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This thesis contributes to ongoing research related to the categorical compositional model for natural language of Coecke, Sadrzadeh and Clark in three ways: Firstly, I propose a concrete instantiation of the abstract framework based on…

Computation and Language · Computer Science 2015-05-04 Dimitri Kartsaklis

We introduce a novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations. The power of the model lies in its ability…

Information Retrieval · Computer Science 2016-08-26 Christophe Van Gysel , Maarten de Rijke , Evangelos Kanoulas

Behaviors of many engineering systems are described by lumped parameter models that encapsulate the spatially distributed nature of the system into networks of lumped elements; the dynamics of such a network is governed by a system of…

Systems and Control · Computer Science 2019-12-04 Randi Wang , Vadim Shapiro

We enrich the Lambek calculus with the cyclic shift operation, which is expected to model the closure operator of formal languages with respect to cyclic shifts. We introduce a Gentzen-style calculus and prove cut elimination. Secondly, we…

Logic · Mathematics 2021-11-09 Tikhon Pshenitsyn

Recent work exhibited that distributed word representations are good at capturing linguistic regularities in language. This allows vector-oriented reasoning based on simple linear algebra between words. Since many different methods have…

Computation and Language · Computer Science 2016-03-25 Fei Sun , Jiafeng Guo , Yanyan Lan , Jun Xu , Xueqi Cheng

The displacement calculus $\mathbf{D}$ is a conservative extension of the Lambek calculus $\mathbf{L1}$ (with empty antecedents allowed in sequents). $\mathbf{L1}$ can be said to be the logic of concatenation, while $\mathbf{D}$ can be said…

Logic in Computer Science · Computer Science 2017-06-13 Oriol Valentín

This paper studies formulations of second-order elliptic partial differential equations in nondivergence form on convex domains as equivalent variational problems. The first formulation is that of Smears \& S\"uli [SIAM J.\ Numer.\ Anal.\…

Numerical Analysis · Mathematics 2017-01-17 Dietmar Gallistl

Despite the recent successes of deep learning in natural language processing (NLP), there remains widespread usage of and demand for techniques that do not rely on machine learning. The advantage of these techniques is their…

Computation and Language · Computer Science 2020-12-04 Adam Hare , Yu Chen , Yinan Liu , Zhenming Liu , Christopher G. Brinton

We introduce a sequent calculus with a simple restriction of Lambek's product rules that precisely captures the classical Tamari order, i.e., the partial order on fully-bracketed words (equivalently, binary trees) induced by a…

Logic in Computer Science · Computer Science 2017-01-12 Noam Zeilberger

Abstract separation logics are a family of extensions of Hoare logic for reasoning about programs that manipulate resources such as memory locations. These logics are "abstract" because they are independent of any particular concrete…

Logic in Computer Science · Computer Science 2018-03-28 Zhé Hóu , Ranald Clouston , Rajeev Goré , Alwen Tiu

The human ability to flexibly reason using analogies with domain-general content depends on mechanisms for identifying relations between concepts, and for mapping concepts and their relations across analogs. Building on a recent model of…

Artificial Intelligence · Computer Science 2021-10-06 Hongjing Lu , Nicholas Ichien , Keith J. Holyoak

It is known that different categorial grammars have surface representation in a fragment of first order multiplicative linear logic (MLL1). We show that the fragment of interest is equivalent to the recently introduced extended tensor type…

Computation and Language · Computer Science 2024-02-14 Sergey Slavnov

We investigate compositional structures in data embeddings from pre-trained vision-language models (VLMs). Traditionally, compositionality has been associated with algebraic operations on embeddings of words from a pre-existing vocabulary.…

Machine Learning · Computer Science 2024-01-12 Matthew Trager , Pramuditha Perera , Luca Zancato , Alessandro Achille , Parminder Bhatia , Stefano Soatto

We address the problem of identifying a proof-theoretic framework that enables a compositional analysis of finite-trace properties in concurrent systems, with a particular focus on those specified via prefix-closure. To this end, we…

Logic in Computer Science · Computer Science 2025-12-08 Ludovico Fusco , Alessandro Aldini

Compounding is a highly productive word-formation process in some languages that is often problematic for natural language processing applications. In this paper, we investigate whether distributional semantics in the form of word…

Computation and Language · Computer Science 2015-09-16 Joachim Daiber , Lautaro Quiroz , Roger Wechsler , Stella Frank

We investigate a class of nominal algebraic Henkin-style models for the simply typed lambda-calculus in which variables map to names in the denotation and lambda-abstraction maps to a (non-functional) name-abstraction operation. The…

Logic in Computer Science · Computer Science 2011-11-02 Murdoch J. Gabbay , Dominic P. Mulligan

Distributional semantic models provide vector representations for words by gathering co-occurrence frequencies from corpora of text. Compositional distributional models extend these from words to phrases and sentences. In categorical…

Computation and Language · Computer Science 2018-10-10 Esma Balkir , Dimitri Kartsaklis , Mehrnoosh Sadrzadeh

We describe a type system for the linear-algebraic $\lambda$-calculus. The type system accounts for the linear-algebraic aspects of this extension of $\lambda$-calculus: it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2017-05-12 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

Despite significant progress in transformer interpretability, an understanding of the computational mechanisms of large language models (LLMs) remains a fundamental challenge. Many approaches interpret a network's hidden representations but…

Machine Learning · Computer Science 2025-10-14 James R. Golden

Embedding learning, a.k.a. representation learning, has been shown to be able to model large-scale semantic knowledge graphs. A key concept is a mapping of the knowledge graph to a tensor representation whose entries are predicted by models…

Artificial Intelligence · Computer Science 2016-05-10 Volker Tresp , Cristóbal Esteban , Yinchong Yang , Stephan Baier , Denis Krompaß