mlsanityData to 7 Oct 2026

Learning Executable Semantic Parsers for Natural Language Understanding

arXiv 1603.06677 ↗First posted 22 Mar 2016cs.CL cs.AIcited by 21

Not on the map. Why?

Abstract (arXiv)

For building question answering systems and natural language interfaces, semantic parsing has emerged as an important and powerful paradigm. Semantic parsers map natural language into logical forms, the classic representation for many important linguistic phenomena. The modern twist is that we are interested in learning semantic parsers from data, which introduces a new layer of statistical and computational issues. This article lays out the components of a statistical semantic parser, highlighting the key challenges. We will see that semantic parsing is a rich fusion of the logical and the statistical world, and that this fusion will play an integral role in the future of natural language understanding systems.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Mar 2016.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 3; 2023: 6; 2024: 1; 2025: 1; 2026: 1.

21 papers.

Sort:

By area:

  1. 2022PAL: Program-aided Language Modelscited by 635
  2. 2022Complexity-Based Prompting for Multi-Step Reasoningcited by 387
  3. 2021KaggleDBQA: Realistic Evaluation of Text-to-SQL Parserscited by 105
  4. 2021Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoningcited by 85
  5. 2021Leveraging Language to Learn Program Abstractions and Search Heuristicscited by 44
  6. 2023Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Modelscited by 37
  7. 2021Communicating Natural Programs to Humans and Machinescited by 35
  8. 2024AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queriescited by 32
  9. 2021RuleBert: Teaching Soft Rules to Pre-trained Language Modelscited by 25
  10. 2021Measuring and Improving BERT's Mathematical Abilities by Predicting the Order of Reasoningcited by 23
  11. 2021Zero-Shot Cross-lingual Semantic Parsingcited by 19
  12. 2021Towards Socially Intelligent Agents with Mental State Transition and Human Utilitycited by 14
9 more
  1. 2023Bring Your Own KG: Self-Supervised Program Synthesis for Zero-Shot KGQAcited by 11
  2. 2023Measuring and Mitigating Constraint Violations of In-Context Learning for Utterance-to-API Semantic Parsingcited by 6
  3. 2023Symbolic Planning and Code Generation for Grounded Dialoguecited by 5
  4. 2026Compress the Context, Keep the Commitments: A Formal Framework for Verifiable LLM Context Compressioncited by 3
  5. 2023Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsingcited by 2
  6. 2025Jackal: A Real-World Execution-Based Benchmark Evaluating Large Language Models on Text-to-JQL Taskscited by 2
  7. 2022Trust in Language Grounding: a new AI challenge for human-robot teamscited by 1
  8. 2021An Inference Approach To Question Answering Over Knowledge Graphscited by 0
  9. 2023Meta Semantics: Towards better natural language understanding and reasoningcited by 0