mlsanityData to 14 Oct 2026

Learning to Map Context-Dependent Sentences to Executable Formal Queries

arXiv 1804.06868 ↗First posted 18 Apr 2018cs.CLcited by 23

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Abstract (arXiv)

We propose a context-dependent model to map utterances within an interaction to executable formal queries. To incorporate interaction history, the model maintains an interaction-level encoder that updates after each turn, and can copy sub-sequences of previously predicted queries during generation. Our approach combines implicit and explicit modeling of references between utterances. We evaluate our model on the ATIS flight planning interactions, and demonstrate the benefits of modeling context and explicit references.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Apr 2018.

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Citing papers per year: 2021: 6; 2022: 11; 2023: 5; 2024: 1.

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  1. 2022Natural Language to Code Translation with Executioncited by 124
  2. 2022Natural Language to Code Generation in Interactive Data Science Notebookscited by 87
  3. 2022Inferring Rewards from Language in Contextcited by 50
  4. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  5. 2021NL-EDIT: Correcting semantic parse errors through natural language interactioncited by 33
  6. 2021Conversational Question Answering: A Surveycited by 31
  7. 2022Continual Learning for Instruction Following from Realtime Feedbackcited by 22
  8. 2021Learning Structural Edits via Incremental Tree Transformationscited by 16
  9. 2021Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsingcited by 15
  10. 2022CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parserscited by 11
  11. 2023Semantic Parsing for Conversational Question Answering over Knowledge Graphscited by 10
  12. 2022Augmenting Multi-Turn Text-to-SQL Datasets with Self-Playcited by 9
11 more
  1. 2021Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generationcited by 8
  2. 2024Evaluating Large Language Models in Semantic Parsing for Conversational Question Answering over Knowledge Graphscited by 7
  3. 2021Memory-Based Semantic Parsingcited by 6
  4. 2023History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modelingcited by 4
  5. 2022Transformer with Tree-order Encoding for Neural Program Generationcited by 3
  6. 2022Neuro-Symbolic Visual Dialogcited by 3
  7. 2022lilGym: Natural Language Visual Reasoning with Reinforcement Learningcited by 3
  8. 2023Conversational Semantic Parsing using Dynamic Context Graphscited by 2
  9. 2022Sentiment is all you need to win US Presidential electionscited by 1
  10. 2023Few-Shot Adaptation for Parsing Contextual Utterances with LLMscited by 1
  11. 2023Semantic Parsing in Limited Resource Conditionscited by 0