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This paper presents a Semantic Attribute Modulation (SAM) for language modeling and style variation. The semantic attribute modulation includes various document attributes, such as titles, authors, and document categories. We consider two…

Computation and Language · Computer Science 2017-09-15 Wenbo Hu , Lifeng Hua , Lei Li , Hang Su , Tian Wang , Ning Chen , Bo Zhang

We introduce a notion of compatibility between constraint encoding and compositional structure. Phrased in the language of category theory, it is given by a "composable constraint encoding". We show that every composable constraint encoding…

Category Theory · Mathematics 2021-12-14 Matt Wilson , Augustin Vanrietvelde

Generating logical form equivalents of human language is a fresh way to employ neural architectures where long short-term memory effectively captures dependencies in both encoder and decoder units. The logical form of the sequence usually…

Machine Learning · Computer Science 2018-07-20 Javid Dadashkarimi , Sekhar Tatikonda

Symmetry arguments are frequently used -- often implicitly -- in mathematical modeling of natural selection. Symmetry simplifies the analysis of models and reduces the number of distinct population states to be considered. Here, I introduce…

Populations and Evolution · Quantitative Biology 2023-07-14 Benjamin Allen

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

This work proposes Adaptive Facilitated Mutation, a self-adaptive mutation method for Structured Grammatical Evolution (SGE), biologically inspired by the theory of facilitated variation. In SGE, the genotype of individuals contains a list…

Neural and Evolutionary Computing · Computer Science 2023-03-31 Pedro Carvalho , Jessica Mégane , Nuno Lourenço , Penousal Machado

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

Marginal models involve restrictions on the conditional and marginal association structure of a set of categorical variables. They generalize log-linear models for contingency tables, which are the fundamental tools for modelling the…

Methodology · Statistics 2023-04-10 Tamas Rudas , Wicher Bergsma

This paper introduces how human languages can be studied in light of recent development of network theories. There are two directions of exploration. One is to study networks existing in the language system. Various lexical networks can be…

Computation and Language · Computer Science 2007-05-23 Jinyun KE

We investigate the possibility of modelling the syntax and semantics of natural language by constraints, or rules, imposed by the multi-dimensional type theory Nabla. The only multiplicity we explicitly consider is two, namely one dimension…

Computation and Language · Computer Science 2007-05-23 Jørgen Villadsen

Large Language Models (LLMs) are transforming language sciences. However, their widespread deployment currently suffers from methodological fragmentation and a lack of systematic soundness. This study proposes two comprehensive…

Computation and Language · Computer Science 2025-12-11 Kun Sun , Rong Wang

Ontologies and taxonomies of research fields are critical for managing and organising scientific knowledge, as they facilitate efficient classification, dissemination and retrieval of information. However, the creation and maintenance of…

Digital Libraries · Computer Science 2025-08-29 Tanay Aggarwal , Angelo Salatino , Francesco Osborne , Enrico Motta

In this paper, we present an approach to define the semantics for object-oriented modeling languages. One important property of this semantics is to support underspecified and incomplete models. To this end, semantics is given as predicates…

Software Engineering · Computer Science 2014-09-24 Hans Grönninger , Jan Oliver Ringert , Bernhard Rumpe

A good feature representation is a determinant factor to achieve high performance for many machine learning algorithms in terms of classification. This is especially true for techniques that do not build complex internal representations of…

Neural and Evolutionary Computing · Computer Science 2019-08-22 Noëlie Cherrier , Jean-Philippe Poli , Maxime Defurne , Franck Sabatié

The semantics used for particular terms in an academic field organically evolve over time. Tracking this evolution through inspection of published literature has either been from the perspective of Linguistic scholars or has concentrated…

Information Retrieval · Computer Science 2023-10-20 Hyung Wook Choi , Mat Kelly

Theory revision integrates inductive learning and background knowledge by combining training examples with a coarse domain theory to produce a more accurate theory. There are two challenges that theory revision and other theory-guided…

Artificial Intelligence · Computer Science 2008-02-03 S. K. Donoho , L. A. Rendell

Ontologies enable knowledge sharing and interdisciplinary collaboration by providing standardized, structured vocabularies for diverse communities. While logical axioms are a cornerstone of ontology design, natural language elements such as…

Formal Languages and Automata Theory · Computer Science 2025-08-29 Paul Fabry , Adrien Barton , Jean-François Éthier

Category theory gives a mathematical characterization of naturality but not of canonicity. The purpose of this paper is to develop the logical theory of canonical maps based on the broader demonstration that the dual notions of elements &…

Category Theory · Mathematics 2024-10-07 David Ellerman

We introduce a model for simulating mutation of prokaryote DNA sequences. Using that model we can then evaluated traditional techniques like parsimony and maximum likelihood methods for computing phylogenetic relationships. We also use the…

Populations and Evolution · Quantitative Biology 2007-05-23 Matthew J. Berryman , Andrew Allison , Derek Abbott

This paper surveys foundation models for AI-enabled biological design, focusing on recent developments in applying large-scale, self-supervised models to tasks such as protein engineering, small molecule design, and genomic sequence design.…

Artificial Intelligence · Computer Science 2025-05-20 Asher Moldwin , Amarda Shehu