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Deep learning methods capable of handling relational data have proliferated over the last years. In contrast to traditional relational learning methods that leverage first-order logic for representing such data, these deep learning methods…

Machine Learning · Computer Science 2020-03-25 Sebastijan Dumancic , Tias Guns , Wannes Meert , Hendrik Blockeel

In this paper, we construct and investigate a hierarchy of spatio-temporal formalisms that result from various combinations of propositional spatial and temporal logics such as the propositional temporal logic PTL, the spatial logics RCC-8,…

Artificial Intelligence · Computer Science 2011-10-13 D. Gabelaia , R. Kontchakov , A. Kurucz , F. Wolter , M. Zakharyaschev

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

Linear Temporal Logic (LTL) is the standard specification language for reactive systems and is successfully applied in industrial settings. However, many shortcomings of LTL have been identified in the literature, among them the limited…

Logic in Computer Science · Computer Science 2021-04-30 Daniel Neider , Alexander Weinert , Martin Zimmermann

Logical fallacy uses invalid or faulty reasoning in the construction of a statement. Despite the prevalence and harmfulness of logical fallacies, detecting and classifying logical fallacies still remains a challenging task. We observe that…

Computation and Language · Computer Science 2024-10-17 Yuanyuan Lei , Ruihong Huang

We present an expressive logic over trace formulas, based on binary state predicates, chop, and least fixed-points, for precise specification of programs with recursive procedures. Both, programs and trace formulas, are equipped with a…

Logic in Computer Science · Computer Science 2024-11-21 Dilian Gurov , Reiner Hähnle

We consider an extension of bi-intuitionistic logic with the traditional modalities from tense logic Kt. Proof theoretically, this extension is obtained simply by extending an existing sequent calculus for bi-intuitionistic logic with…

Logic in Computer Science · Computer Science 2010-06-30 Rajeev Gore , Linda Postniece , Alwen Tiu

The field of Language Reasoning Models (LRMs) has been very active over the past few years with advances in training and inference techniques enabling LRMs to reason longer, and more accurately. However, a growing body of studies show that…

Computation and Language · Computer Science 2026-04-24 Yannis Belkhiter , Seshu Tirupathi , Giulio Zizzo , John D. Kelleher

We present CLTLB(D), an extension of PLTLB (PLTL with both past and future operators) augmented with atomic formulae built over a constraint system D. Even for decidable constraint systems, satisfiability and Model Checking problem of such…

Logic in Computer Science · Computer Science 2010-04-21 Marcello M. Bersani , Achille Frigeri , Angelo Morzenti , Matteo Pradella , Matteo Rossi , Pierluigi San Pietro

Turing's famous 'machine' framework provides an intuitively clear conception of 'computing with real numbers'. A recursive counterexample to a theorem shows that the theorem does not hold when restricted to computable objects. These…

Logic · Mathematics 2020-06-23 Sam Sanders

This paper contains a classification of countable lower 1-transitive linear orders. The notion of lower 1-transitivity generalises that of 1-transitivity for linear orders, and is essential for the structure theory of 1-transitive trees.…

Combinatorics · Mathematics 2015-10-22 Silvia Barbina , Katie Chicot

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

Nomadic applications create replicas of shared objects that evolve independently while they are disconnected. When reconnecting, the system has to reconcile the divergent replicas. In the log-based approach to reconciliation, such as in the…

Programming Languages · Computer Science 2007-05-23 Francois Fages

The notion of bounded expansion captures uniform sparsity of graph classes and renders various algorithmic problems that are hard in general tractable. In particular, the model-checking problem for first-order logic is fixed-parameter…

We present LTLS, a technique for multiclass and multilabel prediction that can perform training and inference in logarithmic time and space. LTLS embeds large classification problems into simple structured prediction problems and relies on…

Machine Learning · Computer Science 2016-11-08 Kalina Jasinska , Nikos Karampatziakis

A Learning Model Predictive Controller (LMPC) for linear system in presented. The proposed controller is an extension of the LMPC [1] and it aims to decrease the computational burden. The control scheme is reference-free and is able to…

Optimization and Control · Mathematics 2019-10-31 Ugo Rosolia , Francesco Borrelli

We introduce and develop propositional continuous intuitionistic logic and propositional continuous affine logic via complete algebraic semantics. Our approach centres on AC-algebras, which are algebras $USC(\mathcal{L})$ of sup-preserving…

Logic in Computer Science · Computer Science 2026-02-06 Guillaume Geoffroy

Standpoint linear temporal logic ($SLTL$) is a recently introduced extension of classical linear temporal logic ($LTL$) with standpoint modalities. Intuitively, these modalities allow to express that, from agent $a$'s standpoint, it is…

Logic in Computer Science · Computer Science 2025-02-28 Rajab Aghamov , Christel Baier , Toghrul Karimov , Rupak Majumdar , Joël Ouaknine , Jakob Piribauer , Timm Spork

Text embedding and generative tasks are usually trained separately based on large language models (LLMs) nowadays. This causes a large amount of training cost and deployment effort. Context compression is also a challenging and pressing…

Computation and Language · Computer Science 2026-05-13 Zhongtao Miao , Qiyu Wu , Yoshimasa Tsuruoka

\ac{CoT} prompting improves LLM accuracy on complex tasks but often increases token usage and inference cost. Existing ``Budget Forcing'' methods reduce cost via fine-tuning with heuristic length penalties, suppressing both essential…

Machine Learning · Computer Science 2026-05-19 Fabio Valerio Massoli , Andrey Kuzmin , Arash Behboodi