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Higher dimensional automata (HDA) are a model of concurrency that can express most of the traditional partial order models like Mazurkiewicz traces, pomsets, event structures, or Petri nets. Modal logics, interpreted over Kripke structures,…

Logic in Computer Science · Computer Science 2014-05-19 Cristian Prisacariu

Despite massive investments in scale, deep models for click-through rate (CTR) prediction often exhibit rapidly diminishing returns - a stark contrast to the smooth, predictable gains seen in large language models. We identify the root…

Information Retrieval · Computer Science 2025-11-18 Bencheng Yan , Yuejie Lei , Zhiyuan Zeng , Di Wang , Kaiyi Lin , Pengjie Wang , Jian Xu , Bo Zheng

In this paper, we introduce and study different dissipativity notions and different turnpike properties for discrete-time stochastic nonlinear optimal control problems. The proposed stochastic dissipativity notions extend the classic notion…

Optimization and Control · Mathematics 2025-04-02 Jonas Schießl , Michael H. Baumann , Timm Faulwasser , Lars Grüne

Syntax is a latent hierarchical structure which underpins the robust and compositional nature of human language. In this work, we explore the hypothesis that syntactic dependencies can be represented in language model attention…

Computation and Language · Computer Science 2023-10-24 Jasper Jian , Siva Reddy

We consider concurrent systems consisting of a finite but unknown number of components, that are replicated instances of a given set of finite state automata. The components communicate by executing interactions which are simultaneous…

Formal Languages and Automata Theory · Computer Science 2019-02-08 Marius Bozga , Radu Iosif , Joseph Sifakis

Static structured control refers to the task of designing a state-feedback controller such that the control gain satisfies a subspace constraint. Structured control has applications in control of communication-inhibited dynamical systems,…

Optimization and Control · Mathematics 2024-11-19 Jared Miller , Jaap Eising , Florian Dörfler , Roy S. Smith

Probabilistic game structures combine both nondeterminism and stochasticity, where players repeatedly take actions simultaneously to move to the next state of the concurrent game. Probabilistic alternating simulation is an important tool to…

Logic in Computer Science · Computer Science 2019-07-10 Chenyi Zhang , Jun Pang

In [ABM07], Abdulla et al. introduced the concept of decisiveness, an interesting tool for lifting good properties of finite Markov chains to denumerable ones. Later, this concept was extended to more general stochastic transition systems…

Logic in Computer Science · Computer Science 2022-01-11 Patricia Bouyer , Thomas Brihaye , Mickael Randour , Cédric Rivière , Pierre Vandenhove

Hyperproperties are a modern specification paradigm that extends trace properties to express properties of sets of traces. Temporal logics for hyperproperties studied in the literature, including HyperLTL, assume a synchronous semantics and…

Logic in Computer Science · Computer Science 2021-04-28 Laura Bozzelli , Adriano Peron , Cesar Sanchez

This paper analyzes the notion of causality in a conceptual model, mainly as applied in software engineering. Conceptual system modeling can be considered a three-level process that begins with building a static structural description to…

Software Engineering · Computer Science 2020-05-07 Sabah Al-Fedaghi

Formal control synthesis approaches over stochastic systems have received significant attention in the past few years, in view of their ability to provide provably correct controllers for complex logical specifications in an automated…

Systems and Control · Computer Science 2016-02-04 Majid Zamani , Ilya Tkachev , Alessandro Abate

This paper offers a natural stochastic semantics of Networks of Priced Timed Automata (NPTA) based on races between components. The semantics provides the basis for satisfaction of probabilistic Weighted CTL properties (PWCTL),…

Software Engineering · Computer Science 2014-12-01 Alexandre David , Kim G. Larsen , Axel Legay , Marius Mikučionis , Danny Bøgsted Poulsen , Jonas van Vliet , Zheng Wang

The Spatio-Temporal Traffic Prediction (STTP) problem is a classical problem with plenty of prior research efforts that benefit from traditional statistical learning and recent deep learning approaches. While STTP can refer to many…

Machine Learning · Computer Science 2022-04-12 Leye Wang , Di Chai , Xuanzhe Liu , Liyue Chen , Kai Chen

We describe several new ways of specifying the behaviour of Lemaitre-Tolman (LT) models, in each case presenting the method for obtaining the LT arbitrary functions from the given data, and the conditions for existence of such solutions. In…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Charles Hellaby , Andrzej Krasinski

Many complex systems share two characteristics: 1) they are stochastic in nature, and 2) they are characterized by a large number of factors. At the same time, various natural complex systems appear to have two types of intertwined…

Physics and Society · Physics 2017-07-07 Amin Zollanvari

Traditional sociotechnical systems (STS) theory has been widely used, but there are many new characteristics in the STS environment as we enter the intelligence era, resulting in the limitations of traditional STS. Based on the…

Human-Computer Interaction · Computer Science 2023-03-07 Wei Xu

Modal automata are a classic formal model for component-based systems that comes equipped with a rich specification theory supporting abstraction, refinement and compositional reasoning. In recent years, quantitative variants of modal…

Logic in Computer Science · Computer Science 2013-06-13 Tingting Han , Christian Krause , Marta Kwiatkowska , Holger Giese

This paper offers an approach to extensible knowledge representation and reasoning for a family of formalisms known as Description Logics. The approach is based on the notion of adding new concept constructors, and includes a heuristic…

Artificial Intelligence · Computer Science 2011-05-30 A. Borgida

Semantic Textual Similarity (STS) research has expanded rapidly since 2021, driven by advances in transformer architectures, contrastive learning, and domain-specific techniques. This survey reviews progress across six key areas:…

Computation and Language · Computer Science 2026-01-08 Lokendra Kumar , Neelesh S. Upadhye , Kannan Piedy

We introduce the State Stream Transformer (SST), a novel LLM architecture that reveals emergent reasoning behaviours and capabilities latent in pretrained weights through addressing a fundamental limitation in traditional transformer…

Machine Learning · Computer Science 2025-01-31 Thea Aviss