Constituency Grammar Induction

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

5 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

20 shown of 20 papers with code (22 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
  22 Oct 2018 7 repositories listed Syntology ran 3 of 12 samples · 9 unverified
  When a larger constituent ends, all of the smaller constituents that are nested within it must also be closed.
• Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at Scale
  13 Mar 2024 2 repositories listed Syntology ran 4 of 7 samples · 3 unverified
  A syntactic language model (SLM) incrementally generates a sentence with its syntactic tree in a left-to-right manner.
• Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs
  1 May 2022 2 repositories listed
  Recent research found it beneficial to use large state spaces for HMMs and PCFGs.
• Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text Representation
  1 Mar 2022 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We propose to use a top-down parser as a model-based pruning method, which also enables parallel encoding during inference.
• Compound Probabilistic Context-Free Grammars for Grammar Induction
  24 Jun 2019 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  We study a formalization of the grammar induction problem that models sentences as being generated by a compound probabilistic context-free grammar.
• On Eliciting Syntax from Language Models via Hashing
  5 Oct 2024 1 repository listed
  Unsupervised parsing, also known as grammar induction, aims to infer syntactic structure from raw text.
• Improving Unsupervised Constituency Parsing via Maximizing Semantic Information
  3 Oct 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we introduce a novel objective for training unsupervised parsers: maximizing the information between constituent structures and sentence semantics (SemInfo).
• Structural Optimization Ambiguity and Simplicity Bias in Unsupervised Neural Grammar Induction
  23 Jul 2024 1 repository listed
  Neural parameterization has significantly advanced unsupervised grammar induction.
• Simple Hardware-Efficient PCFGs with Independent Left and Right Productions
  23 Oct 2023 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Scaling dense PCFGs to thousands of nonterminals via a low-rank parameterization of the rule probability tensor has been shown to be beneficial for unsupervised parsing.
• Ensemble Distillation for Unsupervised Constituency Parsing
  3 Oct 2023 1 repository listed Syntology ran 16 of 22 samples · 6 unverified · 22 pointer-only (licence)
  We investigate the unsupervised constituency parsing task, which organizes words and phrases of a sentence into a hierarchical structure without using linguistically annotated data.
• Augmenting Transformers with Recursively Composed Multi-grained Representations
  28 Sep 2023 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  More interestingly, the hierarchical structures induced by ReCAT exhibit strong consistency with human-annotated syntactic trees, indicating good interpretability brought by the CIO layers.
• Co-training an Unsupervised Constituency Parser with Weak Supervision
  5 Oct 2021 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 1 pointer-only (licence)
  We introduce a method for unsupervised parsing that relies on bootstrapping classifiers to identify if a node dominates a specific span in a sentence.
• Dependency Induction Through the Lens of Visual Perception
  20 Sep 2021 1 repository listed
  Our experiments find that concreteness is a strong indicator for learning dependency grammars, improving the direct attachment score (DAS) by over 50\% as compared to state-of-the-art models trained on pure text.
• Neural Bi-Lexicalized PCFG Induction
  31 May 2021 1 repository listed
  Neural lexicalized PCFGs (L-PCFGs) have been shown effective in grammar induction.
• PCFGs Can Do Better: Inducing Probabilistic Context-Free Grammars with Many Symbols
  28 Apr 2021 1 repository listed
  In this work, we present a new parameterization form of PCFGs based on tensor decomposition, which has at most quadratic computational complexity in the symbol number and therefore allows us to use a much larger number…
• Visually Grounded Compound PCFGs
  25 Sep 2020 1 repository listed
  In this work, we study visually grounded grammar induction and learn a constituency parser from both unlabeled text and its visual groundings.
• Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Auto-Encoders
  1 Jun 2019 1 repository listed
  We introduce the deep inside-outside recursive autoencoder (DIORA), a fully-unsupervised method for discovering syntax that simultaneously learns representations for constituents within the induced tree.
• Unsupervised Recurrent Neural Network Grammars
  7 Apr 2019 1 repository listed
  On language modeling, unsupervised RNNGs perform as well their supervised counterparts on benchmarks in English and Chinese.
• Unsupervised Learning of Syntactic Structure with Invertible Neural Projections
  28 Aug 2018 1 repository listed
  In this work, we propose a novel generative model that jointly learns discrete syntactic structure and continuous word representations in an unsupervised fashion by cascading an invertible neural network with a…
• Neural Language Modeling by Jointly Learning Syntax and Lexicon
  2 Nov 2017 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  In this paper, We propose a novel neural language model, called the Parsing-Reading-Predict Networks (PRPN), that can simultaneously induce the syntactic structure from unannotated sentences and leverage the inferred…

Syntology lines on 10 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.