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Concept embeddings offer a practical and efficient mechanism for injecting commonsense knowledge into downstream tasks. Their core purpose is often not to predict the commonsense properties of concepts themselves, but rather to identify…

Artificial Intelligence · Computer Science 2024-06-06 Hanane Kteich , Na Li , Usashi Chatterjee , Zied Bouraoui , Steven Schockaert

Non-classical logics are used in a wide spectrum of disciplines, including artificial intelligence, computer science, mathematics, and philosophy. The de-facto standard infrastructure for automated theorem proving, the TPTP World, currently…

Artificial Intelligence · Computer Science 2022-02-22 Alexander Steen , David Fuenmayor , Tobias Gleißner , Geoff Sutcliffe , Christoph Benzmüller

Large Language Models (LMs) are known to encode world knowledge in their parameters as they pretrain on a vast amount of web corpus, which is often utilized for performing knowledge-dependent downstream tasks such as question answering,…

Computation and Language · Computer Science 2022-05-25 Joel Jang , Seonghyeon Ye , Sohee Yang , Joongbo Shin , Janghoon Han , Gyeonghun Kim , Stanley Jungkyu Choi , Minjoon Seo

Joint representation learning of text and knowledge within a unified semantic space enables us to perform knowledge graph completion more accurately. In this work, we propose a novel framework to embed words, entities and relations into the…

Computation and Language · Computer Science 2016-11-15 Xu Han , Zhiyuan Liu , Maosong Sun

This paper illustrates the richness of the concept of regular sets of time bounds and demonstrates its application to problems of computational complexity. There is a universe of bounds whose regular subsets allow to represent several time…

Computational Complexity · Computer Science 2013-09-24 Armin Hemmerling

Probing and enhancing large language models' reasoning capacity remains a crucial open question. Here we re-purpose the reverse dictionary task as a case study to probe LLMs' capacity for conceptual inference. We use in-context learning to…

Computation and Language · Computer Science 2024-02-27 Ningyu Xu , Qi Zhang , Menghan Zhang , Peng Qian , Xuanjing Huang

Continual learning is the ability to sequentially learn over time by accommodating knowledge while retaining previously learned experiences. Neural networks can learn multiple tasks when trained on them jointly, but cannot maintain…

Machine Learning · Computer Science 2018-10-26 Frantzeska Lavda , Jason Ramapuram , Magda Gregorova , Alexandros Kalousis

Labeled examples (i.e., positive and negative examples) are an attractive medium for communicating complex concepts. They are useful for deriving concept expressions (such as in concept learning, interactive concept specification, and…

Logic in Computer Science · Computer Science 2024-12-24 Balder ten Cate , Raoul Koudijs , Ana Ozaki

In standard epistemic logic, knowing that p is the same as knowing that p is true, but it does not say anything about understanding p or knowing its meaning. In this paper, we present a conservative extension of Public Announcement Logic…

Logic in Computer Science · Computer Science 2019-07-23 Malvin Gattinger , Yanjing Wang

Many classical planning frameworks are built on first-order languages. The first-order expressive power is desirable for compactly representing actions via schemas, and for specifying quantified conditions such as $\neg\exists…

Logic in Computer Science · Computer Science 2020-06-04 Andrés Occhipinti Liberman , Andreas Achen , Rasmus Kræmmer Rendsvig

Over two decades ago a "quite revolution" overwhelmingly replaced knowledgebased approaches in natural language processing (NLP) by quantitative (e.g., statistical, corpus-based, machine learning) methods. Although it is our firm belief…

Artificial Intelligence · Computer Science 2008-08-11 Walid S. Saba

A new syntactic characterization of problems complete via Turing reductions is presented. General canonical forms are developed in order to define such problems. One of these forms allows us to define complete problems on ordered…

Computational Complexity · Computer Science 2014-11-25 Vladimir Naidenko

Existential fixed point logic (EFPL) is a natural fit for some applications, and the purpose of this talk is to attract attention to EFPL. The logic is also interesting in its own right as it has attractive properties. One of those…

Logic in Computer Science · Computer Science 2008-11-07 Andreas Blass , Yuri Gurevich

A type theory is presented that combines (intuitionistic) linear types with type dependency, thus properly generalising both intuitionistic dependent type theory and full linear logic. A syntax and complete categorical semantics are…

Logic in Computer Science · Computer Science 2026-05-07 Matthijs Vákár

We produce a decidable super-intuitionistic normal modal logic of internalised intuitionistic (and thus disjunctive and monotonic) interactive proofs (LIiP) from an existing classical counterpart of classical monotonic non-disjunctive…

Logic · Mathematics 2015-09-22 Simon Kramer

We compare different epistemic notions in the presence of awareness of propositional variables: the logics of implicit knowledge (in which explicit knowledge is definable), explicit knowledge, and speculative knowledge. Different notions of…

Logic in Computer Science · Computer Science 2013-10-29 Hans van Ditmarsch , Tim French , Fernando R. Velazquez-Quesada , Yi N. Wang

Here we deal with the logic of [GuSh 533], which tries to capture polynomial time (for finite models). There it is proved that the logic cannot say much on models with equality only. Here we prove that it cannot say much on models for which…

Logic · Mathematics 2009-09-25 Saharon Shelah

We propose a validity preserving translation from a subset of epistemic Alternating-time Temporal Logic (ATL) to epistemic Computation Tree Logic (CTL). The considered subset of epistemic ATL is known to have the finite model property and…

Logic in Computer Science · Computer Science 2013-03-05 Dimitar P. Guelev

Starting from the observation that rational closure has the undesirable property of being an "all or nothing" mechanism, we here propose a multipreferential semantics, which enriches the preferential semantics underlying rational closure in…

Artificial Intelligence · Computer Science 2018-01-23 Laura Giordano , Valentina Gliozzi

Commonsense knowledge is essential for advancing natural language processing (NLP) by enabling models to engage in human-like reasoning, which requires a deeper understanding of context and often involves making inferences based on implicit…

Computation and Language · Computer Science 2024-09-16 Yubo Xie , Zonghui Liu , Zongyang Ma , Fanyuan Meng , Yan Xiao , Fahui Miao , Pearl Pu