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Related papers: Group Theory and Grammatical Description

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The paper presents a linguistic and computational model aiming at making the morphological structure of the lexicon emerge from the formal and semantic regularities of the words it contains. The model is word-based. The proposed…

Computation and Language · Computer Science 2009-05-12 Nabil Hathout

In the principles-and-parameters framework, the structural features of languages depend on parameters that may be toggled on or off, with a single parameter often dictating the status of multiple features. The implied covariance between…

Computation and Language · Computer Science 2019-05-16 Johannes Bjerva , Yova Kementchedjhieva , Ryan Cotterell , Isabelle Augenstein

Semantic theories of natural language associate meanings with utterances by providing meanings for lexical items and rules for determining the meaning of larger units given the meanings of their parts. Meanings are often assumed to combine…

cmp-lg · Computer Science 2008-02-03 Mary Dalrymple , John Lamping , Fernando Pereira , Vijay Saraswat

Lexical semantics theories differ in advocating that the meaning of words is represented as an inference graph, a feature mapping or a vector space, thus raising the question: is it the case that one of these approaches is superior to the…

Computation and Language · Computer Science 2020-11-17 António Branco , João Rodrigues , Małgorzata Salawa , Ruben Branco , Chakaveh Saedi

A structural time series model additively decomposes into generative, semantically-meaningful components, each of which depends on a vector of parameters. We demonstrate that considering each generative component together with its vector of…

Methodology · Statistics 2020-09-16 David Rushing Dewhurst

Multilinear Grammar provides a framework for integrating the many different syntagmatic structures of language into a coherent semiotically based Rank Interpretation Architecture, with default linear grammars at each rank. The architecture…

Computation and Language · Computer Science 2017-09-18 Dafydd Gibbon , Sascha Griffiths

Grounded language models use external sources of information, such as knowledge graphs, to meet some of the general challenges associated with pre-training. By extending previous work on compositional generalization in semantic parsing, we…

Computation and Language · Computer Science 2024-06-10 Sondre Wold , Étienne Simon , Lucas Georges Gabriel Charpentier , Egor V. Kostylev , Erik Velldal , Lilja Øvrelid

We propose a categorial grammar based on classical multiplicative linear logic. This can be seen as an extension of abstract categorial grammars (ACG) and is at least as expressive. However, constituents of {\it linear logic grammars (LLG)}…

Logic in Computer Science · Computer Science 2019-02-12 Sergey Slavnov

This technical report presents a general framework for parsing a variety of grammar formalisms. We develop a grammar formalism, called an Abstract Grammar, which is general enough to represent grammars at many levels of the hierarchy,…

Computation and Language · Computer Science 2018-01-22 Daniel Harasim , Chris Bruno , Eva Portelance , Martin Rohrmeier , Timothy J. O'Donnell

Whether language models (LMs) have inductive biases that favor typologically frequent grammatical properties over rare, implausible ones has been investigated, typically using artificial languages (ALs) (White and Cotterell, 2021;…

Computation and Language · Computer Science 2025-10-15 Nadine El-Naggar , Tatsuki Kuribayashi , Ted Briscoe

In this work we define formal grammars in terms of free monoidal categories, along with a functor from the category of formal grammars to the category of automata. Generalising from the Booleans to arbitrary semirings, we extend our…

Formal Languages and Automata Theory · Computer Science 2020-01-13 Dan Shiebler , Alexis Toumi , Mehrnoosh Sadrzadeh

Representing and exploiting multivariate signals requires capturing relations between variables, which we can represent by graphs. Graph dictionaries allow to describe complex relational information as a sparse sum of simpler structures,…

Machine Learning · Computer Science 2026-01-09 William Cappelletti , Pascal Frossard

We present a dataset for evaluating the grammaticality of the predictions of a language model. We automatically construct a large number of minimally different pairs of English sentences, each consisting of a grammatical and an…

Computation and Language · Computer Science 2018-08-29 Rebecca Marvin , Tal Linzen

This article describes the design of a common syntactic description for the core grammar of a group of related dialects. The common description does not rely on an abstract sub-linguistic structure like a metagrammar: it consists in a…

Computation and Language · Computer Science 2008-10-08 Pascal Vaillant

Applied category theory has recently developed libraries for computing with morphisms in interesting categories, while machine learning has developed ways of learning programs in interesting languages. Taking the analogy between categories…

Artificial Intelligence · Computer Science 2022-05-17 Eli Sennesh , Tom Xu , Yoshihiro Maruyama

In this dissertation we develop a new formal graphical framework for causal reasoning. Starting with a review of monoidal categories and their associated graphical languages, we then revisit probability theory from a categorical perspective…

Probability · Mathematics 2013-01-29 Brendan Fong

I introduce a formalism for representing the syntax of recursively structured graph-like patterns. It does not use production rules, like a conventional graph grammar, but represents the syntactic structure in a more direct and declarative…

Formal Languages and Automata Theory · Computer Science 2025-04-25 Peter Fletcher

We describe a type system for the linear-algebraic lambda-calculus. The type system accounts for the part of the language emulating linear operators and vectors, i.e. it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2012-08-01 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

This paper is about pregroup models of natural languages, and how they relate to the explicitly categorical use of pregroups in Compositional Distributional Semantics and Natural Language Processing. These categorical interpretations make…

Computation and Language · Computer Science 2018-11-09 Peter M. Hines

We introduce Transformer Grammars (TGs), a novel class of Transformer language models that combine (i) the expressive power, scalability, and strong performance of Transformers and (ii) recursive syntactic compositions, which here are…

Computation and Language · Computer Science 2022-12-07 Laurent Sartran , Samuel Barrett , Adhiguna Kuncoro , Miloš Stanojević , Phil Blunsom , Chris Dyer