https://github.com/ruiqi-zhong/TestSuiteEval
공식 코드Semantic Evaluation for Text-to-SQL with Distilled Test Suites
Papers with Code 아카이브
Text-To-SQL
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Text-to-SQL is a task in natural language processing (NLP) where the goal is to automatically generate SQL queries from natural language text. The task involves converting the text input into a structured representation and then using this representation to generate a semantically correct SQL query that can be executed on a database.
<span style="color:grey; opacity: 0.6">( Image credit: SyntaxSQLNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ruiqi-zhong/emnlp23-apel
공식 코드Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL
https://github.com/runnerup96/error-detection-in-text2sql
공식 코드Confidence Estimation for Error Detection in Text-to-SQL Systems
https://github.com/runzewang/IST-SQL
공식 코드Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsing
https://github.com/ryanzhumich/editsql
공식 코드https://github.com/salesforce/TabularSemanticParsing
공식 코드Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing
https://github.com/salesforce/WikiSQL
공식 코드Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
https://github.com/sanxing-chen/linking-tale
공식 코드https://github.com/saparina/ambrosia
공식 코드AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries
https://github.com/saparina/disambiguate-then-parse
공식 코드https://github.com/saparina/text2sql-nlvariation
공식 코드Improving Generalization in Semantic Parsing by Increasing Natural Language Variation
https://github.com/sasmohaimeed/sigma
공식 코드Sigma: A dataset for text-to-code semantic parsing with statistical analysis
https://github.com/seonhee99/ehr-seqsql
공식 코드EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Records
https://github.com/shayantalaei/chess
공식 코드https://github.com/shuaichenchang/odis-text-to-sql
공식 코드https://github.com/shuaichenchang/prompt-text-to-sql
공식 코드How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings
https://github.com/shuailyu0110/sql-o1
공식 코드SQL-o1: Automatic Text-to-SQL Program Synthesis via Self-Reward Heuristic Search
https://github.com/siyue-zhang/SynTableQA
공식 코드SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQA
https://github.com/snowflakedb/ArcticTraining
공식 코드ExCoT: Optimizing Reasoning for Text-to-SQL with Execution Feedback
https://github.com/snowflakedb/arcticinference
공식 코드SuffixDecoding: Extreme Speculative Decoding for Emerging AI Applications
https://github.com/songjw133/joint-loss-tuning-of-text-to-sql
공식 코드JOLT-SQL: Joint Loss Tuning of Text-to-SQL with Confusion-aware Noisy Schema Sampling
https://github.com/sunlab-osu/MISP
공식 코드Model-based Interactive Semantic Parsing: A Unified Framework and A Text-to-SQL Case Study
https://github.com/tag-research/tag-bench
공식 코드https://github.com/taolusi/chisp
공식 코드https://github.com/taoyds/spider
공식 코드https://github.com/taoyds/syntaxsql
공식 코드SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task
https://github.com/taoyds/test-suite-sql-eval
공식 코드https://github.com/taoyds/typesql
공식 코드TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generation
https://github.com/tengwang0318/MLPrompt
공식 코드Large Language Models are Good Multi-lingual Learners : When LLMs Meet Cross-lingual Prompts
https://github.com/testzer0/ambiqt
공식 코드Benchmarking and Improving Text-to-SQL Generation under Ambiguity
https://github.com/text-to-sql-survey-coling22/text-to-sql-survey-coling22.github.io
공식 코드Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect
https://github.com/the-inscrutable-x/tacq
공식 코드Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression
https://github.com/thenamek/trustworthy-text2sql
공식 코드https://github.com/thu-bpm/chatgpt-sql
공식 코드A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability
https://github.com/thu-bpm/isesl-sql
공식 코드Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph
https://github.com/tidbcloud/tiinsight
공식 코드Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.