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All languages have a noun category, but its realisation varies considerably. Depending on the language, semantic and/or morphosyntactic differences may be more or less pronounced. This paper explores these variations, using Riffian as a…

Computation and Language · Computer Science 2026-04-07 Mohamed El Idrissi

Sequence theories are an extension of theories of strings with an infinite alphabet of letters, together with a corresponding alphabet theory (e.g. linear integer arithmetic). Sequences are natural abstractions of extendable arrays, which…

Logic in Computer Science · Computer Science 2023-08-02 Artur Jeż , Anthony W. Lin , Oliver Markgraf , Philipp Rümmer

Representation learning plays a central role in structuring internal embeddings to capture the statistical properties of language, influencing the coherence and contextual consistency of generated text. Statistical Coherence Alignment is…

Computation and Language · Computer Science 2025-08-11 Jonathan Gale , Godfrey Aldington , Harriet Thistlewood , Thomas Tattershall , Basil Wentworth , Vincent Enoasmo

Despite the success of neural models in solving reasoning tasks, their compositional generalization capabilities remain unclear. In this work, we propose a new setting of the structured explanation generation task to facilitate…

Computation and Language · Computer Science 2023-09-15 Xiyan Fu , Anette Frank

This thesis investigates how the sub-structure of words can be accounted for in probabilistic models of language. Such models play an important role in natural language processing tasks such as translation or speech recognition, but often…

Computation and Language · Computer Science 2015-08-19 Jan A. Botha

Go is a popular statically-typed industrial programming language. To aid the type safe reuse of code, the recent Go release (Go 1.18) published on 15th March 2022 includes bounded parametric polymorphism via generic types. Go 1.18…

Programming Languages · Computer Science 2022-10-11 Stephen Ellis , Shuofei Zhu , Nobuko Yoshida , Linhai Song

This PhD thesis contains several contributions to the field of statistical causal modeling. Statistical causal models are statistical models embedded with causal assumptions that allow for the inference and reasoning about the behavior of…

Machine Learning · Statistics 2021-10-05 Martin Emil Jakobsen

We present a general and user-extensible equality checking algorithm that is applicable to a large class of type theories. The algorithm has a type-directed phase for applying extensionality rules and a normalization phase based on…

Logic in Computer Science · Computer Science 2023-06-22 Andrej Bauer , Anja Petković Komel

This dissertation introduces executable refinement types, which refine structural types by semi-decidable predicates, and establishes their metatheory and accompanying implementation techniques. These results are useful for undecidable type…

Programming Languages · Computer Science 2014-03-14 Kenneth Knowles

Erlang is a functional programming language with dynamic typing. The language offers great flexibility for destructing values through pattern matching and dynamic type tests. Erlang also comes with a type language supporting parametric…

Programming Languages · Computer Science 2025-08-04 Albert Schimpf , Stefan Wehr , Annette Bieniusa

Traditional language models operate autoregressively, i.e., they predict one token at a time. Rapid explosion in model sizes has resulted in high inference times. In this work, we propose DynaMo, a suite of multi-token prediction language…

Computation and Language · Computer Science 2024-05-03 Shikhar Tuli , Chi-Heng Lin , Yen-Chang Hsu , Niraj K. Jha , Yilin Shen , Hongxia Jin

We develop a comprehensive theory of the stable representation categories of several sequences of groups, including the classical and symmetric groups, and their relation to the unstable categories. An important component of this theory is…

Representation Theory · Mathematics 2015-06-17 Steven V Sam , Andrew Snowden

Reachability types are a recent proposal that has shown promise in scaling to higher-order but monomorphic settings, tracking aliasing and separation on top of a substrate inspired by separation logic. The prior $\lambda^*$ reachability…

Programming Languages · Computer Science 2023-07-27 Guannan Wei , Oliver Bračevac , Songlin Jia , Yuyan Bao , Tiark Rompf

The recently introduced dependent typed higher-order logic (DHOL) offers an interesting compromise between expressiveness and automation support. It sacrifices the decidability of its type system in order to significantly extend its…

Logic in Computer Science · Computer Science 2025-07-04 Colin Rothgang , Florian Rabe

TextRank is a variant of PageRank typically used in graphs that represent documents, and where vertices denote terms and edges denote relations between terms. Quite often the relation between terms is simple term co-occurrence within a…

Information Retrieval · Computer Science 2017-04-07 Wei Lu , Qikai Cheng , Christina Lioma

We consider the problem of large-scale inference on the row or column variables of data in the form of a matrix. Often this data is transposable, meaning that both the row variables and column variables are of potential interest. An example…

Methodology · Statistics 2015-03-13 Genevera I. Allen , Robert Tibshirani

Many automatic theorem provers are restricted to untyped logics, and existing translations from typed logics are bulky or unsound. Recent research proposes monotonicity as a means to remove some clutter when translating monomorphic to…

Logic in Computer Science · Computer Science 2019-03-14 Jasmin Christian Blanchette , Sascha Böhme , Andrei Popescu , Nicholas Smallbone

We propose a novel type system for verifying that programs correctly implement constant-resource behavior. Our type system extends recent work on automatic amortized resource analysis (AARA), a set of techniques that automatically derive…

Programming Languages · Computer Science 2018-01-09 Van Chan Ngo , Mario Dehesa-Azuara , Matthew Fredrikson , Jan Hoffmann

A gradual semantics takes a weighted argumentation framework as input and outputs a final acceptability degree for each argument, with different semantics performing the computation in different manners. In this work, we consider the…

Artificial Intelligence · Computer Science 2023-02-09 Nir Oren , Bruno Yun

Although neural module networks have an architectural bias towards compositionality, they require gold standard layouts to generalize systematically in practice. When instead learning layouts and modules jointly, compositionality does not…

Machine Learning · Computer Science 2021-05-07 Ankit Vani , Max Schwarzer , Yuchen Lu , Eeshan Dhekane , Aaron Courville