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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 7 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 2026-08-07T06:34:17.273281+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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verified exact
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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T05:43:45.517648Z digest=sha256:f32c2328cdaf4a75228703d72e2e576f3d1b860942540231a62053672a295e0e

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:45.600857Z digest=sha256:d3cc517280c16b942b3ae25f407c1b6b6bc576c806ef4e3ef1679e300dff91f0

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=sha256:5cb422913f9ea40dfe768658906f3e9c1a06a04120689ad96940cf79f593ef9c

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T05:43:45.893225Z digest=sha256:580a6fabddbdf8279b3b0b7d41457b71af21b752d715f01d65871b5c66767e0e

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:dadab816238aea24d4cebb38437476409c1f20c2f2af22f55178353734edf473

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:f0a01cf969b6d5204278b95e10df362bcb73d9701c76cac658d00fca05ce00e9

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:d82c07a326aa23c589d75d8656fd09c4d745f33419a1e291fb6978fe59ac6fdc

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:46.544233Z digest=sha256:717dbce68d31cac84a979386585afa4e2b2f01e7eee755d36f241bbb4eb1956b

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:db2a677fb539d49d81d9a9e6956aa74e1d686a228249f7e8260a1a034f7e9d53

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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no resolver link, observed 2026-08-07T05:43:46.801794Z

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source=arxiv_source observed=2026-08-07T05:43:46.801794Z digest=sha256:e4d6f439ef50e6687a767eae217c55ca43b2445284fa01c048e029710cb1cfaa

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:a1b2720c3466dd5dd2868013292c274e256135b72360e27ded8653a4b1f64048

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:47.133873Z digest=sha256:2bb96332ae836183c3f164a946d781b1a3385334e69fbe9bf81a612f5bfcfb95

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=sha256:515ced1db4ae8ea4d7f74af0b7a4711ef8eab1acf19af69ddd39a3aba7aefec4

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:d568092064c25aa808f7c647cc4238de0f15dbe420575cc096e0fa28fe704cec

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:a1d928d59051ff9cedb5ea37a34d08fee7be413910db8db771ce66f37745c548

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=sha256:6cc82be7133591ebe2a3b624e56097c7a3c17c16dc1196fd4caf89ec46c4e6c8

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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no resolver link, observed 2026-08-07T05:43:47.844013Z

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source=arxiv_source observed=2026-08-07T05:43:47.844013Z digest=sha256:9486273f139ab7cfdd467fc806fe6f8345613000cc9f10f6c620c862902dbf5e

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:ffb3b7dfbdd3d75ef1df05361772f4de0ee59121b3affa4a5f619246012659f8

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:dcd7e5efb4fcb6b707340a928b080598030fee51e20c72281aafd593b84e2b72

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:cea97e7a9e203434d5a2f85c3fc1ceb7c11e0c88ea2b84944ac48814e6356bc0

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=sha256:1260d5398be2c6cbf6d9dd897fdbf3c51083052d66dda4477389cb7949b2f78e

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:dd561da54abe60888d13128105c83d1bf30e73b58d8dc440e0a77e43352332fc

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=sha256:549437645c7df0e9e205126c1ade74f4c6487138cc93707ed15ea09005551820

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=sha256:4a134ccacba771faed442b6fb6c42a4c9029b8da966801b94d3f77d8a4b2c8d3

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:bd8736e46d439312eccc513aad88a3d1a09feebada345475c8ea4edba3c0cb8d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T05:43:49.157004Z digest=sha256:cc60e268a387a99260c650d7837dd1bd837d60ce8ff5db42dcb87d92c4c48734

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:43:49.320769Z digest=sha256:ef9474c86e834dc4745375e6fdbd0c8a92117b2ac09c8aa7017bf1a67135ea4f

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=sha256:771bc06c23ea7f156bb851041fafa9d160bc810d9f9880e925dff037b3d89444

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:c7a5d3234871c263c0ffc81598c7ae9ac99bfa806cb685418a9886ae9c48f17e

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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no resolver link, observed 2026-08-07T05:43:49.811096Z

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source=arxiv_source observed=2026-08-07T05:43:49.811096Z digest=sha256:e2f0158b4cdd1db95ae7480ca10807ca1f8fd8e1d9cabfb201b32b61f995c281

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:e45c7973fa1dfbe6f24d5c6b67e77b503061264955cc510ea3652d49315c3571

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T05:43:50.100727Z digest=sha256:de39e5f0c9336726e2aff4987a3a4317808ae5b87da432126f8d4e4f25ffc548

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T05:43:50.262356Z digest=sha256:fb4bbd46a3a78a8fa9a2a8fa7865dda6df6c17f21bbfb7016e581e598b98dc53

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:d895622f782e318b56bc309f41ecc69e47ec12c245af59a7e5eaf8de489bcd60

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=sha256:7c857b66748d932d1040c60deec1f8aae10269d98857dcef03930a44c995ed64

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=sha256:40d56b8ceedbcd54626453387b0d8a9f578820c7b86731858fe6d73f52db393e

Pith citing papers

No inbound Pith citation observations are available.