暂无分享,去创建一个
[1] Christopher D. Manning,et al. Get To The Point: Summarization with Pointer-Generator Networks , 2017, ACL.
[2] Michael D. Ernst,et al. NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System , 2018, LREC.
[3] Po-Sen Huang,et al. Execution-Guided Neural Program Decoding , 2018, ArXiv.
[4] Jonathan Berant,et al. Global Reasoning over Database Structures for Text-to-SQL Parsing , 2019, EMNLP.
[5] Peter Thanisch,et al. Natural language interfaces to databases – an introduction , 1995, Natural Language Engineering.
[6] Omer Levy,et al. RoBERTa: A Robustly Optimized BERT Pretraining Approach , 2019, ArXiv.
[7] Peter Rob,et al. Database systems : design, implementation, and management , 2000 .
[8] Souvik Kundu,et al. Hybrid Ranking Network for Text-to-SQL , 2020, ArXiv.
[9] Alexander I. Rudnicky,et al. Expanding the Scope of the ATIS Task: The ATIS-3 Corpus , 1994, HLT.
[10] Steven C. H. Hoi,et al. Photon: A Robust Cross-Domain Text-to-SQL System , 2020, ACL.
[11] Karen Spärck Jones,et al. Natural language interfaces to databases , 1990, The Knowledge Engineering Review.
[12] Peter Rob,et al. Database systems - design, implementation, and management (2. ed.) , 1995 .
[13] Seunghyun Park,et al. A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization , 2019, ArXiv.
[14] Wen-tau Yih,et al. An Imitation Game for Learning Semantic Parsers from User Interaction , 2020, EMNLP.
[15] Xiaodong Liu,et al. Multi-Task Deep Neural Networks for Natural Language Understanding , 2019, ACL.
[16] Tao Yu,et al. SParC: Cross-Domain Semantic Parsing in Context , 2019, ACL.
[17] Yan Gao,et al. Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation , 2019, ACL.
[18] Jonathan Berant,et al. Span-based Semantic Parsing for Compositional Generalization , 2020, ArXiv.
[19] Xiaodong Liu,et al. RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers , 2019, ACL.
[20] Omer Levy,et al. SpanBERT: Improving Pre-training by Representing and Predicting Spans , 2019, TACL.
[21] Luyao Chen,et al. CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases , 2019, EMNLP.
[22] Mirella Lapata,et al. Language to Logical Form with Neural Attention , 2016, ACL.
[23] Dong Ryeol Shin,et al. RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases , 2020, CL.
[24] Zhifang Sui,et al. Towards Comprehensive Description Generation from Factual Attribute-value Tables , 2019, ACL.
[25] Tao Yu,et al. Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions , 2019, EMNLP.
[26] Arman Cohan,et al. Longformer: The Long-Document Transformer , 2020, ArXiv.
[27] Raymond J. Mooney,et al. Learning to Parse Database Queries Using Inductive Logic Programming , 1996, AAAI/IAAI, Vol. 2.
[28] George R. Doddington,et al. The ATIS Spoken Language Systems Pilot Corpus , 1990, HLT.
[29] Jonathan Berant,et al. SmBoP: Semi-autoregressive Bottom-up Semantic Parsing , 2020, ArXiv.
[30] Lifu Tu,et al. An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models , 2020, Transactions of the Association for Computational Linguistics.
[31] Ming-Wei Chang,et al. Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing , 2020, ACL.
[32] Chen Liang,et al. Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing , 2018, NeurIPS.
[33] Hang Li,et al. “ Tony ” DNN Embedding for “ Tony ” Selective Read for “ Tony ” ( a ) Attention-based Encoder-Decoder ( RNNSearch ) ( c ) State Update s 4 SourceVocabulary Softmax Prob , 2016 .
[34] Luke S. Zettlemoyer,et al. Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars , 2005, UAI.
[35] Ming-Wei Chang,et al. Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both? , 2020, ACL.
[36] Yang Zhang,et al. Mention Extraction and Linking for SQL Query Generation , 2020, EMNLP.
[37] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[38] Thomas Muller,et al. TaPas: Weakly Supervised Table Parsing via Pre-training , 2020, ACL.
[39] Marc van Zee,et al. Compositional Generalization in Semantic Parsing: Pre-training vs. Specialized Architectures , 2020, ArXiv.
[40] Graham Neubig,et al. TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data , 2020, ACL.
[41] Tao Yu,et al. SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task , 2018, EMNLP.
[42] Ashish Vaswani,et al. Self-Attention with Relative Position Representations , 2018, NAACL.
[43] Tong Guo,et al. Content Enhanced BERT-based Text-to-SQL Generation , 2019, ArXiv.
[44] Jesse Vig,et al. A Multiscale Visualization of Attention in the Transformer Model , 2019, ACL.
[45] Colin Raffel,et al. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer , 2019, J. Mach. Learn. Res..
[46] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[47] R'emi Louf,et al. HuggingFace's Transformers: State-of-the-art Natural Language Processing , 2019, ArXiv.
[48] Ian S. Dunn,et al. Exploring the Limits , 2009 .
[49] Kaushik Chakrabarti,et al. X-SQL: reinforce schema representation with context , 2019, ArXiv.
[50] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[51] Richard Socher,et al. Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning , 2018, ArXiv.
[52] Xifeng Yan,et al. What It Takes to Achieve 100 Percent Condition Accuracy on WikiSQL , 2018, EMNLP.
[53] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[54] Philip Massey,et al. Generating Logical Forms from Graph Representations of Text and Entities , 2019, ACL.
[55] Jonathan Berant,et al. Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing , 2019, ACL.
[56] Andrew McCallum,et al. Linguistically-Informed Self-Attention for Semantic Role Labeling , 2018, EMNLP.