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Abstract predicates are considered in this paper as abstraction technique for heap-separated configurations, and as genuine Prolog predicates which are translated straight into a corresponding formal language grammar used as validation…

Logic in Computer Science · Computer Science 2019-06-04 René Haberland , Kirill Krinkin , Sergey Ivanovskiy

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

We introduce a new semantics for justification logic based on subset relations. Instead of using the established and more symbolic interpretation of justifications, we model justifications as sets of possible worlds. We introduce a new…

Logic · Mathematics 2020-08-19 Eveline Lehmann , Thomas Studer

We endow prioritised default logic (PDL) with argumentation semantics using the ASPIC+ framework for structured argumentation, and prove that the conclusions of the justified arguments are exactly the prioritised default extensions.…

Artificial Intelligence · Computer Science 2015-07-02 Anthony P. Young , Sanjay Modgil , Odinaldo Rodrigues

We describe the problem of aggregating the label predictions of diverse classifiers using a class taxonomy. Such a taxonomy may not have been available or referenced when the individual classifiers were designed and trained, yet mapping the…

Artificial Intelligence · Computer Science 2015-12-02 Amrita Saha , Sathish Indurthi , Shantanu Godbole , Subendhu Rongali , Vikas C. Raykar

A well-known approach to treating syntactic island constraints in the setting of Lambek grammars consists in adding specific bracket modalities to the logic. We adapt this approach to abstract categorial grammars (ACG). Thus we define…

Logic · Mathematics 2020-05-21 Sergey Slavnov

A fuzzy multipreference semantics has been recently proposed for weighted conditional knowledge bases, and used to develop a logical semantics for Multilayer Perceptrons, by regarding a deep neural network (after training) as a weighted…

Artificial Intelligence · Computer Science 2021-10-27 Laura Giordano

Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are widely studied, but their applicability is limited by a representational restriction to…

Artificial Intelligence · Computer Science 2026-04-14 Emanuele De Angelis , Fabio Fioravanti , Maria Chiara Meo , Alberto Pettorossi , Maurizio Proietti , Francesca Toni

Beyond exploring disaggregated labels for modeling perspectives, annotator rationales provide fine-grained signals of individual perspectives. In this work, we propose a framework for jointly modeling annotator-specific label prediction and…

Computation and Language · Computer Science 2026-04-24 Olufunke O. Sarumi , Charles Welch , Daniel Braun

In this paper we propose a general approach to define a many-valued preferential interpretation of gradual argumentation semantics. The approach allows for conditional reasoning over arguments and boolean combination of arguments, with…

Artificial Intelligence · Computer Science 2025-06-10 Mario Alviano , Laura Giordano , Daniele Theseider Dupré

Monitoring the performance of classification models in production is critical yet challenging due to strict labeling budgets, one-shot batch acquisition of labels and extremely low error rates. We propose a general framework based on…

Machine Learning · Computer Science 2026-02-02 Lupo Marsigli , Angel Lopez de Haro

We propose "semantic labelling" as a novel ingredient for solving games in the context of LTL synthesis. It exploits recent advances in the automata-based approach, yielding more information for each state of the generated parity game than…

Logic in Computer Science · Computer Science 2019-07-30 Jan Křetínský , Alexander Manta , Tobias Meggendorfer

Framed combinatorial topology is a recent approach to tame geometry which expresses higher-dimensional stratified spaces via tractable combinatorial data. The resulting theory of spaces is well-behaved and computable. In this paper we…

Algebraic Topology · Mathematics 2023-05-11 Lukas Heidemann

Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argument. There are various interpretations that can be ascribed…

Artificial Intelligence · Computer Science 2014-05-15 Anthony Hunter , Matthias Thimm

We continue work of our earlier paper (Lewitzka and Brunner: Minimally generated abstract logics, Logica Universalis 3(2), 2009), where abstract logics and particularly intuitionistic abstract logics are studied. Abstract logics can be…

Logic in Computer Science · Computer Science 2017-04-04 Andreas B. M. Brunner , Steffen Lewitzka

Category theory can be used to state formulas in First-Order Logic without using set membership. Several notable results in logic such as proof of the continuum hypothesis can be elegantly rewritten in category theory. We propose in this…

Logic in Computer Science · Computer Science 2022-04-19 Chan Le Duc

Argument search aims at identifying arguments in natural language texts. In the past, this task has been addressed by a combination of keyword search and argument identification on the sentence- or document-level. However, existing…

Computation and Language · Computer Science 2021-12-02 Michael Färber , Anna Steyer

Ideological attitudes and stance are often expressed through subtle meanings of words and phrases. Understanding these connotations is critical to recognizing the cultural and emotional perspectives of the speaker. In this paper, we use…

Computation and Language · Computer Science 2021-03-02 Emily Allaway , Kathleen McKeown

Extreme multi-label classification (XML) is becoming increasingly relevant in the era of big data. Yet, there is no method for effectively generating stratified partitions of XML datasets. Instead, researchers typically rely on provided…

Machine Learning · Computer Science 2021-03-08 Maximillian Merrillees , Lan Du

We present a novel approach to uncertainty quantification in classification tasks based on label-wise decomposition of uncertainty measures. This label-wise perspective allows uncertainty to be quantified at the individual class level,…

Machine Learning · Computer Science 2024-06-05 Yusuf Sale , Paul Hofman , Timo Löhr , Lisa Wimmer , Thomas Nagler , Eyke Hüllermeier