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Probabilistic team semantics is a framework for logical analysis of probabilistic dependencies. Our focus is on the axiomatizability, complexity, and expressivity of probabilistic inclusion logic and its extensions. We identify a natural…

Logic in Computer Science · Computer Science 2021-12-22 Miika Hannula , Jonni Virtema

Literal movement grammars (LMGs) provide a general account of extraposition phenomena through an attribute mechanism allowing top-down displacement of syntactical information. LMGs provide a simple and efficient treatment of complex…

cmp-lg · Computer Science 2016-08-31 Annius V. Groenink

Nested words are a structured model of execution paths in procedural programs, reflecting their call and return nesting structure. Finite nested words also capture the structure of parse trees and other tree-structured data, such as XML. We…

Logic in Computer Science · Computer Science 2015-07-01 Rajeev Alur , Marcelo Arenas , Pablo Barcelo , Kousha Etessami , Neil Immerman , Leonid Libkin

Large language models (LLMs) remain vulnerable to a slew of adversarial attacks and jailbreaking methods. One common approach employed by white-hat attackers, or red-teamers, is to process model inputs and outputs using string-level…

Computation and Language · Computer Science 2024-12-12 Brian R. Y. Huang

Let $M(A,I)$ be a free partially commutative monoid with involution and $G(A,I)$ be its quotient group, e.g. a right-angled Artin or Coxeter group. Given a system of word equations over $M(A,I)$ with recognizable constraints with input size…

Formal Languages and Automata Theory · Computer Science 2025-06-11 Volker Diekert , Artur Jeż , Manfred Kufleitner , Alexander Thumm

Language models based on the Transformer architecture achieve excellent results in many language-related tasks, such as text classification or sentiment analysis. However, despite the architecture of these models being well-defined, little…

Computation and Language · Computer Science 2025-04-14 Miguel López-Otal , Jorge Gracia , Jordi Bernad , Carlos Bobed , Lucía Pitarch-Ballesteros , Emma Anglés-Herrero

Much theoretical work has described the ability of transformers to represent formal languages. However, linking theoretical results to empirical performance is not straightforward due to the complex interplay between the architecture, the…

Computation and Language · Computer Science 2024-10-07 Anej Svete , Nadav Borenstein , Mike Zhou , Isabelle Augenstein , Ryan Cotterell

In program semantics and verification, reasoning about loops is complicated by the need to produce two separate mathematical arguments: an invariant, for functional properties (ignoring termination); and a variant, for termination (ignoring…

Programming Languages · Computer Science 2025-04-14 Bertrand Meyer

We introduce a sound and complete coinductive proof system for reachability properties in transition systems generated by logically constrained term rewriting rules over an order-sorted signature modulo builtins. A key feature of the…

Logic in Computer Science · Computer Science 2018-04-24 Ştefan Ciobâcă , Dorel Lucanu

In this paper we present a fully lexicalized grammar formalism as a particularly attractive framework for the specification of natural language grammars. We discuss in detail Feature-based, Lexicalized Tree Adjoining Grammars (FB-LTAGs), a…

cmp-lg · Computer Science 2008-02-03 B. Srinivas , Dania Egedi , Christy Doran , Tilman Becker

Deep transformer models have pushed performance on NLP tasks to new limits, suggesting sophisticated treatment of complex linguistic inputs, such as phrases. However, we have limited understanding of how these models handle representation…

Computation and Language · Computer Science 2020-10-15 Lang Yu , Allyson Ettinger

By algorithmic metatheorems for a model checking problem P over infinite-state systems we mean generic results that can be used to infer decidability (possibly complexity) of P not only over a specific class of infinite systems, but over a…

Logic in Computer Science · Computer Science 2009-10-28 Anthony Widjaja To , Leonid Libkin

Regular cost functions have been introduced recently as an extension to the notion of regular languages with counting capabilities, which retains strong closure, equivalence, and decidability properties. The specificity of cost functions is…

Logic in Computer Science · Computer Science 2017-02-09 Denis Kuperberg

We present, in easily reproducible terms, a simple transformation for offline-parsable grammars which results in a provably terminating parsing program directly top-down interpretable in Prolog. The transformation consists in two steps: (1)…

cmp-lg · Computer Science 2008-02-03 Marc Dymetman

The grammar representation of a narrowing tree for a syntactically deterministic conditional term rewriting system and a pair of terms is a regular tree grammar that generates expressions for substitutions obtained by all possible…

Logic in Computer Science · Computer Science 2019-02-25 Naoki Nishida , Yuya Maeda

This paper proposes a novel framework for understanding large language models (LLMs) by reconceptualizing them as semiotic machines rather than as imitations of human cognition. Drawing from structuralist and post-structuralist theories of…

Artificial Intelligence · Computer Science 2024-10-18 Elad Vromen

We introduce the Insertion Chain Complex, a higher-dimensional extension of insertion graphs, as a new framework for analyzing finite sets of words. We study its topological and combinatorial properties, in particular its homology groups,…

Combinatorics · Mathematics 2025-09-17 Nataša Jonoska , Francisco Martinez-Figueroa , Masahico Saito

Let $\Lambda^{\ast}$ be the free monoid of (finite) words over a not necessarily finite alphabet $\Lambda$, which is equipped with some (partial) order. This ordering lifts to $\Lambda^{\ast}$, where it extends the divisibility ordering of…

Combinatorics · Mathematics 2018-05-08 Hans-Jürgen Bandelt , Maurice Pouzet

Natural Language Processing enables computers to understand human language by analysing and classifying text efficiently with deep-level grammatical and semantic features. Existing models capture features by learning from large corpora with…

Computation and Language · Computer Science 2026-02-25 Azrin Sultana , Firoz Ahmed

Many NLP applications require models to be interpretable. However, many successful neural architectures, including transformers, still lack effective interpretation methods. A possible solution could rely on building explanations from…

Computation and Language · Computer Science 2024-04-04 Federico Ruggeri , Marco Lippi , Paolo Torroni
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