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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 17 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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T05:43:45.517648Z digest=sha256:b06ad87e77a216df43b2df00a4191eec454396e6de902ac96647df9f08c44486

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:45.600857Z digest=sha256:5ea519cc6faebaf9667a48294246a1452ab80571df1aa11bf44cf217e69dc8d8

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=sha256:21039dd0347bcef806e26be5b04b42771575a644b321d0caf2d2677c48dcd257

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T05:43:45.893225Z digest=sha256:0b3d7c51a4e9e182f35de902b04f00b6d3db034984f06fc06cd47b3d99a95bc5

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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no resolver link, observed 2026-08-07T05:43:46.077389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:46.077389Z digest=sha256:816578bf29e4208930102fc79475cb0b50ebacf47dfa5fb9dde8a39d02781448

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:a10ddf62f6841f75837672dc701f713e9070153e34b181cbc8fe186e6b987721

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:ac1c753c2c4734bd642e42d9592cc535317317a687ec9053da9f1b58c30f279b

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=sha256:22495a3ca186da80c6ced50908e31205b8cd0cd3000dfd67a6cf08434fae1124

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:ea782da091b74cdca5c05967d6904f354e75375225299ecffa5ca393c9d859a3

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:a82e1bfa15611452eaee3c5cec6cc724171e45b8cb69280946b4bf69e3a14798

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=sha256:4bc8b54eb771eac637943c580fe3197bceddc6c9148b72eb2ecbc56865b95813

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:a8014304e8f0c178b9dc83e4b04dedc7f7c6320b33c5f700bd57de2bd3c140df

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:c13c492609b98b64e219a32bea474d9c803fcd400d34a9eaa63754d1af7efe3f

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=sha256:03b303a0f81ee68933cf96cd5fed04350f76b7d7e505f684f57c2c00c1c8ab02

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:d0c65e33ba0fed6c588efa2ac2762a450a811b5ba8f17d84787e7df40c1bc494

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=sha256:076ed6fbb53d7a3d951b2011cd9c1ef9c30731f1545d8ca0ba089b77e7c43ecc

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:cd8dc2d19554a6a82417a2435b9d4ed6ddc3debaff28896812e8366d15c3df97

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:b396867564c2f5437a936e8de2bd2538ae71a0d9e054584c8c02fce19c6f2a17

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=sha256:846359a633f6e77ca97997845fbcf79d3c1373da63a26ddaf2ca90b301dc5c67

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=sha256:2d2bb78ff148dd26d6d4107b95bb9e85484e8789f62239b5e86c5f6cd55e8e4f

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=sha256:92f9ad7599f70e4d748e65e1e17cbdb34a16f4787207c35a05f535b446eea1d6

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:b0424e8c5a5d7874611b4c8ca614a49338a5b56969cd0be613419bfeb8d1a648

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=sha256:104e664e95105fae1c17b98561fcc7cf2e215d71dcd528b2a96ec28310a7b707

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=sha256:0ed203bbac1751082dedfc78e07a1733f1508bd4b6d243f3b262ecc6f0b287bb

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=sha256:13f8557c4258efb8d43d8623c1101bb93ec7df1a396b26f8147410db1f83e13f

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T05:43:49.157004Z digest=sha256:a439c6f3789982d7f111a603a9969f955697587dfb2a052c9f9c3212f34131b8

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=sha256:7b7d07022c366a80c274047776e3cf811f3794f8486c5a3a5fd6f0be39dfd703

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=sha256:18a30634899da8f8227dd0d56a74aaf843f0accd3b1e7861d8755c16e21af11b

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:f79a88c0f63495594fa370bc88b266d0810cd1b14ca9e1232d841c020c154c99

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:eca78a8002ff5ca5c007806f4448c38289a5bce2fe918e02add4d1c19d843b83

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:f6c30ad176ac9d849bb3f96090afc4059ab047c5e86ac59637947844decb7274

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T05:43:50.100727Z digest=sha256:915dc0171316c208cb0b7a6fabb90454114d28e85aedb79d06ca31063f2f2456

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-07T05:43:50.262356Z digest=sha256:a1aaeba0e5def3706fe1f7a3ad5253d367e877e78116fe95b8dceaf4cec21cff

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=sha256:2f68516f338a25515f03926449ec48e632df4e2b7296e3fe1c59effc3b9cac82

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=sha256:9434af020bb0decdd4560ba47d1c82084629892b398bb85da0cbcd44fdea746f

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:e04f02298843c52c6f1f5ac5e9690ebb2a09a383540fed4d8042e3dfd0e9fe59

Pith citing papers

No inbound Pith citation observations are available.