mlsanityData to 14 Oct 2026

Memory-Based Semantic Parsing

arXiv 2110.07358 ↗First posted 7 Sep 2021cs.CLcited by 6

Not on the map. Why?

Abstract (arXiv)

We present a memory-based model for context-dependent semantic parsing. Previous approaches focus on enabling the decoder to copy or modify the parse from the previous utterance, assuming there is a dependency between the current and previous parses. In this work, we propose to represent contextual information using an external memory. We learn a context memory controller that manages the memory by maintaining the cumulative meaning of sequential user utterances. We evaluate our approach on three semantic parsing benchmarks. Experimental results show that our model can better process context-dependent information and demonstrates improved performance without using task-specific decoders.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 21 of its 54 references that are in the map. First posted on arXiv 7 Sep 2021.

Builds on

21 of 54 references.

References · 21

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
  4. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,139
  5. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 687
  6. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 424
  7. 2014Memory Networkscited by 363
  8. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
  9. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 185
  10. 2018Neural Approaches to Conversational AIcited by 165
  11. 2016Language to Logical Form with Neural Attentioncited by 158
  12. 2019SParC: Cross-Domain Semantic Parsing in Contextcited by 144
9 more
  1. 2016Data Recombination for Neural Semantic Parsingcited by 111
  2. 2017Learning a Neural Semantic Parser from User Feedbackcited by 99
  3. 2019Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questionscited by 80
  4. 2018SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Taskcited by 74
  5. 2018A Survey on Semantic Parsingcited by 62
  6. 2020How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Contextcited by 53
  7. 2015Describing Multimedia Content using Attention-based Encoder--Decoder Networkscited by 32
  8. 2018Learning to Map Context-Dependent Sentences to Executable Formal Queriescited by 23
  9. 2019Grammar-based Neural Text-to-SQL Generationcited by 23

Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 1.

6 papers.

  1. 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 52
  2. 2022CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parserscited by 11
  3. 2023Semantic Parsing for Conversational Question Answering over Knowledge Graphscited by 10
  4. 2024Conversational Code Generation: a Case Study of Designing a Dialogue System for Generating Driving Scenarios for Testing Autonomous Vehiclescited by 4
  5. 2023Conversational Semantic Parsing using Dynamic Context Graphscited by 2
  6. 2023Sentence-Incremental Neural Coreference Resolutioncited by 2