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We develop a general framework for weighted parsing which is built on top of grammar-based language models and employs multioperator monoids as weight algebras. It generalizes previous work in that area (semiring parsing, weighted deductive…

Formal Languages and Automata Theory · Computer Science 2019-11-18 Richard Mörbitz , Heiko Vogler

Effective token compression remains a critical challenge for scaling models to handle increasingly complex and diverse datasets. A novel mechanism based on contextual reinforcement is introduced, dynamically adjusting token importance…

Computation and Language · Computer Science 2025-08-11 Naderdel Piero , Zacharias Cromwell , Nathaniel Wainwright , Matthias Nethercott

Argument graphs provide an abstract representation of an argumentative situation. A bipolar argument graph is a directed graph where each node denotes an argument, and each arc denotes the influence of one argument on another. Here we…

Artificial Intelligence · Computer Science 2023-08-09 Anthony Hunter

Many semantics for weighted argumentation frameworks assume that each argument is associated with an initial weight. However, eliciting these initial weights poses challenges: (1) accurately providing a specific numerical value is often…

Artificial Intelligence · Computer Science 2025-02-12 Nir Oren , Bruno Yun

Recently, Strength-based Argumentation Frameworks (StrAFs) have been proposed to model situations where some quantitative strength is associated with arguments. In this setting, the notion of accrual corresponds to sets of arguments that…

Artificial Intelligence · Computer Science 2022-07-07 Yohann Bacquey , Jean-Guy Mailly , Pavlos Moraitis , Julien Rossit

Relational properties arise in many settings: relating two versions of a program that use different data representations, noninterference properties for security, etc. The main ingredient of relational verification, relating aligned pairs…

Logic in Computer Science · Computer Science 2016-11-29 Anindya Banerjee , David A. Naumann , Mohammad Nikouei

We tackle the problem of computing counterfactual explanations -- minimal changes to the features that flip an undesirable model prediction. We propose a solution to this question for linear Support Vector Machine (SVMs) models. Moreover,…

Machine Learning · Computer Science 2022-12-16 Sebastian Salazar , Samuel Denton , Ansaf Salleb-Aouissi

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There is, however, a subtle difference between networks where weights are continuos…

Physics and Society · Physics 2013-12-06 Oleguer Sagarra , Conrad J. Pérez-Vicente , Albert Dïaz-Guilera

Modelling qualitative uncertainty in formal argumentation is essential both for practical applications and theoretical understanding. Yet, most of the existing works focus on \textit{abstract} models for arguing with uncertainty. Following…

Artificial Intelligence · Computer Science 2026-02-18 Carlo Proietti , Antonio Yuste-Ginel

Assumption-based Argumentation (ABA) is a well-known structured argumentation formalism, whereby arguments and attacks between them are drawn from rules, defeasible assumptions and their contraries. A common restriction imposed on ABA…

Artificial Intelligence · Computer Science 2024-01-09 Markus Ulbricht , Nico Potyka , Anna Rapberger , Francesca Toni

In various data settings, it is necessary to compare observations from disparate data sources. We assume the data is in the dissimilarity representation and investigate a joint embedding method that results in a commensurate representation…

Methodology · Statistics 2016-01-05 Sancar Adali , Carey E. Priebe

We propose a general framework to allow: (a) specifying the operational semantics of a programming language; and (b) stating and proving properties about program correctness. Our framework is based on a many-sorted system of hybrid modal…

Logic in Computer Science · Computer Science 2025-12-01 Ioana Leustean , Natalia Moanga , Traian Florin Serbanuta

There is a generic way to add any new feature to a system. It involves 1) identifying the basic units which build up the system and 2) introducing the new feature to each of these basic units. In the case where the system is argumentation…

Artificial Intelligence · Computer Science 2015-03-19 D. M. Gabbay , O. Rodrigues

In compositional model-theoretic semantics, researchers assemble truth-conditions or other kinds of denotations using the lambda calculus. It was previously observed that the lambda terms and/or the denotations studied tend to follow the…

Computation and Language · Computer Science 2016-07-11 Jirka Maršík , Maxime Amblard

Multimodal models often over-rely on dominant modalities, failing to achieve optimal performance. While prior work focuses on modifying training objectives or optimization procedures, data-centric solutions remain underexplored. We propose…

Machine Learning · Computer Science 2025-10-01 Seong-Hyeon Hwang , Soyoung Choi , Steven Euijong Whang

We present a novel approach to construction of a formal semantics for a programming language. Our approach, using a parametric denotational semantics, allows the semantics to be easily extended to support new language features, and…

Programming Languages · Computer Science 2018-12-04 In-Ho Yi

A mathematical framework for modelling constrained mixed-variable optimization problems is presented in a blackbox optimization context. The framework introduces a new notation and allows solution strategies. The notation framework allows…

Optimization and Control · Mathematics 2022-04-05 Charles Audet , Edward Hallé-Hannan , Sébastien Le Digabel

This paper presents a novel framework for structured argumentation, named extend argumentative decision graph ($xADG$). It is an extension of argumentative decision graphs built upon Dung's abstract argumentation graphs. The $xADG$…

Artificial Intelligence · Computer Science 2023-11-15 Lucas Rizzo , Luca Longo

Multimodal sarcasm detection, which aims to precisely identify pragmatic incongruities between literal text and nonverbal cues, has gained substantial attention in multimodal understanding. Recent advancements have predominantly relied on…

Computation and Language · Computer Science 2026-05-05 Maoheng Li , Ling Zhou , Xiaohua Huang , Rubing Huang , Wenming Zheng , Guoying Zhao

Learning to solve long horizon temporally extended tasks with reinforcement learning has been a challenge for several years now. We believe that it is important to leverage both the hierarchical structure of complex tasks and to use expert…

Machine Learning · Computer Science 2022-10-18 Bharat Prakash , Nicholas Waytowich , Tim Oates , Tinoosh Mohsenin
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