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Paper Citation Record · LEDGER

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs

As of 18 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2509.05899.

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

pith.paper-citation-record.v1
2509.05899 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:24:42.026474Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e18a0c1-ca7f-491d-b138-5a2170d9f2cc · outbound

This paper cites C3: Zero-shot Text-to-SQL with ChatGPT.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs C3: Zero-shot Text-to-SQL with ChatGPT

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.944661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.944661Z digest=sha256:ef4c3b9e83d7f6a9e7e3f10a10a4a609f1ce04fb86701b395cb028a0a87bc46b

Observation d1046e4d-c176-487e-bb31-fe525f85ba67 · outbound

This paper cites Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.948804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.948804Z digest=sha256:84e97b370988847ac49371554a6b18a1642a883203e29341ac7bb33d1ea6c90f

Observation b3593bcb-50fc-4844-ba65-05b17e02bb25 · outbound

This paper cites Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.957431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.957431Z digest=sha256:c284d0fd42b43828c8c683473290cf172c03d4bdd95f1664143429841c918d5e

Observation 290bcc1c-39c7-444c-b5e2-b201fb110bfd · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.962226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.962226Z digest=sha256:9841bb430227a263aaa5d61b6ff39b6e42064b899b912693b1a008dc32acd95e

Observation 94c8ee23-6c30-450e-a759-aa5692362f6c · outbound

This paper cites MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.966334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.966334Z digest=sha256:52bb8522a9d1c3ff9dc76bf07e66b7a70c98b55c7a5e82a25d89da88f92be4e3

Observation 05e4a02c-8f3b-417e-873d-1de17175baed · outbound

This paper cites LLM Evaluators Recognize and Favor Their Own Generations.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs LLM Evaluators Recognize and Favor Their Own Generations

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.978223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.978223Z digest=sha256:6ef133fbeaff5a236a7adf073be9f0150b7aa8aeb0576a63c148fe1f7e12ea17

Observation 658cbb6a-d3ce-44cc-bcb5-452f7fd4b50f · outbound

This paper cites Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.982358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.982358Z digest=sha256:2eb515bbf0c0cbc2376cc0368635d86bcbac594367ca0a7a935e08b4840a4e98

Observation 4a8c8c1f-1eec-4a58-9aa1-4cc140b0b030 · outbound

This paper cites Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generation.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.990483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.990483Z digest=sha256:1a6a981e901120eec7d6546218a046d7469cab3e83636911321a2b7d6b55e485

Observation 0362454f-9eb2-465a-a855-d7b7226c24a4 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Code Llama: Open Foundation Models for Code

Reference 15

Resolution
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no resolver link, observed 2026-08-15T16:24:41.994404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.994404Z digest=sha256:f1eeaab32b16700df0de95246c42970cbaaaf2daa197059b3a3fa30009d6b7ef

Observation 76c215ce-290f-479b-bcc6-7a7ba460742c · outbound

This paper cites Small LLMs Are Weak Tool Learners: A Multi-LLM Agent.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Small LLMs Are Weak Tool Learners: A Multi-LLM Agent

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.998551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.998551Z digest=sha256:95068ff88aa11945ef571c423f766b4e36105fa76ae3e54de4aaaaacc451b268

Observation 78053b07-94fa-4e15-8492-f3cd2db8622a · outbound

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

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:42.002581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:42.002581Z digest=sha256:1b980666832934766ad6e5c6d440d0a81e2f556a7f3838caf5f869faf2998141

Observation e3675680-e415-4fd9-8954-6911e3f1fd14 · outbound

This paper cites MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:42.006918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:42.006918Z digest=sha256:f1c34f6bcaa663169d8a6bc4c111931b962d84cea51369d1a5d2b1cab9809b15

Observation 29c0ce13-7418-4f54-81ab-3373acad1f9b · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:42.010525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:42.010525Z digest=sha256:713755722a70fd6c4d8118c308a3c0c7ff1878d57cd58276633b91ca0d33012d

Observation 7aea2d86-f7b0-48a4-accd-8c2fc67dddc5 · outbound

This paper cites Qwen2 Technical Report.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Qwen2 Technical Report

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:42.014503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:42.014503Z digest=sha256:ec10b59e8ed406d0c1431eb0cf6256194c84db547a411ec3b28903df72140a26

Observation 789e3d54-d557-4e97-b2a7-eb5325009de5 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:42.022484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:42.022484Z digest=sha256:c4f65e2d3f25f2aa17091b0fedbf384c6371bdc29f69629e98b20cfb7938ac58

Observation 5a4e86a2-6009-4c48-a5b5-3b4406308e02 · outbound

This paper cites Experiments.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Experiments

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:24:42.318552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T16:24:42.026474Z digest=sha256:3fb5b40dae68a2924485895a42cbce6e65883b8a304e8e492fb0157120bb0a64

Observation c103a6be-9194-493b-9767-dfe86f08efd5 · outbound

This paper cites PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.970245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.970245Z digest=sha256:8d787de0c304381e2f80e4433d1548c287b97f8fef7fe578f6fe5ff74cb074e2

Observation 754c45b4-17c6-42f3-a9d9-b04dd10ec2df · outbound

This paper cites Decoupled Weight Decay Regularization.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Decoupled Weight Decay Regularization

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.974259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.974259Z digest=sha256:376d3d0157352aeebc808081f866a2747adf9500fb9e879570028af8a14af9a9

Observation 1930f385-5bd6-4812-a194-0d01661561dc · outbound

This paper cites Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 2018

Resolution
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no resolver link, observed 2026-08-15T16:24:42.018653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:42.018653Z digest=sha256:c5cad6f2fc65c9ef50981ca93dd4b137b0ba3766197f3764cb75f006b16b9ae6

Observation bd7f94cf-3a2d-4f8a-b846-b67d209cf3ac · outbound

This paper cites Natural SQL: Making SQL Easier to Infer from Natural Language Specifications.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs Natural SQL: Making SQL Easier to Infer from Natural Language Specifications

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.952848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.952848Z digest=sha256:44bf41f3e73f9b977e0814c48550d70a8a6e187765cf3f3538be35ff8aaeccbf

Observation 94523183-05ab-4c48-98e6-62f4372bdbcb · outbound

This paper cites A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.986416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.986416Z digest=sha256:664d29be8d4da4437ac900c999462068b802d9ec8907a90cdcd407f1a1968983

Observation a0ec8d7b-3650-4ff4-8221-12cb37936080 · outbound

This paper cites GPT-4 Technical Report.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs GPT-4 Technical Report

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.936003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.936003Z digest=sha256:36a532a56d79b8888b68372921e86a6ba8cc3ca50a414b6dade177276425f6c8

Observation 4b247c68-5d33-4dfd-91a5-0930959e9eb0 · outbound

This paper cites SQLFixAgent: Towards Semantic-Accurate Text-to-SQL Parsing via Consistency-Enhanced Multi-Agent Collaboration.

X-SQL: Expert Schema Linking and Understanding of Text-to-SQL with Multi-LLMs SQLFixAgent: Towards Semantic-Accurate Text-to-SQL Parsing via Consistency-Enhanced Multi-Agent Collaboration

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-15T16:24:41.940451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:24:41.940451Z digest=sha256:76b2613906dad1e2eb415e3d6d4f84b8d01ea90e095826bc3a333ef6597fc5d6

Pith citing papers

No inbound Pith citation observations are available.