mlsanityData to 7 Oct 2026

From Partial to Strictly Incremental Constituent Parsing

arXiv 2402.02782 ↗First posted 5 Feb 2024cs.CLcited by 1

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Abstract (arXiv)

We study incremental constituent parsers to assess their capacity to output trees based on prefix representations alone. Guided by strictly left-to-right generative language models and tree-decoding modules, we build parsers that adhere to a strong definition of incrementality across languages. This builds upon work that asserted incrementality, but that mostly only enforced it on either the encoder or the decoder. Finally, we conduct an analysis against non-incremental and partially incremental models.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 19 of its 35 references that are in the map. First posted on arXiv 5 Feb 2024.

Builds on

19 of 35 references.

References · 19

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,416
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  5. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
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  7. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
  8. 2016Deep Biaffine Attention for Neural Dependency Parsingcited by 334
  9. 2018Constituency Parsing with a Self-Attentive Encodercited by 196
  10. 2022mGPT: Few-Shot Learners Go Multilingualcited by 141
  11. 2018Constituent Parsing as Sequence Labelingcited by 26
  12. 2020Strongly Incremental Constituency Parsing with Graph Neural Networkscited by 23
7 more
  1. 2019Tetra-Tagging: Word-Synchronous Parsing with Linear-Time Inferencecited by 17
  2. 2020Incremental Processing in the Age of Non-Incremental Encoders: An Empirical Assessment of Bidirectional Models for Incremental NLUcited by 13
  3. 2020Discontinuous Constituent Parsing as Sequence Labelingcited by 9
  4. 2018Incremental Natural Language Processing: Challenges, Strategies, and Evaluationcited by 8
  5. 2020Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oraclecited by 5
  6. 2023On the Challenges of Fully Incremental Neural Dependency Parsingcited by 2
  7. 2016Incremental Parsing with Minimal Features Using Bi-Directional LSTMcited by 1

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Citing papers per year: 2025: 1.

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  1. 2025Bringing Emerging Architectures to Sequence Labeling in NLPcited by 1