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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=sha256:3a8903c63744bf508e6bb8435176796879c75f4b92818e4295d9a8e8672d449c

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:c48956d07f8cf53d71e8e34571bdd953005945fed3a750a7ec227ba840414317

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=sha256:12b036d98e4b9cdf2c8ac8e38bb772c281a01a02e62443026847500bd2be3f30

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=sha256:42f0e1cc733a22483ad5fd14c0aad054bd24eba47e87f0b396a7fb8ef2e3737c

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=sha256:99df59c0cd18b7b21cca5e7657a5ad047259d319df4f478c5ab62e6f47efac58

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=sha256:47cebfbea671e73434ed5378aa65d1b644b0bcc95d0c297de75743704f979f09

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=sha256:7dc295af2c1ea5d9077552aa4b581921edda331cbfc96e50ecc711888e24f1c7

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=sha256:8dc8e86aa5e77ed8b97dc7084ccea54030ef84fce1a0ebb8572946a986914643

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=sha256:3ae4cf48a9e712f3d62777e489aadf725079ca94bac76288d2a1d8477dc4bf25

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=sha256:8b9c6185b2606f14da0f1d7127303aa19ba03ebe7b61a030a3b128c460d79e52

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=sha256:44db3e3d782825473657de6417ab0046afaf02f1b577b7c2752cb5ae9f47725d

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:cfd66687cd90fcfeef95ba190684dd2ffdfffcdfe334a9c54f875cdabfd1d458

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=sha256:98bb947bb27742ae6f0ef507872d825359f7e44a686dfcfb79e0a0a1182cf9e4

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=sha256:80ddeb47b5fd83420c7fdbf161f1ca115361c2f71244618954d3438326919b06

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
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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:b7cecb4597c3fed90fe1166c09497353f3fd4f02690377714f7d47d521dd537b

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=sha256:68f16cac0b98d915bcb7592f3df05188a979bb1c31310292366ca9372f885ddf

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:fa33da7cd7dab75db28f9fbe1b1d526b563a4c18ffa59da1f0d8b789d491c690

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:dfb497f33caa20caea4c1fc31e4f852fd561ca519094feee3c3f6da5e5311362

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=sha256:2a74eec83a871f4d4af3f25e15498ce026ac6eddaf92d965ebb06b656d9ff339

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
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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=sha256:6b587f8919f8f0bd3063b3db2ebb810e708022dbe5683284646855c165035078

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
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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=sha256:601083d0285265b4da80f281c06cf8aa3f85e6585fac5486efc02a7677ef92b6

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
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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:f79b621a89c3f763b6d08fafd21899677f4c7d5e1e89c96add51a8984bc8252e

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

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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=sha256:2f43a6b246547a743809a1a7c95250d8e94f314d898517d756de6509daa3de43

Pith citing papers

No inbound Pith citation observations are available.