mlsanityData to 7 Oct 2026

Grammar as a Foreign Language

arXiv 1412.7449 ↗First posted 23 Dec 2014cs.CL cs.LG stat.MLcited by 70

Not on the map. Why?

Abstract (arXiv)

Syntactic constituency parsing is a fundamental problem in natural language processing and has been the subject of intensive research and engineering for decades. As a result, the most accurate parsers are domain specific, complex, and inefficient. In this paper we show that the domain agnostic attention-enhanced sequence-to-sequence model achieves state-of-the-art results on the most widely used syntactic constituency parsing dataset, when trained on a large synthetic corpus that was annotated using existing parsers. It also matches the performance of standard parsers when trained only on a small human-annotated dataset, which shows that this model is highly data-efficient, in contrast to sequence-to-sequence models without the attention mechanism. Our parser is also fast, processing over a hundred sentences per second with an unoptimized CPU implementation.

Key facts. Cited by 70 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Dec 2014.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 25; 2022: 14; 2023: 15; 2024: 7; 2025: 5; 2026: 4.

70 papers.

Sort:

By area:

  1. 2021Pix2seq: A Language Modeling Framework for Object Detectioncited by 345
  2. 2023Grammar-Constrained Decoding for Structured NLP Tasks without Finetuningcited by 186
  3. 2021Structured Prediction as Translation between Augmented Natural Languagescited by 183
  4. 2021Episodic Transformer for Vision-and-Language Navigationcited by 155
  5. 2021Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extractioncited by 129
  6. 2021How to represent part-whole hierarchies in a neural networkcited by 123
  7. 2023DyVal: Dynamic Evaluation of Large Language Models for Reasoning Taskscited by 100
  8. 2021Attention, please! A survey of Neural Attention Models in Deep Learningcited by 50
  9. 2022Autoregressive Structured Prediction with Language Modelscited by 43
  10. 2022Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scalecited by 40
  11. 2021Paradigm Shift in Natural Language Processingcited by 39
  12. 2021Maximum Bayes Smatch Ensemble Distillation for AMR Parsingcited by 27
38 more
  1. 2021Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsingcited by 25
  2. 2021Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interactioncited by 21
  3. 2021Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networkscited by 21
  4. 2021Solving Aspect Category Sentiment Analysis as a Text Generation Taskcited by 21
  5. 2023Pushdown Layers: Encoding Recursive Structure in Transformer Language Modelscited by 18
  6. 2021Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networkscited by 16
  7. 2022Constrained Sequence-to-Tree Generation for Hierarchical Text Classificationcited by 13
  8. 2022SVD-PINNs: Transfer Learning of Physics-Informed Neural Networks via Singular Value Decompositioncited by 13
  9. 2022BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsingcited by 12
  10. 2023Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generationcited by 10
  11. 2024Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at Scalecited by 9
  12. 2021El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsingcited by 8
  13. 2021A Conditional Splitting Framework for Efficient Constituency Parsingcited by 7
  14. 2024Deep Autoregressive Models as Causal Inference Enginescited by 6
  15. 2021The Limitations of Limited Context for Constituency Parsingcited by 5
  16. 2023HPE:Answering Complex Questions over Text by Hybrid Question Parsing and Executioncited by 5
  17. 2023User-Aware Prefix-Tuning is a Good Learner for Personalized Image Captioningcited by 5
  18. 2021Discontinuous Grammar as a Foreign Languagecited by 4
  19. 2025Self-Correction Makes LLMs Better Parserscited by 4
  20. 2023Approximating CKY with Transformerscited by 3
  21. 2023Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systemscited by 3
  22. 2021Generating CCG Categoriescited by 2
  23. 2022When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systemscited by 2
  24. 2023On graph-based reentrancy-free semantic parsingcited by 2
  25. 2023On the Challenges of Fully Incremental Neural Dependency Parsingcited by 2
  26. 2023Constituency Parsing using LLMscited by 2
  27. 2025Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMscited by 2
  28. 2021In-Order Chart-Based Constituent Parsingcited by 1
  29. 2021Neural Combinatory Constituency Parsingcited by 1
  30. 2021Generating Diverse Descriptions from Semantic Graphscited by 1
  31. 2021Revisiting Tri-training of Dependency Parserscited by 1
  32. 2021Towards More Efficient Insertion Transformer with Fractional Positional Encodingcited by 1
  33. 2022GROOT: Corrective Reward Optimization for Generative Sequential Labelingcited by 1
  34. 2022Dense Paraphrasing for Textual Enrichmentcited by 1
  35. 2022An Overview on Controllable Text Generation via Variational Auto-Encoderscited by 1
  36. 2022Fast Rule-Based Decoding: Revisiting Syntactic Rules in Neural Constituency Parsingcited by 1
  37. 2022How Does Beam Search improve Span-Level Confidence Estimation in Generative Sequence Labeling?cited by 1
  38. 2023Unleashing the True Potential of Sequence-to-Sequence Models for Sequence Tagging and Structure Parsingcited by 1

50 most cited of 70 All 70 (JSON)