-to-SQL in Large Language Models Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T22:36:21.662011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 248ff1fe-02ec-4179-b5be-fcb89aa3e1f3 · inbound

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables cites this paper.

When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:40:40.854998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation caf60981-7921-4f4e-862f-bf56b7774d51 · inbound

SQLStructEval: Structural Evaluation of LLM Text-to-SQL Generation cites this paper.

SQLStructEval: Structural Evaluation of LLM Text-to-SQL Generation Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:55:51.647769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8a6bf66a-05cb-4fd9-a762-b830db0d5048 · inbound

AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views cites this paper.

AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:30:58.032502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a30a8ed6-c9cd-450a-b9ad-c9ecbc7e59ed · inbound

CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning cites this paper.

CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:01:00.618123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 601f59a8-0180-48a0-82b6-e2036eaaa12c · inbound

The Power of Order: Fooling LLMs with Adversarial Table Permutations cites this paper.

The Power of Order: Fooling LLMs with Adversarial Table Permutations Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:36:06.431090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d63e85c-2edc-4f5c-a454-c8b5e500c476 · inbound

The Power of Order: Fooling LLMs with Adversarial Table Permutations cites this paper.

The Power of Order: Fooling LLMs with Adversarial Table Permutations Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:26:16.638140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c92a6d9-4a2c-409f-9fd6-d014ea0b9d6d · 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 Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 254

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:45:59.662981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 02dd1365-95cd-4568-a52f-29789ab5ce2e · 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 Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 239

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:01:00.332645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f0c10a32-f983-40d5-b9ac-26faa45f58d3 · inbound

Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Method cites this paper.

Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Method Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T01:09:20.348789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9eda148f-a5cb-4b19-a6b3-190529aa8d7b · inbound

ClinQueryAgent: A Conversational Agent for Population Health Management cites this paper.

ClinQueryAgent: A Conversational Agent for Population Health Management Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 261

Resolution: verified exact; arxiv_id, observed 2026-05-21T01:33:56.279530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 550a390b-4d07-4704-96c0-5407ad68cefe · inbound

ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm cites this paper.

ProgramTab: Boosting Table Reasoning of LLMs via Programmatic Paradigm Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-07-14T06:18:02.826534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2f58c5a-699b-4b06-986d-a3194461a0fe · inbound

Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generation cites this paper.

Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generation Evaluating the Text-to-SQL Capabilities of Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T16:22:36.383016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.