mlsanityData to 7 Oct 2026

CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing

arXiv 2210.07074 ↗First posted 13 Oct 2022cs.CL cs.AI cs.LGcited by 21

Not on the map. Why?

Abstract (arXiv)

A bottleneck to developing Semantic Parsing (SP) models is the need for a large volume of human-labeled training data. Given the complexity and cost of human annotation for SP, labeled data is often scarce, particularly in multilingual settings. Large Language Models (LLMs) excel at SP given only a few examples, however LLMs are unsuitable for runtime systems which require low latency. In this work, we propose CLASP, a simple method to improve low-resource SP for moderate-sized models: we generate synthetic data from AlexaTM 20B to augment the training set for a model 40x smaller (500M parameters). We evaluate on two datasets in low-resource settings: English PIZZA, containing either 348 or 16 real examples, and mTOP cross-lingual zero-shot, where training data is available only in English, and the model must generalize to four new languages. On both datasets, we show significant improvements over strong baseline methods.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 26 of its 49 references that are in the map. First posted on arXiv 13 Oct 2022.

Builds on

26 of 49 references.

References · 26

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  4. 2020Language Models are Few-Shot Learnerscited by 32,199
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  6. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  7. 2019The Curious Case of Neural Text Degenerationcited by 2,881
  8. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,973
  9. 2018Hierarchical Neural Story Generationcited by 1,182
  10. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,028
  11. 2021Generating Datasets with Pretrained Language Modelscited by 192
  12. 2021Constrained Language Models Yield Few-Shot Semantic Parserscited by 162
14 more
  1. 2019Good-Enough Compositional Data Augmentationcited by 158
  2. 2020MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmarkcited by 156
  3. 2020SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddingscited by 155
  4. 2016Data Recombination for Neural Semantic Parsingcited by 111
  5. 2021Towards Zero-Label Language Learningcited by 76
  6. 2020Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsingcited by 59
  7. 2022AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Modelcited by 57
  8. 2020Cross-lingual Retrieval for Iterative Self-Supervised Trainingcited by 54
  9. 2021Neural Data Augmentation via Example Extrapolationcited by 54
  10. 2022Data Augmentation for Intent Classification with Off-the-shelf Large Language Modelscited by 49
  11. 2022LINGUIST: Language Model Instruction Tuning to Generate Annotated Utterances for Intent Classification and Slot Taggingcited by 29
  12. 2022Transforming Sequence Tagging Into A Seq2Seq Taskcited by 15
  13. 2022Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentationcited by 7
  14. 2022Training Naturalized Semantic Parsers with Very Little Datacited by 6

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 9; 2024: 9; 2025: 2.

21 papers.

Sort:

By area:

  1. 2023PLACES: Prompting Language Models for Social Conversation Synthesiscited by 72
  2. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  3. 2023FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answeringcited by 51
  4. 2024Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontierscited by 49
  5. 2023Generating Data for Symbolic Language with Large Language Modelscited by 12
  6. 2024LegalLens: Leveraging LLMs for Legal Violation Identification in Unstructured Textcited by 12
  7. 2022Tokenization Consistency Matters for Generative Models on Extractive NLP Taskscited by 7
  8. 2023Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Modelscited by 7
  9. 2024Grounding Data Science Code Generation with Input-Output Specificationscited by 7
  10. 2024Controllable and Diverse Data Augmentation with Large Language Model for Low-Resource Open-Domain Dialogue Generationcited by 4
  11. 2023Learning Translation Quality Evaluation on Low Resource Languages from Large Language Modelscited by 2
  12. 2023Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsingcited by 2
9 more
  1. 2024TransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Textcited by 2
  2. 2023Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Modelscited by 1
  3. 2023Vicinal Risk Minimization for Few-Shot Cross-lingual Transfer in Abusive Language Detectioncited by 1
  4. 2025SpeechDialogueFactory: Generating High-Quality Speech Dialogue Data to Accelerate Your Speech-LLM Developmentcited by 1
  5. 2025NL2GenSym: Natural Language to Generative Symbolic Rules for SOAR Cognitive Architecture via Large Language Modelscited by 1
  6. 2023(Vector) Space is Not the Final Frontier: Product Search as Program Synthesiscited by 0
  7. 2024Better Python Programming for all: With the focus on Maintainabilitycited by 0
  8. 2024Cross-lingual Back-Parsing: Utterance Synthesis from Meaning Representation for Zero-Resource Semantic Parsingcited by 0
  9. 2024CALICO: Conversational Agent Localization via Synthetic Data Generationcited by 0