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Paper Citation Record · LEDGER

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2506.07245.

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

pith.paper-citation-record.v1
2506.07245 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:43:50.670099Z

measured 36 of 36 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 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

36 of 36 outbound references displayed

  • verified exact3
  • verified fuzzy1
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb46711c-a81c-4523-941f-6b64201dc113 · outbound

This paper cites SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL

Reference 1

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local_arxiv, observed 2026-08-07T05:43:52.598812Z

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.

source=arxiv_source observed=2026-08-07T05:43:45.517648Z digest=sha256:78635d69afe568c255e222024a569752f18432d715177a40cd5664bec698b6c9

Observation 2147b60e-64c0-4d16-842e-3ba62bb5a94f · outbound

This paper cites LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations

Reference 2

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source=arxiv_source observed=2026-08-07T05:43:45.600857Z digest=sha256:dc3a6aa289982f733ed4f04bc769c79690625428a19c81461d3694e3719de568

Observation e09d43cc-907d-48a4-add6-bf6d58e59244 · outbound

This paper cites Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Models

Reference 3

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source=arxiv_source observed=2026-08-07T05:43:45.716773Z digest=sha256:35c2c648ce80429c2a3d37beadb1ca6c32fadb72388f6825397bdb615bcd24d2

Observation a9baf11e-862d-422a-9ce5-2968008e9b91 · outbound

This paper cites RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases

Reference 4

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verified exact
local_arxiv, observed 2026-08-07T05:43:52.214881Z

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.

source=arxiv_source observed=2026-08-07T05:43:45.893225Z digest=sha256:ba33aef5eb2b810fe8584fdc597cde891a93aa8bcae92e58bc015f8f9191b32e

Observation fb79ec98-ce90-4fcb-ac0d-ab8696f6a7f6 · outbound

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

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:46.077389Z digest=sha256:fd5be40746bdbe0228eaa51cf6a65e2e4426e24df126ac27575dc70d75748a84

Observation 3123b1a7-d225-40a4-92f3-e8e92609cfd7 · outbound

This paper cites A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL

Reference 6

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source=arxiv_source observed=2026-08-07T05:43:46.260991Z digest=sha256:9a612717332a8e3c39763c41af1992c497a7bda50ea0d2b3c81d15616c689119

Observation f1f2f424-aeba-40a7-8b0c-d9b209452c1c · outbound

This paper cites Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation

Reference 7

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source=arxiv_source observed=2026-08-07T05:43:46.422364Z digest=sha256:4f82cef46c04b8c8724a480996e2218a33d3341948ebbf5efcd2b0b735c82804

Observation 6a7af6fb-cf5b-4c9c-aecf-29fdd2fb61f0 · outbound

This paper cites Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM

Reference 8

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source=arxiv_source observed=2026-08-07T05:43:46.544233Z digest=sha256:28f80936010b0219cd6f095ae63d1c537b196979752351d776ea719dbd46b403

Observation 70812fef-8bd9-4196-b7ec-ce6d129d8e22 · outbound

This paper cites Improving Text-to-SQL with Schema Dependency Learning.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Improving Text-to-SQL with Schema Dependency Learning

Reference 9

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source=arxiv_source observed=2026-08-07T05:43:46.696618Z digest=sha256:2179a3b45eeb341c503b0e81b3172c625a78fca461ae4f0d0a3611a1f46033d8

Observation bdf22a74-0798-4ba7-aaf4-e5c63cbbb03a · outbound

This paper cites A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization

Reference 10

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source=arxiv_source observed=2026-08-07T05:43:46.801794Z digest=sha256:400cb213389d22873aff7d35bac5e3647d0dbc851072b5e731820dc206e24571

Observation 0c18eb8e-a45e-4295-8454-4fdc4edecebc · outbound

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

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation

Reference 11

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source=arxiv_source observed=2026-08-07T05:43:46.984628Z digest=sha256:71f75b57a92b11dc67331c5c9812baa73122a32fc117ecd790bf2957696f3f82

Observation a4187268-02c4-45bb-9d82-da1cc7482c43 · outbound

This paper cites Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Reference 12

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source=arxiv_source observed=2026-08-07T05:43:47.133873Z digest=sha256:a130f0a8bb3d356783f70ac384077516155a0bd69e59387c9806845d6964c9b0

Observation 983ad3fe-3921-476b-9c1a-760c3648f354 · outbound

This paper cites CodeS: Towards Building Open-source Language Models for Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes CodeS: Towards Building Open-source Language Models for Text-to-SQL

Reference 13

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source=arxiv_source observed=2026-08-07T05:43:47.261026Z digest=sha256:00a8b63f117271247b9406e8f8909a73d720b4bfd1c89e19b91660cd5eb99f58

Observation 949702dd-fab4-4141-89de-707dcdaae9f6 · outbound

This paper cites Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs

Reference 14

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source=arxiv_source observed=2026-08-07T05:43:47.425068Z digest=sha256:74031edf81f4f77b86fa65409a20454b01c96bc47cc36dcceeb0195482c4b9e0

Observation 6de1c4c0-88ab-44b9-b94d-bbf5f4460811 · outbound

This paper cites Divide and Prompt: Chain of Thought Prompting for Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Divide and Prompt: Chain of Thought Prompting for Text-to-SQL

Reference 15

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source=arxiv_source observed=2026-08-07T05:43:47.530614Z digest=sha256:64c2d3a5f9fef292c1128ad1692e0c7c6d4058ced403f40aa63a60d5c20d2436

Observation 03d05ef6-520f-4612-9a92-166508a95908 · outbound

This paper cites GPT-4o System Card.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes GPT-4o System Card

Reference 16

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source=arxiv_source observed=2026-08-07T05:43:47.711471Z digest=sha256:98eb092841285dd5b695beeae1a60c2ce483f2eadb5b6794891f2d3bb44bb78a

Observation 6b1a1cd7-98be-4ba8-b8a8-5ad49a8b17d0 · outbound

This paper cites CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL

Reference 17

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source=arxiv_source observed=2026-08-07T05:43:47.844013Z digest=sha256:2eb930fbcebc2f0c9d67001277cbd6df710ab69db2e3a266be9a2bbaf577199f

Observation 8883a1b2-8dad-4e82-95f2-764044e9d279 · outbound

This paper cites DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction

Reference 18

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source=arxiv_source observed=2026-08-07T05:43:48.023831Z digest=sha256:99fa58ee6a2ff4fe54a21795d295137a2e912a430f8ca803f57d6b5f8000a896

Observation 4d6d5eb6-ddc9-4405-9e83-b930558823ca · outbound

This paper cites DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models

Reference 19

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source=arxiv_source observed=2026-08-07T05:43:48.112832Z digest=sha256:f6293ccc6f0fa67d7e2693808d1a011686bd5edfff14da7228fcf23273c99ab5

Observation 3fee2182-aad9-4283-a62b-cca229ba034a · outbound

This paper cites SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging

Reference 20

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source=arxiv_source observed=2026-08-07T05:43:48.271709Z digest=sha256:e72b4f73bd405a8607424ddfa556227907e78e7c4b42cc1efc8a04ab5d75ea46

Observation c73f30ac-9cb6-4c0b-8076-737b163ac0eb · outbound

This paper cites Evaluating the Text-to-SQL Capabilities of Large Language Models.

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

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source=arxiv_source observed=2026-08-07T05:43:48.389620Z digest=sha256:7e756b4bc8bcacf2949b2dcaa71aa9b5dbdfca85169ef461643e852cab520f28

Observation f2f095c1-602f-4359-8c5b-cee405fecc16 · outbound

This paper cites an unresolved cited work.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Unresolved cited work

Reference 22

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source=arxiv_source observed=2026-08-07T05:43:48.555082Z digest=sha256:f355578d4f786368761620b56501d32300e6092fd28778136b640945c6f79ca1

Observation a4e84391-0c72-4bc6-8269-540fb7a50a4e · outbound

This paper cites SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended).

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)

Reference 23

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source=arxiv_source observed=2026-08-07T05:43:48.666087Z digest=sha256:5f49c803ebbe4f7c95e6f9da3c6d5f7513f260837536904e9f5cb74d4b52c83a

Observation d7b991e0-06fe-449a-b10c-40821a66caad · outbound

This paper cites Exploring Chain-of-Thought Style Prompting for Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Exploring Chain-of-Thought Style Prompting for Text-to-SQL

Reference 24

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source=arxiv_source observed=2026-08-07T05:43:48.836906Z digest=sha256:13c1ddf502e7ba09f500deb1e423078541e2409021701a747a4d9f7350ea5822

Observation 70c46b0d-7a22-4b98-a52a-294fe5c1c578 · outbound

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

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 25

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source=arxiv_source observed=2026-08-07T05:43:49.001095Z digest=sha256:5f9ca87fe6bf43b63abe074cd4f1b79f2a99c511247cd0879e731c4f7ad824c6

Observation 446da94a-2a78-44b3-8601-04535ebbe310 · outbound

This paper cites an unresolved cited work.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Unresolved cited work

Reference 26

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raw_fallback, observed 2026-08-07T05:43:53.294678Z

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.

source=arxiv_source observed=2026-08-07T05:43:49.157004Z digest=sha256:55b638516f2297d618bce52c111a5fb770a5a3b4e98cba5304da08b8410dc41d

Observation dd239da5-060d-4948-8b34-e9b970570abd · outbound

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

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Reference 27

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source=arxiv_source observed=2026-08-07T05:43:49.320769Z digest=sha256:0f9590948e775211143f47f99cafd60b3b8426d824f508686beb803016df3a97

Observation 72624989-fb8c-4200-9d9e-d21ca01b48f4 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 28

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source=arxiv_source observed=2026-08-07T05:43:49.445120Z digest=sha256:166047d9af0b896fc3dea165063a819d1114e46451891c8db65c2a04e709cee0

Observation 98d67c5e-3550-4ee1-a5cf-6b7af737efb7 · outbound

This paper cites MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL

Reference 29

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source=arxiv_source observed=2026-08-07T05:43:49.622152Z digest=sha256:835f24df287c9cbe6eb45a8dac888735c6b32ae62046b2203e062ddcd8315cbb

Observation b7348c48-7ebd-4ad0-ac8a-d82484970bd1 · outbound

This paper cites SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

Reference 30

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source=arxiv_source observed=2026-08-07T05:43:49.811096Z digest=sha256:9490d5d8a86287125df80fc245da99e7548293bdb2c63bf392c64111c24695f6

Observation 988110fe-a8ca-43ab-9aae-d3b1d1c02cf4 · outbound

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

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 31

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source=arxiv_source observed=2026-08-07T05:43:49.960539Z digest=sha256:5188c3ca8889e24716b0c2fa3cdf03830f82e69ff6ad2e6e871765c5b4e89d3c

Observation 6ab2f102-b8a2-4f3d-a806-43aceba7a236 · outbound

This paper cites Zelle and Raymond J.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes Zelle and Raymond J

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T05:43:52.950758Z

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.

source=arxiv_source observed=2026-08-07T05:43:50.100727Z digest=sha256:c599ed899437b486647317a12f2a02d5a2f76946479a72a1c2b50e73f43b0f14

Observation 954a10c7-0c21-48eb-8136-0790d67d9ab1 · outbound

This paper cites CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editions.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editions

Reference 33

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local_arxiv, observed 2026-08-07T05:43:51.034351Z

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.

source=arxiv_source observed=2026-08-07T05:43:50.262356Z digest=sha256:4ef95e9d488eb479d02d52858cde14c1f6ccc130ab18b4c89f247d65f88a5590

Observation b7fd1806-0e7f-4412-9a69-0bf63414d52a · outbound

This paper cites SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:50.385334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:50.385334Z digest=sha256:6e8476c8e849fb62b1b93295effce4bb8d6d4ee438e1db2a848976d5c83edf04

Observation d056311a-65da-4886-b060-253df6e0e37c · outbound

This paper cites online" 'onlinestring :=.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes online" 'onlinestring :=

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:50.530030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:50.530030Z digest=sha256:d3a710f09ce9f8d6224922dcc6f76751df4171607988b0321cc14e57e05ae721

Observation de8e5b4b-9ca7-4cd7-82ce-0fc08f5c8ce7 · outbound

This paper cites write newline.

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes write newline

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T05:43:50.670099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:50.670099Z digest=sha256:26f3b8ebfbf241df52e8d42e6d4185c94de7889adca85dd94cd787807bfb7bcc

Pith citing papers

No inbound Pith citation observations are available.