9 papers · ranked by Valyu relevance
Lars Vogt
This manuscript introduces the Semantic Units Framework, a technology-agnostic representational approach to semantic modularization in which statements and compound meaning structures are treated as first-class semantic units with explicit boundaries, identity, and epistemic status. Motivated by recurring limitations…
Parisa Kordjamshidi, Dan Roth, Kristian Kersting
Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these solutions. Often, a solution involves multiple learning models, along with significant levels of reasoning with the models'…
Adam Pease, Richard Thompson
Human language is often vague and ambiguous. There have been many efforts to create formal languages and many attempts to translate human language into formal languages. Logic has a great deal of flexibility, not least in how the symbols used are defined. We anchor lexical elements in a formal ontology, which helps…
Prakash Mondal
Fundamental tensions exist between formal-logical approaches and cognitive approaches to linguistic meaning. The divergence arises from the fundamental differences in nature and form between formal/mathematical structures of natural language meaning and their cognitive representations. While the former are abstract and…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
Violetta Molokopoy, Amedeo D’Angiulli, Tomaso Vecchi
This article will explore the expressivity and tractability of vividness, as viewed from the interdisciplinary perspective of the cognitive sciences, including the sub-disciplines of artificial intelligence, cognitive psychology, neuroscience, and phenomenology. Following the precursor work by Benussi in experimental…
Fang Wan, Chaoyang Song
This paper describes a neural network design using auxiliary inputs, namely the indicators, that act as the hints to explain the predicted outcome through logical reasoning, mimicking the human behavior of deductive reasoning. Besides the original network input and output, we add an auxiliary input that reflects the…
Authors not listed
In the real world, many reversal phenomena occur—for example, cases in which a statement once regarded as false is later recognized as true. Upside-Down Logic is a framework designed to formalize such reversal phenomena as a logical system. It inverts the truth and falsity of propositions through contextual…
Authors not listed
Machine learning is increasingly used to predict reaction properties such as barrier heights, reaction energies, rates, or yields, as well as the underlying molecular geometries, including transition state structures. While such predictions have the potential to provide mechanistic insight for high-impact applications…