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Paper Citation Record · LEDGER

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL

As of 18 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 4 inbound Pith citation observations for arXiv:2505.12768.

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

pith.paper-citation-record.v1
2505.12768 v2

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:32:41.075935Z

measured 73 of 73 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T05:40:55.951093Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:37:09.671815Z

Reference resolution

69 of 69 outbound references displayed

  • verified exact0
  • verified fuzzy21
  • unresolved46
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da719f27-1cdd-429c-b9cc-429dd498b96e · outbound

This paper cites Chi, Quoc V.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Chi, Quoc V

Reference 1

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raw_fallback, observed 2026-08-15T20:32:42.366808Z

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=2026-08-15T20:32:40.758076Z digest=sha256:5fd8645b7a3ff33588800c4ca350191616d4a6005beb4e724590cd911e4ab41a

Observation b09d775a-c53e-40d7-afd2-4c1fca39f8e4 · outbound

This paper cites Recent advances in text-to-sql: A survey of what we have and what we expect.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Recent advances in text-to-sql: A survey of what we have and what we expect

Reference 2

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raw_fallback, observed 2026-08-15T20:32:42.353366Z

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=2026-08-15T20:32:40.763185Z digest=sha256:575c2dc3b2e69ad7d7badd67cd7c6ecffc95d99ae57fae8db2cb324811f67435

Observation 510b49d7-7a6a-468e-9562-b2e13d8358a3 · outbound

This paper cites A survey on deep learning approaches for text-to- sql.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL A survey on deep learning approaches for text-to- sql

Reference 3

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source=pdf_text observed=2026-08-15T20:32:40.767806Z digest=sha256:bbdaaeb28d25af8279e0938f567b88d6ca4d1719db7f4bd44a124fb34c2e646f

Observation d634264d-cc82-4cbd-93dd-303ed2b11f46 · outbound

This paper cites Chan, Raymond Chi-Wing Wong, and Haiqin Yang.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Chan, Raymond Chi-Wing Wong, and Haiqin Yang

Reference 5

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raw_fallback, observed 2026-08-15T20:32:42.339577Z

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=2026-08-15T20:32:40.777219Z digest=sha256:051d4d76d8eb7c88c74fe3a020a4ffe27af4ba01d713b75df0110375989d63ac

Observation bcc37a19-dcb5-4b0b-bc3f-be237481534e · outbound

This paper cites A survey of nl2sql with large language models: Where are we, and where are we going? CoRR, abs/2408.05109, 2024.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL A survey of nl2sql with large language models: Where are we, and where are we going? CoRR, abs/2408.05109, 2024

Reference 6

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source=pdf_text observed=2026-08-15T20:32:40.781716Z digest=sha256:56f55eb89a0412bea9aa64544c38193e6dc9b4f94d8ac92a969fa5ca685501e4

Observation 3ebf4acd-ea64-470b-be74-14f1483559ad · outbound

This paper cites Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Alpha-SQL: Zero-Shot Text-to-SQL using Monte Carlo Tree Search

Reference 7

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source=pdf_text observed=2026-08-15T20:32:40.786318Z digest=sha256:17a5634c1a7a25a569303cb4dfdc912ecb229440f85f612fa3af398f99d59dad

Observation fd850957-46d3-4d19-bf7c-032adeb94e81 · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 8

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source=pdf_text observed=2026-08-15T20:32:40.791083Z digest=sha256:19e23c774ebdc724ba0cb44557cf3b4575fdaa600d32f2564c3fdd312ee13393

Observation f67849e9-5864-47d4-896c-042adb59623a · outbound

This paper cites RAT-SQL: relation-aware schema encoding and linking for text-to-sql parsers.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL RAT-SQL: relation-aware schema encoding and linking for text-to-sql parsers

Reference 9

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source=pdf_text observed=2026-08-15T20:32:40.795563Z digest=sha256:d4f56e7c962009196105c36c19c60dc2b1d6097f49fd8a2304a99209ba108ddb

Observation b29921a4-5cb4-44bb-afe4-d708e17fdeb8 · outbound

This paper cites Finsql: Model-agnostic llms-based text-to-sql framework for financial analysis.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Finsql: Model-agnostic llms-based text-to-sql framework for financial analysis

Reference 10

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source=pdf_text observed=2026-08-15T20:32:40.799593Z digest=sha256:b3e251f80d51899393d0d0a4f766e6c8b938f87f691b45ab287ef15f4906f74a

Observation 266426ec-6b66-4241-9ea5-05419bb62d42 · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL

Reference 11

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source=pdf_text observed=2026-08-15T20:32:40.803718Z digest=sha256:760d9584f93f07609ab97bda3cadc6ac712864f4b5586e9d87fd3188728652d1

Observation 527226f7-e02c-43e6-9128-3ba056cadb2f · outbound

This paper cites The dawn of natural language to SQL: are we fully ready? [experiment, analysis \u0026 benchmark ].

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL The dawn of natural language to SQL: are we fully ready? [experiment, analysis \u0026 benchmark ]

Reference 12

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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=2026-08-15T20:32:40.808127Z digest=sha256:eee423e58e19fb3b20806bf236e3fd3b174ba09c6b7025c3832ab850532c68ba

Observation 7bb2879d-cdbf-4790-a579-ad0b4edbec7c · outbound

This paper cites Sean Wang.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Sean Wang

Reference 13

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raw_fallback, observed 2026-08-15T20:32:42.310654Z

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=2026-08-15T20:32:40.812276Z digest=sha256:834e927ad58cbd225dc90b8d20ff07d093e15025036fa831f8b3752647ed4b41

Observation 970d675c-26a1-4ce4-b162-b90f15e02468 · outbound

This paper cites DIN-SQL: decomposed in-context learning of text- to-sql with self-correction.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL DIN-SQL: decomposed in-context learning of text- to-sql with self-correction

Reference 14

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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=2026-08-15T20:32:40.816322Z digest=sha256:746bae07a042298d6171dee42365d4c51f5c5194429ef6d8775491cadd19260e

Observation 7a8f18ec-a3c1-4c56-991a-06bb772f7845 · outbound

This paper cites Navigate through enigmatic labyrinth A survey of chain of thought reasoning: Advances, frontiers and future.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Navigate through enigmatic labyrinth A survey of chain of thought reasoning: Advances, frontiers and future

Reference 15

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raw_fallback, observed 2026-08-15T20:32:42.280928Z

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=2026-08-15T20:32:40.820438Z digest=sha256:0a29aa670936d8b69a23f0365066e92e484eed2543dde95032f21cb11a210b99

Observation 3773cba8-ca70-487f-9e89-ce53bfcebc07 · outbound

This paper cites ACT-SQL: in-context learning for text-to-sql with automatically-generated chain-of-thought.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ACT-SQL: in-context learning for text-to-sql with automatically-generated chain-of-thought

Reference 16

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raw_fallback, observed 2026-08-15T20:32:42.267198Z

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=2026-08-15T20:32:40.824463Z digest=sha256:b5159cfc3f78b72f14eaf01b79057327b79b808c5798425a2b15c29d1df54fdb

Observation f5ced2c8-c2ae-41ea-9ac0-8e6bbf2c0089 · outbound

This paper cites ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback

Reference 17

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source=pdf_text observed=2026-08-15T20:32:40.828556Z digest=sha256:7ed1acc4bdc876140dc93912e784e8431419d34f64f46e67fab01c2b67bdb67d

Observation 9bcc4b44-8921-4927-b637-0f05e65ca45b · outbound

This paper cites Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes

Reference 18

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source=pdf_text observed=2026-08-15T20:32:40.832884Z digest=sha256:706cba3c37d5dd0b47d346b59066b4a5e890025e74f16df80de3be9b8d43db88

Observation d6458ee6-9b67-4537-aaa4-6dd47b53c5a8 · outbound

This paper cites Nl2sql-bugs: A benchmark for detecting semantic errors in NL2SQL translation.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Nl2sql-bugs: A benchmark for detecting semantic errors in NL2SQL translation

Reference 20

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source=pdf_text observed=2026-08-15T20:32:40.841546Z digest=sha256:4143ef8fe56ac9aa9d52d5a054c24917c3510c804b48362add6da80dad5b6782

Observation cb63952e-a1d2-4e01-b9c8-e3c4967b164a · outbound

This paper cites SQLCritic: Correcting Text-to-SQL Generation via Clause-wise Critic.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL SQLCritic: Correcting Text-to-SQL Generation via Clause-wise Critic

Reference 21

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source=pdf_text observed=2026-08-15T20:32:40.845298Z digest=sha256:d35b539fed104e3bab198a1b05a94c02a24fb20dac96cd5adc6785f030df3d02

Observation 64f836fb-d22d-45f6-bdf9-0b5e5a8f3386 · outbound

This paper cites A study of in-context-learning-based text-to-sql errors.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL A study of in-context-learning-based text-to-sql errors

Reference 22

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source=pdf_text observed=2026-08-15T20:32:40.849543Z digest=sha256:0016912369d679ab3cae9a102d1c046fb20a280b4fc953ffe64beb244cd772b2

Observation d11a1933-5c39-4b86-b771-c92ae3b12bd1 · outbound

This paper cites Llms cannot find reasoning errors, but can correct them given the error location.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Llms cannot find reasoning errors, but can correct them given the error location

Reference 23

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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=2026-08-15T20:32:40.853548Z digest=sha256:0a21be2ae5614bd7efcceb8b7712bccb734eeee4d23b37a34a34d5d53b6238cf

Observation d1583c34-9ed0-423c-b235-2a941c06a608 · outbound

This paper cites Boosting text-to-sql through multi-grained error identification.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Boosting text-to-sql through multi-grained error identification

Reference 24

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

source=pdf_text observed=2026-08-15T20:32:40.858014Z digest=sha256:ce7efd122b87fd2c3c559326c717d7363d0ca1af63f1123ec4b088c8e9e72941

Observation d3c8c5a4-e731-4320-88c8-64cd4efa0882 · outbound

This paper cites The Dawn of Natural Language to SQL: Are We Fully Ready?.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL The Dawn of Natural Language to SQL: Are We Fully Ready?

Reference 25

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source=pdf_text observed=2026-08-15T20:32:40.862090Z digest=sha256:cb929002bf16882305d95858d85bd571939cdb379741173fa82a418f8ddc076b

Observation e64b0825-afec-4a3f-97fc-e3ff6089c0c0 · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL

Reference 26

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source=pdf_text observed=2026-08-15T20:32:40.866513Z digest=sha256:0aba1dce9de0f20dfe54d2a74f04b1c2d517f4d15825fbb289e2a8d3dda914fe

Observation 67cdcf59-2d2a-4a2a-b2dd-8ab1b815b350 · outbound

This paper cites SQL-o1: A Self-Reward Heuristic Dynamic Search Method for Text-to-SQL.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL SQL-o1: A Self-Reward Heuristic Dynamic Search Method for Text-to-SQL

Reference 27

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source=pdf_text observed=2026-08-15T20:32:40.872304Z digest=sha256:de3c8e5034b554aeca3c4f68ad89819b51d7124c6ece91f117aceda0639bdc85

Observation 23e5a09f-3f19-44d8-80d4-e09ea8f15bf3 · outbound

This paper cites EllieSQL: Cost-Efficient Text-to-SQL with Complexity-Aware Routing.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL EllieSQL: Cost-Efficient Text-to-SQL with Complexity-Aware Routing

Reference 28

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source=pdf_text observed=2026-08-15T20:32:40.877267Z digest=sha256:25ceea85cd3f7069e197d401a594f4c432d41384a4c72938c35cbf9260a5a428

Observation 12b8559f-9d54-4eae-8d5d-c2e564597ee6 · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Reference 29

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source=pdf_text observed=2026-08-15T20:32:40.882379Z digest=sha256:af174d487b2befd2d6062e7aabbf2ee021cf1fd7d8790222c2ee139aa2301643

Observation 8d99767f-8a70-47e7-af7b-7452f56e24c9 · outbound

This paper cites ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQL

Reference 30

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source=pdf_text observed=2026-08-15T20:32:40.889809Z digest=sha256:7f479eab1f6b5ab0813ddb0a3837c03278f7d4ef7ee4ad69ea83b9b867883f1f

Observation 4fed8399-1824-429d-a951-0eb3536e05b3 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 31

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source=pdf_text observed=2026-08-15T20:32:40.894612Z digest=sha256:40190a61acad25a5957cdb1604e2ea422add8a1c8d9dacd21ca4dd7080577ae7

Observation 3a5672c3-48e9-4e67-8384-103023e7b32b · outbound

This paper cites Manning, Stefano Ermon, and Chelsea Finn.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Manning, Stefano Ermon, and Chelsea Finn

Reference 32

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source=pdf_text observed=2026-08-15T20:32:40.899062Z digest=sha256:67650ceae39caaa8aa44f116abde4b3c3f567f36c9f4706a8cb1b595784c46ff

Observation 1d6539d3-0d86-4969-bf13-e1f879dad3a0 · outbound

This paper cites Mag-sql: Multi-agent generative approach with soft schema linking and iterative sub-sql refinement for text-to-sql, 2024.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Mag-sql: Multi-agent generative approach with soft schema linking and iterative sub-sql refinement for text-to-sql, 2024

Reference 33

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raw_fallback, observed 2026-08-15T20:32:42.208108Z

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=2026-08-15T20:32:40.903160Z digest=sha256:fb9ec5e7ff6cd02658e8952b444cbddbc66449bc25d9baae5d654e5e0531ccc2

Observation a0203573-7a83-494d-9a13-64cd197cde6c · outbound

This paper cites Text-to-sql empowered by large language models: A benchmark evaluation.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Text-to-sql empowered by large language models: A benchmark evaluation

Reference 34

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raw_fallback, observed 2026-08-15T20:32:42.194391Z

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=2026-08-15T20:32:40.907626Z digest=sha256:80105c69a86285b780a1c1907be803e51d00e7087648f5dae530656930c20d9e

Observation eef49cfa-4bdd-4e05-bd40-181b19602515 · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL C3: Zero-shot Text-to-SQL with ChatGPT

Reference 35

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source=pdf_text observed=2026-08-15T20:32:40.916498Z digest=sha256:a1d0aa7ae7d011762db7bb4f19a161ae6bfe061917a55ce0de9d26a73543eaaf

Observation de5f25b5-f2e7-4786-ac14-895b7ec855dc · outbound

This paper cites Codes: Towards building open-source language models for text-to-sql.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Codes: Towards building open-source language models for text-to-sql

Reference 36

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source=pdf_text observed=2026-08-15T20:32:40.921565Z digest=sha256:5b3739a9b07efc8054495e13b8f880604da81c3c25d80a9733b44ea8b03ee98f

Observation f8612cbd-2333-45d2-bb13-05f94ba32fde · outbound

This paper cites RESDSQL: decoupling schema linking and skeleton parsing for text-to-sql.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL RESDSQL: decoupling schema linking and skeleton parsing for text-to-sql

Reference 37

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source=pdf_text observed=2026-08-15T20:32:40.926014Z digest=sha256:6f697ec65d83681fead8b8b482856fed5f1706924009207944595f32c0e457e7

Observation fced2de5-4fe6-4003-b1ad-947409c26cf2 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 38

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source=pdf_text observed=2026-08-15T20:32:40.930480Z digest=sha256:a416637f8d5dcecece11bd9e17c2b7b3d7715914b684cffa26c1c3a1eb348bd7

Observation 26810719-4d86-4fc9-a98f-5da39ca609dd · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 39

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source=pdf_text observed=2026-08-15T20:32:40.934642Z digest=sha256:7ecc455964ee69beb36acb0d25227e4a2288948126f131121c7b0369dd2243ce

Observation c06ff157-1865-40c6-9d7d-91580c335f8f · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 40

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source=pdf_text observed=2026-08-15T20:32:40.938709Z digest=sha256:5f63fb94076fb613826b4b536f11e8276777272c9b0b7cd8f19277a87a959154

Observation 414525b9-8a5b-4065-8483-a71f77bbeffb · outbound

This paper cites ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Reference 41

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source=pdf_text observed=2026-08-15T20:32:40.942724Z digest=sha256:4ce0b927b220eacd6160118fa8afd8504c6b437ebf4bd82b52bfa55b3e037345

Observation 24f356d9-bbf9-40db-8d5c-cfcfe7b64b0a · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 42

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source=pdf_text observed=2026-08-15T20:32:40.947028Z digest=sha256:0c484b7244bbf0ec77e17120b5dde451ec3be1fc745c01f5fdc18655945f0e83

Observation 274692de-a92e-4369-af54-11a06ca048b5 · outbound

This paper cites Can LLM already serve as A database interface? A big bench for large-scale database grounded text-to-sqls.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Can LLM already serve as A database interface? A big bench for large-scale database grounded text-to-sqls

Reference 43

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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=2026-08-15T20:32:40.951606Z digest=sha256:5a0a10140abfa07689ab026d1b77157a88560e1ab6a93f180deded462d93960c

Observation c0a8f68b-546d-46ed-861d-83335c12f674 · outbound

This paper cites an unresolved cited work.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Unresolved cited work

Reference 44

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source=pdf_text observed=2026-08-15T20:32:40.955770Z digest=sha256:49038de953230b2f8c3f8bae61716d115c450ca0c1009135e580bf53849a7c04

Observation 7c08a0e0-9c40-4a7d-8217-425145c7bf77 · outbound

This paper cites Woodward, Jinxia Xie, and Peng- sheng Huang.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Woodward, Jinxia Xie, and Peng- sheng Huang

Reference 45

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source=pdf_text observed=2026-08-15T20:32:40.959901Z digest=sha256:c5c4e689d2a31af44e4cef8bbca46890799fd457cf3025ad9a995ac557e43eb9

Observation 3f8772e4-7837-4833-8e0e-35f6158907a0 · outbound

This paper cites Structure-grounded pretraining for text-to-sql.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Structure-grounded pretraining for text-to-sql

Reference 46

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no resolver link, observed 2026-08-15T20:32:40.963970Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:32:40.963970Z digest=sha256:8e7049abb6de0ba0642eac7f705b02f15e29f03e5ee29d0c11913868fc955a06

Observation 64426ab0-605c-4e20-9127-541faaf10c73 · outbound

This paper cites Exploring underexplored limitations of cross-domain text-to-sql generalization.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Exploring underexplored limitations of cross-domain text-to-sql generalization

Reference 47

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source=pdf_text observed=2026-08-15T20:32:40.968750Z digest=sha256:2a0c12fc864bea630af17f6f491c873d27bfecc9ed7858f423a970421cf0dda9

Observation 147b7042-c24f-44aa-b352-b440ba779c22 · outbound

This paper cites Semantic evaluation for text-to-sql with distilled test suites.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Semantic evaluation for text-to-sql with distilled test suites

Reference 48

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source=pdf_text observed=2026-08-15T20:32:40.973089Z digest=sha256:8adc4c710641eafed11a0998d9b02b1b182bab01d70fed379f0fd1cc02788b36

Observation 2761e7cd-33d0-436c-b242-ec043a6d0aa7 · outbound

This paper cites Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generation.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generation

Reference 49

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:32:40.977265Z digest=sha256:17d3a3ab558b01621467004e30b4a2011f3e83cc256bbc5fc6f16bd10ac42cd8

Observation 93cdbcc2-bdb8-4134-a2d5-e45ad1a145c9 · outbound

This paper cites OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Reference 50

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source=pdf_text observed=2026-08-15T20:32:40.982143Z digest=sha256:0c30c21a87cf5c933444e56f5913be927e52e4443554749d019bb72b2eebb215

Observation 28270467-f991-4251-9f3b-bf92c6665afe · outbound

This paper cites Sqlite home page, n.d.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Sqlite home page, n.d

Reference 51

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raw_fallback, observed 2026-08-15T20:32:42.122553Z

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=2026-08-15T20:32:40.986662Z digest=sha256:79f9ff53e2663bda30b480c4b12ac4361077f913935b1f049dfe319137e28c65

Observation 82db7444-3c8f-4fbc-8903-3d151d0d57ab · outbound

This paper cites MCTS-SQL: an effective framework for text-to-sql with monte carlo tree search.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL MCTS-SQL: an effective framework for text-to-sql with monte carlo tree search

Reference 52

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source=pdf_text observed=2026-08-15T20:32:40.990796Z digest=sha256:81b5cc76104adcfe72e1af34d0e4a0d4222bcd64ece77608b3cd6dead06c9bb3

Observation 558721ec-9157-41f6-ba4c-da3a45ddacd8 · outbound

This paper cites Bridging the Gap: Transforming Natural Language Questions into SQL Queries via Abstract Query Pattern and Contextual Schema Markup.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Bridging the Gap: Transforming Natural Language Questions into SQL Queries via Abstract Query Pattern and Contextual Schema Markup

Reference 53

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source=pdf_text observed=2026-08-15T20:32:40.995113Z digest=sha256:dc33fdbdb4a95bbd4f44ceef6ba281d8b6ea4e2ab63c951027eea555e46fcb3f

Observation 9281878b-0dae-4d03-9513-f66877df744f · outbound

This paper cites MCS-SQL: leveraging multiple prompts and multiple-choice selection for text-to-sql generation.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL MCS-SQL: leveraging multiple prompts and multiple-choice selection for text-to-sql generation

Reference 54

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verified fuzzy
raw_fallback, observed 2026-08-15T20:32:42.109177Z

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=2026-08-15T20:32:40.999776Z digest=sha256:081b21405f30554cd44eca7910c98a5ddff5dbeba94cf21b40c9c13c1430b1f6

Observation 30cc354a-1ac5-450d-80dd-1bc2046ed8c9 · outbound

This paper cites Synthesizing text-to-sql data from weak and strong llms.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Synthesizing text-to-sql data from weak and strong llms

Reference 55

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source=pdf_text observed=2026-08-15T20:32:41.003877Z digest=sha256:1ae714110306555e8b48251b869aabcc8bae461aae06ad226d2c94f640c11554

Observation ce6c8b22-6abb-4a88-8ebc-7fdbd2c1e628 · outbound

This paper cites Uncovering the Impact of Chain-of-Thought Reasoning for Direct Preference Optimization: Lessons from Text-to-SQL.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Uncovering the Impact of Chain-of-Thought Reasoning for Direct Preference Optimization: Lessons from Text-to-SQL

Reference 56

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source=pdf_text observed=2026-08-15T20:32:41.007995Z digest=sha256:10da539654379f39b920d75485c07cbfcc622e630d504b84744b1c2996a8682b

Observation 4a514209-8fa4-47f6-b45a-a00f4a4e89c5 · outbound

This paper cites DTS-SQL: decomposed text-to-sql with small large language models.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL DTS-SQL: decomposed text-to-sql with small large language models

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-15T20:32:42.095624Z

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=2026-08-15T20:32:41.011749Z digest=sha256:43a289856da43d3d28be0986552c519249cbcfeae6de1ce9c1d7cdc1a60d0bb6

Observation 2e92b068-0656-4764-aac6-81f756d8aa1d · outbound

This paper cites DB-Explore: Automated Database Exploration and Instruction Synthesis for Text-to-SQL.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL DB-Explore: Automated Database Exploration and Instruction Synthesis for Text-to-SQL

Reference 58

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source=pdf_text observed=2026-08-15T20:32:41.015782Z digest=sha256:7e8ff03397a314485a87b5969f714ace4180eee214191250760b9e7ef8cd0ca8

Observation d5cf0d55-9a5a-4e9f-a0fc-665ca9272785 · outbound

This paper cites an unresolved cited work.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Unresolved cited work

Reference 59

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

source=pdf_text observed=2026-08-15T20:32:41.019887Z digest=sha256:aed803c895044f4dcdaaaa89fe9a11bcb37f59dbc9c66bf423c62f15d60059b8

Observation 4062a673-0b1d-4ed7-b428-a5f683d1be8d · outbound

This paper cites Before generation, align it! A novel and effective strategy for mitigating hallucinations in text-to-sql generation.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Before generation, align it! A novel and effective strategy for mitigating hallucinations in text-to-sql generation

Reference 60

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raw_fallback, observed 2026-08-15T20:32:42.068954Z

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=2026-08-15T20:32:41.023780Z digest=sha256:986a20838002d5b354b1c1f8ec111f05ce4b93061a986dbd8b674453a904843d

Observation 6064df58-073f-4acd-803c-c2f326040690 · outbound

This paper cites Sean Wang.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Sean Wang

Reference 61

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source=pdf_text observed=2026-08-15T20:32:41.027825Z digest=sha256:cd9c166c76a7c67f37d7143ad4e38730e8356c7d2aec427eaf559b82799ce81d

Observation 808c3ffe-a5fb-4f43-918c-886817e53156 · outbound

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

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)

Reference 62

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source=pdf_text observed=2026-08-15T20:32:41.031817Z digest=sha256:bd64cbc683e777c64fba01936c35f6cbc6bb9b9b20276d7077a234450b84f38e

Observation 621dce57-5b21-4f2e-ac30-15303e259e07 · outbound

This paper cites OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale

Reference 63

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source=pdf_text observed=2026-08-15T20:32:41.035888Z digest=sha256:241a1c48cdc6a8c3e4faa4f0b2732a54bcc618ccc5ac040d3c66eb3fc132344d

Observation ae34205c-2471-4d00-8fae-456cd67e48dd · outbound

This paper cites ‘sql your intermediate SQL here.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ‘sql your intermediate SQL here

Reference 66

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raw_fallback, observed 2026-08-15T20:32:42.041275Z

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=2026-08-15T20:32:41.045133Z digest=sha256:4b1d9e26c5e0f9eca76383d691931c332b8e6ada2ab98dc896759708a2137f08

Observation e2a0aa7a-b211-4967-9ae2-8ec66583bfff · outbound

This paper cites an unresolved cited work.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Unresolved cited work

Reference 68

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unresolved
raw_fallback, observed 2026-08-15T20:32:42.025959Z

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=2026-08-15T20:32:41.054418Z digest=sha256:0d23e1f6b36aefcefee6b96890791781153d50dcd2fc25576b48defdd41da81e

Observation 0cda1a64-ce3b-4600-a079-53db621053ae · outbound

This paper cites an unresolved cited work.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Unresolved cited work

Reference 69

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unresolved
raw_fallback, observed 2026-08-15T20:32:42.012659Z

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=2026-08-15T20:32:41.058583Z digest=sha256:067c84a9969d4158bb0dea84bbbbd6f7c513599cc4976642256cce63ed821d5a

Observation 7e7b71b3-6cab-4c86-8668-d9e5c3b39fda · outbound

This paper cites ‘sql your final SQL here.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ‘sql your final SQL here

Reference 70

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raw_fallback, observed 2026-08-15T20:32:41.999297Z

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=2026-08-15T20:32:41.062414Z digest=sha256:25c140caef808f122b41c59550cc0adef7147529b1785b17e86b44321e8c1ff9

Observation c1775199-a768-4640-b97a-225151687fb5 · outbound

This paper cites an unresolved cited work.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Unresolved cited work

Reference 71

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unresolved
raw_fallback, observed 2026-08-15T20:32:42.054963Z

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=2026-08-15T20:32:41.066358Z digest=sha256:24771d0265c66a31e027b0c1cfd10cf5e3b29a16749235a4a74ca7046b0e6f65

Observation f2763a25-6021-43a6-a104-792063577fdf · outbound

This paper cites ‘sql your final SQL here.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL ‘sql your final SQL here

Reference 72

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verified fuzzy
raw_fallback, observed 2026-08-15T20:32:41.985301Z

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=2026-08-15T20:32:41.070609Z digest=sha256:1ffbed9f279334510507534f3fd35bbf64980fa10135213b7b294b91200c2ac9

Observation fd9dc8b9-76f7-4fc4-bd85-65585c149a01 · outbound

This paper cites fastestlaptime.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL fastestlaptime

Reference 1971

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verified fuzzy
raw_fallback, observed 2026-08-15T20:32:41.971944Z

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=2026-08-15T20:32:41.075935Z digest=sha256:3ffcddffe16b3644d9a9da4da9dd12e931cb4d42cdf64734a5ca1918754c2871

Observation 5ba5a1f1-a537-4034-971b-9be23e7b4a9e · outbound

This paper cites an unresolved cited work.

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL Unresolved cited work

Reference 2024

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unresolved
raw_fallback, observed 2026-08-15T20:32:42.180799Z

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=2026-08-15T20:32:40.912119Z digest=sha256:d00b8efb885ffe49d794316d8ca3449e8b28aeab9395974907737965f9213483

Pith citing papers

Observation 85310cf9-4ec0-45a0-b024-6ef43f7bb8e6 · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:02:25.235666Z

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=arxiv_source observed=2026-05-18T00:02:24.352947Z digest=sha256:b0aa8c5d72a6e19674e94fcc121a71f8b699f719ed2d81fc3d3030d81a47af53

Observation 05004209-3df8-49a7-b630-50ae134e58c9 · inbound

ReLog: Execution-Aware Logging with Runtime Feedback for LLM-Oriented Debugging cites this paper.

ReLog: Execution-Aware Logging with Runtime Feedback for LLM-Oriented Debugging ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T05:40:55.951093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:40:55.951093Z digest=sha256:e264f2d20e0cf415913f7b80bc5c6c8b6e93ade3691962a8ef7d1cfbff59742a

Observation d515d7cc-2d10-4ecd-b10d-5398db85108d · inbound

Draft-Refine-Optimize: Self-Evolved Learning for Natural Language to MongoDB Query Generation cites this paper.

Draft-Refine-Optimize: Self-Evolved Learning for Natural Language to MongoDB Query Generation ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:20:02.232960Z

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=2026-05-15T13:16:49.107656Z digest=sha256:4b177bbfd7252b1dd75cf8f54e9979051d8f3cd19e05fca21ac0c99e139b6cb3

Observation 7ef15ec5-b352-47d7-ab8e-d09c25ed60a7 · inbound

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards cites this paper.

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:37:09.673424Z

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=arxiv_source observed=2026-06-27T22:27:38.131329Z digest=sha256:f28616336fdb7306cb7e131797dc5833a13a0d9442692707786100f099a33f8f