Copertina

Beyond Query-Level Comparison: Fine-Grained Reinforcement Learning for Text-to-SQL with Automated Interpretable Critiques

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Guifeng, Song, Yuanfeng, Yang, Meng, Zhu, Tao, Yin, Xiaoming, Chen, Xing
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Beyond SELECT: A Comprehensive Taxonomy-Guided Benchmark for Real-World Text-to-SQL Translation
di: Wang, Hao, et al.
Pubblicazione: (2025)

Graph-Reward-SQL: Execution-Free Reinforcement Learning for Text-to-SQL via Graph Matching and Stepwise Reward
di: Weng, Han, et al.
Pubblicazione: (2025)

Beyond Sparse Rewards: Enhancing Reinforcement Learning with Language Model Critique in Text Generation
di: Cao, Meng, et al.
Pubblicazione: (2024)

Pi-SQL: Enhancing Text-to-SQL with Fine-Grained Guidance from Pivot Programming Languages
di: chi, Yongdong, et al.
Pubblicazione: (2025)

Decoupling SQL Query Hardness Parsing for Text-to-SQL
di: Yi, Jiawen, et al.
Pubblicazione: (2023)

DataSage: Multi-agent Collaboration for Insight Discovery with External Knowledge Retrieval, Multi-role Debating, and Multi-path Reasoning
di: Liu, Xiaochuan, et al.
Pubblicazione: (2025)

MultiTEND: A Multilingual Benchmark for Natural Language to NoSQL Query Translation
di: Qin, Zhiqian, et al.
Pubblicazione: (2025)

MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation
di: Gorti, Satya Krishna, et al.
Pubblicazione: (2024)

ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQL
di: Dai, Yaxun, et al.
Pubblicazione: (2025)

LEAF-SQL: Level-wise Exploration with Adaptive Fine-graining for Text-to-SQL Skeleton Prediction
di: Tan, Zhao, et al.
Pubblicazione: (2026)

SQL-Trail: Multi-Turn Reinforcement Learning with Interleaved Feedback for Text-to-SQL
di: Hua, Harper, et al.
Pubblicazione: (2026)

DAC: Decomposed Automation Correction for Text-to-SQL
di: Wang, Dingzirui, et al.
Pubblicazione: (2024)

ReViSQL: Achieving Human-Level Text-to-SQL
di: Zhu, Yuxuan, et al.
Pubblicazione: (2026)

CSC-SQL: Corrective Self-Consistency in Text-to-SQL via Reinforcement Learning
di: Sheng, Lei, et al.
Pubblicazione: (2025)

Beyond Text-to-SQL for IoT Defense: A Comprehensive Framework for Querying and Classifying IoT Threats
di: Pavlich, Ryan, et al.
Pubblicazione: (2024)

Critique Fine-Tuning: Learning to Critique is More Effective than Learning to Imitate
di: Wang, Yubo, et al.
Pubblicazione: (2025)

Beyond Static Pipelines: Learning Dynamic Workflows for Text-to-SQL
di: Wang, Yihan, et al.
Pubblicazione: (2026)

SAFE-SQL: Self-Augmented In-Context Learning with Fine-grained Example Selection for Text-to-SQL
di: Lee, Jimin, et al.
Pubblicazione: (2025)

Critique-Coder: Enhancing Coder Models by Critique Reinforcement Learning
di: Ruan, Chi, et al.
Pubblicazione: (2025)

AmbiSQL: Interactive Ambiguity Detection and Resolution for Text-to-SQL
di: Ding, Zhongjun, et al.
Pubblicazione: (2025)

MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL
di: Wang, Bing, et al.
Pubblicazione: (2023)

Text2VectorSQL: Towards a Unified Interface for Vector Search and SQL Queries
di: Wang, Zhengren, et al.
Pubblicazione: (2025)

Unveiling Large Language Models Generated Texts: A Multi-Level Fine-Grained Detection Framework
di: Tao, Zhen, et al.
Pubblicazione: (2024)

PolySQL: Scaling Text-to-SQL Evaluation Across SQL Dialects via Automated Backend Isomorphism
di: Perlitz, Yotam, et al.
Pubblicazione: (2026)

Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL
di: Pourreza, Mohammadreza, et al.
Pubblicazione: (2025)

Query Carefully: Detecting the Unanswerables in Text-to-SQL Tasks
di: Saxer, Jasmin, et al.
Pubblicazione: (2025)

Dubo-SQL: Diverse Retrieval-Augmented Generation and Fine Tuning for Text-to-SQL
di: Thorpe, Dayton G., et al.
Pubblicazione: (2024)

Generating Grounded Responses to Counter Misinformation via Learning Efficient Fine-Grained Critiques
di: Xu, Xiaofei, et al.
Pubblicazione: (2025)

Critique-RL: Training Language Models for Critiquing through Two-Stage Reinforcement Learning
di: Xi, Zhiheng, et al.
Pubblicazione: (2025)

Using LLM to select the right SQL Query from candidates
di: Li, Zhenwen, et al.
Pubblicazione: (2024)

Text2SQL-Flow: A Robust SQL-Aware Data Augmentation Framework for Text-to-SQL
di: Cai, Qifeng, et al.
Pubblicazione: (2025)

Reinforcing Code Generation: Improving Text-to-SQL with Execution-Based Learning
di: Kulkarni, Atharv, et al.
Pubblicazione: (2025)

PRACTIQ: A Practical Conversational Text-to-SQL dataset with Ambiguous and Unanswerable Queries
di: Dong, Mingwen, et al.
Pubblicazione: (2024)

EvolSQL: Structure-Aware Evolution for Scalable Text-to-SQL Data Synthesis
di: Pan, Xuanguang, et al.
Pubblicazione: (2026)

ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinement
di: Hong, Zijin, et al.
Pubblicazione: (2026)

XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL
di: Liu, Yifu, et al.
Pubblicazione: (2025)

GenProve: Learning to Generate Text with Fine-Grained Provenance
di: Wei, Jingxuan, et al.
Pubblicazione: (2026)

E3: Issue-Level Backtesting for Automated Research Critique
di: Chaudhuri, Yashwardhan, et al.
Pubblicazione: (2026)

Bridging the Gap: Enabling Natural Language Queries for NoSQL Databases through Text-to-NoSQL Translation
di: Lu, Jinwei, et al.
Pubblicazione: (2025)

Towards Faithful and Controllable Personalization via Critique-Post-Edit Reinforcement Learning
di: Zhu, Chenghao, et al.
Pubblicazione: (2025)