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Related papers: On Uniform Equivalence of Epistemic Logic Programs

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Large language models (LLMs) are a promising venue for natural language understanding and generation tasks. However, current LLMs are far from reliable: they are prone to generate non-factual information and, more crucially, to contradict…

Machine Learning · Computer Science 2024-04-22 Diego Calanzone , Stefano Teso , Antonio Vergari

We study abduction in First Order Horn logic theories where all atoms can be abduced and we are looking for preferred solutions with respect to three objective functions: cardinality minimality, coherence, and weighted abduction. We…

Artificial Intelligence · Computer Science 2018-02-01 Peter Schüller

Answering compositional questions that require multiple steps of reasoning against text is challenging, especially when they involve discrete, symbolic operations. Neural module networks (NMNs) learn to parse such questions as executable…

Computation and Language · Computer Science 2020-02-18 Nitish Gupta , Kevin Lin , Dan Roth , Sameer Singh , Matt Gardner

Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an application point of view, existing semantics are not…

Artificial Intelligence · Computer Science 2012-03-19 Kim Bauters , Steven Schockaert , Martine De Cock , Dirk Vermeir

\emph{Canonical (logic) programs} (CP) refer to normal logic programs augmented with connective $not\ not$. In this paper we address the question of whether CP are \emph{succinctly incomparable} with \emph{propositional formulas} (PF). Our…

Logic in Computer Science · Computer Science 2015-01-27 Yuping Shen , Xishun Zhao

Rules in logic programming encode information about mutual interdependencies between literals that is not captured by any of the commonly used semantics. This information becomes essential as soon as a program needs to be modified or…

Artificial Intelligence · Computer Science 2011-03-02 Martin Slota , João Leite

Entity matching (EM) is a critical step in entity resolution (ER). Recently, entity matching based on large language models (LLMs) has shown great promise. However, current LLM-based entity matching approaches typically follow a binary…

Computation and Language · Computer Science 2024-12-13 Tianshu Wang , Xiaoyang Chen , Hongyu Lin , Xuanang Chen , Xianpei Han , Hao Wang , Zhenyu Zeng , Le Sun

We examine the practicality for a user of using Answer Set Programming (ASP) for representing logical formalisms. We choose as an example a formalism aiming at capturing causal explanations from causal information. We provide an…

Artificial Intelligence · Computer Science 2010-12-06 Yves Moinard

Assessing the trustworthiness of artificial intelligence systems requires knowledge from many different disciplines. These disciplines do not necessarily share concepts between them and might use words with different meanings, or even use…

Information Retrieval · Computer Science 2022-08-10 Dennis Vetter , Jesmin Jahan Tithi , Magnus Westerlund , Roberto V. Zicari , Gemma Roig

A growing interest in tasks involving language understanding by the NLP community has led to the need for effective semantic parsing and inference. Modern NLP systems use semantic representations that do not quite fulfill the nuanced needs…

Computation and Language · Computer Science 2019-04-01 Gene Louis Kim , Lenhart Schubert

Researchers in answer set programming and constraint programming have spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts…

Artificial Intelligence · Computer Science 2017-12-04 Marcello Balduccini , Yuliya Lierler

The Logic of Proofs, LP, and its successor, Justification Logic, is a refinement of the modal logic approach to epistemology in which proofs/justifications are taken into account. In 2000 Kuznets showed that satisfiability for LP is in the…

Logic in Computer Science · Computer Science 2014-04-29 Antonis Achilleos

The Autoepistemic Logic of Knowledge and Belief (AELB) is a powerful nonmonotic formalism introduced by Teodor Przymusinski in 1994. In this paper, we specialize it to a class of theories called `super logic programs'. We argue that these…

Artificial Intelligence · Computer Science 2007-05-23 Stefan Brass , Juergen Dix , Teodor C. Przymusinski

Since the introduction of the stable marriage problem (SMP) by Gale and Shapley (1962), several variants and extensions have been investigated. While this variety is useful to widen the application potential, each variant requires a new…

Artificial Intelligence · Computer Science 2020-02-19 Sofie De Clercq , Steven Schockaert , Martine De Cock , Ann Nowé

Knowledge Representation and Reasoning and Machine Learning are two important fields in AI. Nonmonotonic logic programming (NMLP) and Answer Set Programming (ASP) provide formal languages for representing and reasoning with commonsense…

Artificial Intelligence · Computer Science 2013-11-20 Katsumi Inoue , Chiaki Sakama

Large language models (LLMs) have achieved strong performance on reasoning benchmarks, yet their ability to solve real-world problems requiring end-to-end workflows remains unclear. Mathematical modeling competitions provide a stringent…

Computation and Language · Computer Science 2026-04-07 Yuhang Liu , Heyan Huang , Yizhe Yang , Hongyan Zhao , Zhizhuo Zeng , Yang Gao

Answer Set Programming (ASP) is nowadays a dominant rule-based knowledge representation tool. Though existing ASP variants enjoy efficient implementations, generating an answer set remains intractable. The goal of this research is to define…

Logic in Computer Science · Computer Science 2020-06-30 Andrzej Szalas

Uniform proofs are sequent calculus proofs with the following characteristic: the last step in the derivation of a complex formula at any stage in the proof is always the introduction of the top-level logical symbol of that formula. We…

Logic in Computer Science · Computer Science 2014-11-17 Gopalan Nadathur

Semantic caching enhances the efficiency of large language model (LLM) systems by identifying semantically similar queries, storing responses once, and serving them for subsequent equivalent requests. However, existing semantic caching…

Machine Learning · Computer Science 2025-07-10 Shervin Ghaffari , Zohre Bahranifard , Mohammad Akbari

LLMs increasingly serve as tools for knowledge acquisition, yet users cannot effectively specify how they want information presented. When users request that LLMs "cite reputable sources," "express appropriate uncertainty," or "include…

Human-Computer Interaction · Computer Science 2025-04-03 Nicholas Clark , Hua Shen , Bill Howe , Tanushree Mitra
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