Papers SQL Parsing
“SQL Parsing” 태그가 달린 논문 50편 · 필터 해제
Importance of Synthesizing High-quality Data for Text-to-SQL Parsing
Recently, there has been increasing interest in synthesizing data to improve downstream text-to-SQL tasks. In this paper, we first examined the existing synthesized datasets and discovered that state-of-the-art text-to-S…
SQL ParsingSQL-to-TextText to SQLText-To-SQL+1Towards Generalizable and Robust Text-to-SQL Parsing
Text-to-SQL parsing tackles the problem of mapping natural language questions to executable SQL queries. In practice, text-to-SQL parsers often encounter various challenging scenarios, requiring them to be generalizable …
SQL ParsingText to SQLText-To-SQLSTAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing
In this paper, we propose a novel SQL guided pre-training framework STAR for context-dependent text-to-SQL parsing, which leverages contextual information to enrich natural language (NL) utterance and table schema repres…
Contrastive LearningSQL ParsingText to SQLText-To-SQLSUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers
This paper aims to improve the performance of text-to-SQL parsing by exploring the intrinsic uncertainties in the neural network based approaches (called SUN). From the data uncertainty perspective, it is indisputable th…
SQL ParsingText to SQLText-To-SQLA Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions
Text-to-SQL parsing is an essential and challenging task. The goal of text-to-SQL parsing is to convert a natural language (NL) question to its corresponding structured query language (SQL) based on the evidences provide…
SQL ParsingText to SQLText-To-SQLSeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Dataset
As the first session-level Chinese dataset, CHASE contains two separate parts, i.e., 2,003 sessions manually constructed from scratch (CHASE-C), and 3,456 sessions translated from English SParC (CHASE-T). We find the two…
SQL ParsingText to SQLText-To-SQLSemantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph
The generalizability to new databases is of vital importance to Text-to-SQL systems which aim to parse human utterances into SQL statements. Existing works achieve this goal by leveraging the exact matching method to ide…
Graph LearningSQL ParsingText to SQLText-To-SQLProton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing
The importance of building text-to-SQL parsers which can be applied to new databases has long been acknowledged, and a critical step to achieve this goal is schema linking, i.e., properly recognizing mentions of unseen c…
SQL ParsingText to SQLText-To-SQLCQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parsers
Context-dependent text-to-SQL is the task of translating multi-turn questions into database-related SQL queries. Existing methods typically focus on making full use of history context or previously predicted SQL for curr…
SQL ParsingText to SQLText-To-SQLBridging the Generalization Gap in Text-to-SQL Parsing with Schema Expansion
Text-to-SQL parsers map natural language questions to programs that are executable over tables to generate answers, and are typically evaluated on large-scale datasets like Spider (Yu et al., 2018). We argue that existin…
Domain GeneralizationSQL ParsingText to SQLText-To-SQLLeveraging Explicit Lexico-logical Alignments in Text-to-SQL Parsing
Text-to-SQL aims to parse natural language questions into SQL queries, which is valuable in providing an easy interface to access large databases. Previous work has observed that leveraging lexico-logical alignments is v…
SQL ParsingText to SQLText-To-SQLFaster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss
Grammar-based parsers have achieved high performance in the cross-domain text-to-SQL parsing task, but suffer from low decoding efficiency due to the much larger number of actions for grammar selection than that of token…
SQL ParsingText to SQLText-To-SQLWeakly Supervised Text-to-SQL Parsing through Question Decomposition
Text-to-SQL parsers are crucial in enabling non-experts to effortlessly query relational data. Training such parsers, by contrast, generally requires expert annotation of natural language (NL) utterances paired with corr…
SQL ParsingText to SQLText-To-SQLWeakly Supervised Text-to-SQL Parsing through Question Decomposition
Text-to-SQL parsers are crucial in enabling non-experts to effortlessly query relational data. Training such parsers, by contrast, generally requires expertise in annotating natural language (NL) utterances with correspo…
SQL ParsingText to SQLText-To-SQLSpeech-to-SQL Parsing: Error Correction with Multi-modal Representations
We study the task of spoken natural language to SQL parsing (speech-to-SQL), where the goal is to map a spoken utterance to the corresponding SQL. Existing work on SQL parsing has focused on text as input (text-to-SQL). …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech Recognition+3Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing
The importance of building text-to-SQL parsers which can be applied to new databases has long been acknowledged, and a critical step to achieve this goal is schema linking, i.e., properly recognizing mentions of unseen c…
SQL ParsingText to SQLText-To-SQLKaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers
The goal of database question answering is to enable natural language querying of real-life relational databases in diverse application domains. Recently, large-scale datasets such as Spider and WikiSQL facilitated novel…
Question AnsweringSQL ParsingText to SQLText-To-SQL+1Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL
Recently, Text-to-SQL for multi-turn dialogue has attracted great interest. Here, the user input of the current turn is parsed into the corresponding SQL query of the appropriate database, given all previous dialogue his…
Semantic ParsingSQL ParsingText to SQLText-To-SQLLearning to Synthesize Data for Semantic Parsing
Synthesizing data for semantic parsing has gained increasing attention recently. However, most methods require handcrafted (high-precision) rules in their generative process, hindering the exploration of diverse unseen d…
Domain GeneralizationSemantic ParsingSQL ParsingText to SQL+2Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing
Data augmentation has attracted a lot of research attention in the deep learning era for its ability in alleviating data sparseness. The lack of labeled data for unseen evaluation databases is exactly the major challenge…
Data AugmentationQuestion GenerationQuestion-GenerationSQL Parsing+2