ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects | Paper Citation Record

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This paper cites Github copilot – your ai pair programmer.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Github copilot – your ai pair programmer

Reference 1

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Observation 32f3dc6e-44de-45d5-a230-ef8009e87908 · outbound

This paper cites an unresolved cited work.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Unresolved cited work

Reference 2

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Observation 60112040-b5d2-4afe-9b92-9f30e9ee323d · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 4

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 5

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls

Reference 6

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Observation fbf11f26-cd60-428a-a446-e12bde52f205 · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Reference 7

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Observation 57002d14-9f9e-4693-9762-6f1da5a85e2c · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Codes: Towards building open-source language models for text-to-sql

Reference 8

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Observation 7ca4bd9b-78ad-47f6-9196-1f9749e3c247 · outbound

This paper cites StructLM: Towards Building Generalist Models for Structured Knowledge Grounding.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects StructLM: Towards Building Generalist Models for Structured Knowledge Grounding

Reference 9

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Observation 3f5845b0-f46c-4c85-83b9-28e570f4db3b · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects C3: Zero-shot Text-to-SQL with ChatGPT

Reference 10

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Observation 88130d9f-aabd-4845-b43b-0c0b93c34444 · outbound

This paper cites Din-sql: Decomposed in-context learning of text-to-sql with self-correction.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Din-sql: Decomposed in-context learning of text-to-sql with self-correction

Reference 11

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Observation 699838f5-0e84-400f-ae34-09269da49e24 · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Reference 12

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Observation b47d81f7-0375-4b7f-97a9-addaa3e5a00c · outbound

This paper cites Natural SQL: Making SQL Easier to Infer from Natural Language Specifications.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Natural SQL: Making SQL Easier to Infer from Natural Language Specifications

Reference 13

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Observation eb376313-8d80-40e6-862a-ab050307ae0b · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Structure-grounded pretraining for text-to-sql

Reference 14

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Observation 9c1bcc7f-fa6e-4eb8-a417-c31f57edd79c · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging

Reference 15

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ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Unresolved cited work

Reference 16

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Observation 9e6d14ce-37b9-4e6d-bd8a-5c43b70b1692 · outbound

This paper cites Translating between sql dialects for cloud migration.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Translating between sql dialects for cloud migration

Reference 17

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Observation 32b6f81e-418c-486d-a2d8-c46eb5aa5d07 · outbound

This paper cites Magicoder: Empowering Code Generation with OSS-Instruct.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Magicoder: Empowering Code Generation with OSS-Instruct

Reference 18

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Observation bf3dad4d-5735-48d4-a8b8-f35920e5fb29 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 19

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Observation 7e73cfd8-dc84-4a3d-8beb-05899e30c9d5 · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Recent advances in text-to-sql: A survey of what we have and what we expect

Reference 20

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Observation caa6844a-5056-48d2-8605-f883f99dc97c · outbound

This paper cites TAPEX: table pre-training via learning a neural SQL executor.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects TAPEX: table pre-training via learning a neural SQL executor

Reference 21

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Observation a7f04155-9413-4147-9d41-3b6714b689ac · outbound

This paper cites Learning from Executions for Semantic Parsing.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Learning from Executions for Semantic Parsing

Reference 22

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ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Unresolved cited work

Reference 23

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ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Unresolved cited work

Reference 24

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Observation 5e569a2b-f3d7-4427-b05e-33600a798f0e · outbound

This paper cites GPT-4 Technical Report.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects GPT-4 Technical Report

Reference 25

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Observation 2a30537b-d041-4ca4-9f2b-7a551d0f9078 · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 26

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Observation 6ab4703d-9bbf-446e-a75b-ea806c802bca · outbound

This paper cites Benchmarking meaning representations in neural semantic parsing.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Benchmarking meaning representations in neural semantic parsing

Reference 27

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This paper cites MoMQ: Mixture-of-Experts Enhances Multi-Dialect Query Generation across Relational and Non-Relational Databases.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects MoMQ: Mixture-of-Experts Enhances Multi-Dialect Query Generation across Relational and Non-Relational Databases

Reference 28

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Observation 3c5aa5db-2b62-41ac-b4a4-cd33ecf22363 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Evaluating Large Language Models Trained on Code

Reference 29

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 30

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Observation db33d94d-fb4d-4a57-ba9a-f633955bf079 · outbound

This paper cites StarCoder: may the source be with you!.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects StarCoder: may the source be with you!

Reference 31

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Observation 5bfe67ba-2629-428c-907c-6e001e227878 · outbound

This paper cites Code Llama: Open Foundation Models for Code.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Code Llama: Open Foundation Models for Code

Reference 32

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Observation f6055ec2-1473-4d97-8287-7ab6f664e428 · outbound

This paper cites Qwen2.5-Coder Technical Report.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Qwen2.5-Coder Technical Report

Reference 33

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Observation 6af15b12-8a8e-4db4-898f-371d6b45266a · outbound

This paper cites Wizardcoder: Empowering code large language models with evol-instruct.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Wizardcoder: Empowering code large language models with evol-instruct

Reference 34

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Observation bdd496d1-7107-4883-9a8d-f564bff54525 · outbound

This paper cites WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning

Reference 35

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Observation 68f31090-3956-48f1-94c3-ea870ec8498e · outbound

This paper cites Wizardlm: Empowering large language models to follow complex instructions.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Wizardlm: Empowering large language models to follow complex instructions

Reference 36

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Observation 6f1cdc92-c4ba-4516-8791-f37cc701aabf · outbound

This paper cites OctoPack: Instruction Tuning Code Large Language Models.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects OctoPack: Instruction Tuning Code Large Language Models

Reference 37

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Observation 33b272c7-4fd3-46cc-a73b-af5fe95f6251 · outbound

This paper cites IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators

Reference 38

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This paper cites UniCoder: Scaling Code Large Language Model via Universal Code.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects UniCoder: Scaling Code Large Language Model via Universal Code

Reference 39

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Observation 5b478ff1-c744-4863-b47d-ed88d23ab3f3 · outbound

This paper cites Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Reference 41

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Observation 8b6da9a1-e4ca-473b-a352-46ff9a7757d3 · outbound

This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 42

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Observation fd849909-c311-403b-ba6c-77d77eba7568 · outbound

This paper cites Scaling Relationship on Learning Mathematical Reasoning with Large Language Models.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Scaling Relationship on Learning Mathematical Reasoning with Large Language Models

Reference 43

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Observation 7667fae6-a1c3-491b-b111-15d020cc63b6 · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 44

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Observation 4910ac59-fb04-4d3c-8764-96caa009b18f · outbound

This paper cites Star: Bootstrapping reasoning with reasoning.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Star: Bootstrapping reasoning with reasoning

Reference 45

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Observation 36a56f51-7c21-40e1-9933-6679a979981c · outbound

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ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model

Reference 46

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Observation 25472f58-38ef-457d-a941-3594765ceb59 · outbound

This paper cites Personalized Visual Instruction Tuning.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Personalized Visual Instruction Tuning

Reference 47

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Observation 1447f460-5199-4168-918b-e8be79810684 · outbound

This paper cites Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 48

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Observation 38e59e8a-d385-4e29-98f1-7c5aa6a0a585 · outbound

This paper cites VideoDPO: Omni-Preference Alignment for Video Diffusion Generation.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects VideoDPO: Omni-Preference Alignment for Video Diffusion Generation

Reference 49

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Observation ce01d40c-141d-49a2-9264-2d02b2e6bb5b · outbound

This paper cites Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions

Reference 50

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Observation 5bbc2eb1-6e42-4aa2-a23b-b405ee5c834b · outbound

This paper cites ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

Reference 51

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Observation 32d43535-3a36-405e-a1dc-2c1b4f6cfb16 · outbound

This paper cites RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

Reference 52

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Observation 565495d2-4a8d-42c1-9b8c-e2b642543bbb · outbound

This paper cites Reinforced Self-Training (ReST) for Language Modeling.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Reinforced Self-Training (ReST) for Language Modeling

Reference 53

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Observation 8b648291-c5c9-4a08-9d88-4db484388f4e · outbound

This paper cites Proximal Policy Optimization Algorithms.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Proximal Policy Optimization Algorithms

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.084335Z

Source-reported events for the cited work

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Observation 3b356100-4e41-4ff9-8f92-5ad0337c8541 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Direct preference optimization: Your language model is secretly a reward model

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.165655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25452884-198f-419e-acf0-d0fde7eaafaa · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.229475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 075bf78f-aae2-44a7-a6c9-7fe466566dc7 · outbound

This paper cites Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.300594Z

Source-reported events for the cited work

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Observation 5f40b8b2-24f1-42cf-a1d3-c9231cf2c9aa · outbound

This paper cites Text-to-SQL Generation for Question Answering on Electronic Medical Records.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Text-to-SQL Generation for Question Answering on Electronic Medical Records

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:56:03.636962Z

Source-reported events for the cited work

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Observation 35fcc647-705c-48dd-81b2-b400e92639df · outbound

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

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Recent advances in text-to- SQL : A survey of what we have and what we expect

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:04.941566Z

Source-reported events for the cited work

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Observation de089142-ae97-4f92-85c5-533f9a8cd8d6 · outbound

This paper cites https://ai.meta.com/blog/meta-llama-3/.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects https://ai.meta.com/blog/meta-llama-3/

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:04.766742Z

Source-reported events for the cited work

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Observation 6866a837-e748-4026-a7ef-e74b87ec5b6b · outbound

This paper cites an unresolved cited work.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Unresolved cited work

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.531021Z

Source-reported events for the cited work

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Observation 82a8397e-6cdb-465e-b41e-286a1a9506b5 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.636977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ae691fd-bf8d-4499-9c10-a8e220b28650 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Gonzalez, Hao Zhang, and Ion Stoica

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.694734Z

Source-reported events for the cited work

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Observation 5316736b-685e-43d3-abe8-893985b9b0b6 · outbound

This paper cites LIMA: Less Is More for Alignment.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects LIMA: Less Is More for Alignment

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.750025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19ceb1a9-73c0-48df-8fe4-a233a493fa12 · outbound

This paper cites Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.805632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e8d89a0-ba6f-4b57-a90c-9a04fb02de9d · outbound

This paper cites Mitigating Catastrophic Forgetting in Language Transfer via Model Merging.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Mitigating Catastrophic Forgetting in Language Transfer via Model Merging

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.896817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3693e30-e69d-4840-8577-d937c1221150 · outbound

This paper cites ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:02.947308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06eaf234-dbfa-4b6e-8877-ee3e34034ffb · outbound

This paper cites DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:03.006603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02b76a65-7a54-43de-9bbc-5c7ad1d15192 · outbound

This paper cites Mitigating the Alignment Tax of RLHF.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Mitigating the Alignment Tax of RLHF

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:03.062616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bab13e99-53ba-4ecd-bd19-efb2cfdc97c9 · outbound

This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:04.440455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3fd15962-a233-4737-9793-7a3fe59d4cd8 · outbound

This paper cites Can LLM already serve as a database interface? a BI g bench for large-scale database grounded text-to- SQL s.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Can LLM already serve as a database interface? a BI g bench for large-scale database grounded text-to- SQL s

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:04.254964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Outbound references

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