4 and 7-bit Labeling for Projective and Non-Projective Dependency Trees
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Abstract (arXiv)
We introduce an encoding for parsing as sequence labeling that can represent any projective dependency tree as a sequence of 4-bit labels, one per word. The bits in each word's label represent (1) whether it is a right or left dependent, (2) whether it is the outermost (left/right) dependent of its parent, (3) whether it has any left children and (4) whether it has any right children. We show that this provides an injective mapping from trees to labels that can be encoded and decoded in linear time. We then define a 7-bit extension that represents an extra plane of arcs, extending the coverage to almost full non-projectivity (over 99.9% empirical arc coverage). Results on a set of diverse treebanks show that our 7-bit encoding obtains substantial accuracy gains over the previously best-performing sequence labeling encodings.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 12 of its 27 references that are in the map. First posted on arXiv 22 Oct 2023.
Builds on
12 of 27 references.
References · 12
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
- 2020Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLPcited by 50
- 2019Viable Dependency Parsing as Sequence Labelingcited by 34
- 2018Constituent Parsing as Sequence Labelingcited by 26
- 2019Tetra-Tagging: Word-Synchronous Parsing with Linear-Time Inferencecited by 17
- 2020Bracketing Encodings for 2-Planar Dependency Parsingcited by 15
- 2020A Unifying Theory of Transition-based and Sequence Labeling Parsingcited by 12
- 2019How to best use Syntax in Semantic Role Labellingcited by 11
- 2021A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021cited by 9
- 2021Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsingcited by 7
- 2020Distilling Neural Networks for Greener and Faster Dependency Parsingcited by 5
- 2021A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsingcited by 5
Built on by
Citing papers per year: 2024: 3; 2025: 4; 2026: 1.
8 papers.
- 2024A Syntax-Injected Approach for Faster and More Accurate Sentiment Analysiscited by 2
- 2024Dancing in the syntax forest: fast, accurate and explainable sentiment analysis with SALSAcited by 2
- 2024Dependency Graph Parsing as Sequence Labelingcited by 2
- 2025Hierarchical Bracketing Encodings for Dependency Parsing as Taggingcited by 1
- 2025Bringing Emerging Architectures to Sequence Labeling in NLPcited by 1
- 2025Hierarchical Bracketing Encodings Work for Dependency Graphscited by 0
- 2025Translation via Annotation: A Computational Study of Translating Classical Chinese into Japanesecited by 0
- 2026Formal Constraints on Dependency Syntaxcited by 0
- 2026Formal Constraints on Dependency Syntax6 Apr 2026
- 2025Translation via Annotation: A Computational Study of Translating Classical Chinese into Japanese7 Nov 2025
- 2025Bringing Emerging Architectures to Sequence Labeling in NLP30 Sep 2025
- 2025Hierarchical Bracketing Encodings Work for Dependency Graphs11 Sep 2025
- 2025Hierarchical Bracketing Encodings for Dependency Parsing as Tagging16 May 2025
- 2024Dependency Graph Parsing as Sequence Labeling23 Oct 2024
- 2024Dancing in the syntax forest: fast, accurate and explainable sentiment analysis with SALSA23 Jun 2024
- 2024A Syntax-Injected Approach for Faster and More Accurate Sentiment Analysis21 Jun 2024
Similar, not cited
Close in wording, no citation either way
- 2026The Communication Bottleneck: A Round-Trip Study of Tree-Structured Expression Serialization in Language Models
- 2022Probing for Labeled Dependency Trees
- 2025TreeGPT: Pure TreeFFN Encoder-Decoder Architecture for Structured Reasoning Without Attention Mechanisms
- 2021R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling
- 2026Directional Contextual Representations for Dependency Relations: Why Cross-Direction Pairing Fails
- 2024Hitting "Probe"rty with Non-Linearity, and More
- 2026Chain-of-Thought Shows the Path to a Tree: Realizing Branching Complexity
- 2026DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models