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Recurrent neural network (RNN) based joint intent classification and slot tagging models have achieved tremendous success in recent years for building spoken language understanding and dialog systems. However, these models suffer from poor…

Computation and Language · Computer Science 2019-10-17 Avik Ray , Yilin Shen , Hongxia Jin

On the Semantic Web, metadata and ontologies are used to enable computers to read data. The Web Ontology Language (OWL) has been proposed as a standard ontological language, and various inference systems for this language have been studied.…

Logic in Computer Science · Computer Science 2022-08-11 Daiki Takahashi , Ken Kaneiwa

Reactive languages are dedicated to the programming of systems which interact continuously and concurrently with their environment. Values take the form of unbounded streams modeling the (discrete) passing of time or the sequence of…

Programming Languages · Computer Science 2023-11-29 Dumitru Potop Butucaru , Albert Cohen , Gordon Plotkin , Hugo Pompougnac

Mechanism design has long been a cornerstone of economic theory, with traditional approaches relying on mathematical derivations. Recently, automated approaches, including differentiable economics with neural networks, have emerged for…

Machine Learning · Computer Science 2025-02-19 Jiayuan Liu , Mingyu Guo , Vincent Conitzer

This report is mostly written for educational purposes. It is meant as a self contained introduction to regular languages, regular expressions, and regular expression matching by using Brzozowski derivatives. As such it is mostly based on…

Formal Languages and Automata Theory · Computer Science 2019-08-01 Ola Wingbrant

Recurrent neural networks (RNNs) provide a powerful approach in neuroscience to infer latent dynamics in neural populations and to generate hypotheses about the neural computations underlying behavior. However, past work has focused on…

Machine Learning · Computer Science 2025-10-30 Elia Torre , Michele Viscione , Lucas Pompe , Benjamin F Grewe , Valerio Mante

Reinforcement Learning (RL) is a widely employed machine learning architecture that has been applied to a variety of control problems. However, applications in safety-critical domains require a systematic and formal approach to specifying…

Machine Learning · Computer Science 2023-06-07 Hosein Hasanbeig , Daniel Kroening , Alessandro Abate

We present a simple technique for semantic, open logical relations arguments about languages with recursive types, which, as we show, follows from a principled foundation in categorical semantics. We demonstrate how it can be used to give a…

Programming Languages · Computer Science 2022-10-25 Fernando Lucatelli Nunes , Matthijs Vákár

In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a prominent approach. In recent years, RC has gained even more popularity in the context of Description Logics (DLs), the logic underpinning the…

Artificial Intelligence · Computer Science 2023-06-02 Giovanni Casini , Umberto Straccia

Given an order of the underlying alphabet we can lift it to the states of a finite deterministic automaton: to compare states we use the order of the strings reaching them. When the order on strings is the co-lexicographic one \emph{and}…

Formal Languages and Automata Theory · Computer Science 2022-03-24 Giovanna D'Agostino , Davide Martincigh , Alberto Policriti

Many automatic theorem-provers rely on rewriting. Using theorems as rewrite rules helps to simplify the subgoals that arise during a proof. LCF is an interactive theorem-prover intended for reasoning about computation. Its implementation of…

Logic in Computer Science · Computer Science 2016-08-31 Lawrence C. Paulson

We propose an approach that connects recurrent networks with different orders of hidden interaction with regular grammars of different levels of complexity. We argue that the correspondence between recurrent networks and formal…

Machine Learning · Computer Science 2019-11-13 Qinglong Wang , Kaixuan Zhang , Xue Liu , C. Lee Giles

Watson-Crick automata are finite automata working on double strands. Extensive research work has already been done on non-deterministic Watson-Crick automata and on deterministic Watson-Crick automata. In this paper, we introduce a new…

Formal Languages and Automata Theory · Computer Science 2015-12-10 Kingshuk Chatterjee , Kumar Sankar Ray

In the mid 80s, Lichtenstein, Pnueli, and Zuck proved a classical theorem stating that every formula of Past LTL (the extension of LTL with past operators) is equivalent to a formula of the form $\bigwedge_{i=1}^n \mathbf{G}\mathbf{F}…

Logic in Computer Science · Computer Science 2020-05-04 Salomon Sickert , Javier Esparza

Decision Transformer (DT) has emerged as a promising class of algorithms in offline reinforcement learning (RL) tasks, leveraging pre-collected datasets and Transformer's capability to model long sequences. Recent works have demonstrated…

Machine Learning · Computer Science 2025-12-03 Yu Yang , Pan Xu

In this paper, different variants of reversible finite automata are compared, and their hierarchy by the expressive power is established. It is shown that one-way reversible automata with multiple initial states (MRFA) recognize strictly…

Formal Languages and Automata Theory · Computer Science 2024-11-25 Maria Radionova , Alexander Okhotin

The ability of Large Language Models (LLMs) to perform reasoning tasks such as deduction has been widely investigated in recent years. Yet, their capacity to generate proofs-faithful, human-readable explanations of why conclusions…

Artificial Intelligence · Computer Science 2026-01-21 Hui Yang , Jiaoyan Chen , Uli Sattler

The notion of Wheeler languages is rooted in the Burrows-Wheeler transform (BWT), one of the most central concepts in data compression and indexing. The BWT has been generalized to finite automata, the so-called Wheeler automata, by Gagie…

Formal Languages and Automata Theory · Computer Science 2025-04-29 Ruben Becker , Giuseppa Castiglione , Giovanna D'Agostino , Alberto Policriti , Nicola Prezza , Antonio Restivo , Brian Riccardi

Long-horizon tasks requiring multi-step reasoning and dynamic re-planning remain challenging for large language models (LLMs). Sequential prompting methods are prone to context drift, loss of goal information, and recurrent failure cycles,…

Artificial Intelligence · Computer Science 2025-10-30 Zhenyu Zhang , Tianyi Chen , Weiran Xu , Alex Pentland , Jiaxin Pei

We provide new insights on the determinization and minimization of tree automata using congruences on trees. From this perspective, we study a Brzozowski's style minimization algorithm for tree automata. First, we prove correct this method…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Pierre Ganty , Elena Gutiérrez , Pedro Valero
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