mlsanityData to 7 Oct 2026

Retrieval-Augmented Semantic Parsing: Improving Generalization with Lexical Knowledge

arXiv 2412.10207 ↗First posted 13 Dec 2024cs.CLcited by 1

On the map: Retrieval-augmented generation → Generation and context integration

Abstract (arXiv)

Open-domain semantic parsing remains a challenging task, as neural models often rely on heuristics and struggle to handle unseen concepts. In this paper, we investigate the potential of large language models (LLMs) for this task and introduce Retrieval-Augmented Semantic Parsing (RASP), a simple yet effective approach that integrates external symbolic knowledge into the parsing process. Our experiments not only show that LLMs outperform previous encoder-decoder baselines for semantic parsing, but that RASP further enhances their ability to predict unseen concepts, nearly doubling the performance of previous models on out-of-distribution concepts. These findings highlight the promise of leveraging large language models and retrieval mechanisms for robust and open-domain semantic parsing.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Generation and context integration, one of 15 directions in Retrieval-augmented generation. Builds on 31 of its 60 references that are in the map. First posted on arXiv 13 Dec 2024.

Builds on

31 of 60 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Models5 Aug
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks22 May
  3. 2020REALM: Retrieval-Augmented Language Model Pre-Training10 Feb

Other references · 28

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  3. 2021Improving language models by retrieving from trillions of tokenscited by 1,278
  4. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  5. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,065
  6. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 352
  7. 2020How Context Affects Language Models' Factual Predictionscited by 181
  8. 2020KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoningcited by 106
  9. 2023UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluationcited by 74
  10. 2024What Evidence Do Language Models Find Convincing?cited by 74
  11. 2022Graph Pre-training for AMR Parsing and Generationcited by 55
  12. 2017The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representationscited by 41
16 more
  1. 2021AMR Parsing with Action-Pointer Transformercited by 25
  2. 2023Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Datacited by 23
  3. 2020AMR Similarity Metrics from Principlescited by 21
  4. 2023Prompt-Guided Retrieval Augmentation for Non-Knowledge-Intensive Taskscited by 21
  5. 2017Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representationscited by 18
  6. 2023"You Are An Expert Linguistic Annotator": Limits of LLMs as Analyzers of Abstract Meaning Representationcited by 15
  7. 2018Exploring Neural Methods for Parsing Discourse Representation Structurescited by 14
  8. 2020'UFAL at MRP 2020: Permutation-invariant Semantic Parsing in PERINcited by 12
  9. 2022BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsingcited by 12
  10. 2024Analyzing the Role of Semantic Representations in the Era of Large Language Modelscited by 12
  11. 2016RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracycited by 11
  12. 2023Pre-Trained Language-Meaning Models for Multilingual Parsing and Generationcited by 9
  13. 2024Neural Semantic Parsing with Extremely Rich Symbolic Meaning Representationscited by 5
  14. 2023Discourse Representation Structure Parsing for Chinesecited by 3
  15. 2024MACT: Model-Agnostic Cross-Lingual Training for Discourse Representation Structure Parsingcited by 3
  16. 2024Scope-enhanced Compositional Semantic Parsing for DRTcited by 2

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Citing papers per year: 2025: 1.

1 paper.

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