26 papers · ranked by Valyu relevance
Jingde Cheng
— Recently, with the application progress of AIGC tools based on large language models (LLMs), led by ChatGPT, many AI experts and more non-professionals are trumpeting the "reasoning ability" of the LLMs. The present author considers that the so-called "reasoning ability" of LLMs are just illusions of those people who…
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…
Seunghyun Park, Yuanyuan Lei
While LLMs demonstrate impressive reasoning capabilities, they remain fragile in multi-step logical deduction, where a single transition error can propagate through the entire reasoning chain, leading to unstable performance. In this work, we identify logical connectives as primary points of this structural fragility.…
Hope Kean, Alexander Fung, Paris Jaggers, Jason Chen + 6 more
Humans are endowed with a powerful capacity for both inductive and deductive logical thought: we easily form generalizations based on a few examples and draw conclusions from known premises. Humans also arguably have the most sophisticated communication system in the animal kingdom: natural language allows us to…
Siyuan Wang, Wanjun Zhong, Duyu Tang, Zhongyu Wei + 4 more
'Daxin Jiang' 'Ming Zhou' 'Nan Duan'] Logical reasoning of text requires understanding critical logical information in the text and performing inference over them. Largescale pre-trained models for logical reasoning mainly focus on word-level semantics of text while struggling to capture symbolic logic. In this paper…
Wesley H. Holliday, Matthew Mandelkern
The reasoning abilities of large language models (LLMs) are the topic of a growing body of research in AI and cognitive science. In this paper, we probe the extent to which twenty-nine LLMs are able to distinguish logically correct inferences from logically fallacious ones. We focus on inference patterns involving…
Yanda Li, Dixuan Wang, Jiaqing Liang, Guochao Jiang + 3 more
'Yanghua Xiao' 'Deqing Yang'] Large Language Models (LLMs) have demonstrated good performance in many reasoning tasks, but they still struggle with some complicated reasoning tasks including logical reasoning. One non-negligible reason for LLMs' suboptimal performance on logical reasoning is their overlooking of…
Hope Kean, Alexander Fung, Paris Jaggers, Jason Chen + 6 more
Humans are endowed with a powerful capacity for both inductive and deductive logical thought: we easily form generalizations based on a few examples and draw conclusions from known premises. Humans also arguably have the most sophisticated communication system in the animal kingdom: natural language allows us to…
Antigoni Belekou, Charalabos Papageorgiou, Efstratios Karavasilis, Eleftheria Tsaltas + 3 more
Paradoxes are a special form of reasoning leading to absurd inferences in contrast to logical reasoning that is used to reach valid conclusions. A functional MRI (fMRI) study was conducted to investigate the neural substrates of paradoxical and deductive reasoning. Twenty-four healthy participants were scanned using…
Maryam Ziaei, Mohammad Reza Bonyadi, David C. Reutens
In logical reasoning, difficulties in inhibition of currently-held beliefs may lead to unwarranted conclusions, known as belief bias. Aging is associated with difficulties in inhibitory control, which may lead to deficits in inhibition of currently-held beliefs. No study to date, however, has investigated the…
Ana Martín-Salguero, Carlo Reverberi, Aldo Solari, Luca Filippin + 2 more
'Christophe Pallier' 'Luca L. Bonatti'] We often express our thoughts through words, but thinking goes well beyond language. Here we focus on an elementary but basic thinking process, disjunction elimination, elicited by elementary visual scenes deprived of linguistic content, describing its neural and oculomotor…
Reto Gubelmann
Taking Leibniz' ideal of a universal truth-calculating machine as a vantage point, this article provides a philosophically sound analysis of the concept of reasoning in NLP. It argues that reasoning always involves inference, which in turn requires being guided by reason relations. Based on this, the article argues…
Maryam Ziaei, Mohammad Reza Bonyadi, David Reutens
Prior knowledge and beliefs influence our reasoning in daily life and may lead us to draw unwarranted conclusions with undesirable consequences. The underlying neural correlates of the interaction between belief and logic, prior to making logical decisions, are largely unknown. In this study, we aimed to identify brain…
Ulrich Furbach, Claudia Schon, Frieder Stolzenburg, Karl-Heinz Weis + 1 more
'Claus-Peter Wirth'] Abstract Higher-level cognition includes logical reasoning and the ability of question answering with common sense. The RatioLog project addresses the problem of rational reasoning in deep question answering by methods from automated deduction and cognitive computing. In a first phase, we combine…
Henrik Singmann, Karl Christoph Klauer, David Kellen, Jean Daunizeau
Recent research on syllogistic reasoning suggests that the logical status (valid vs. invalid) of even difficult syllogisms can be intuitively detected via differences in conceptual fluency between logically valid and invalid syllogisms when participants are asked to rate how much they like a conclusion following from a…
Omid Ghasemi, Simon J. Handley, Rachel G. Stephens
When individuals are asked to evaluate the believability of the conclusions to valid or invalid arguments, they often endorse valid conclusions at higher rates than invalid ones. This effect of validity on belief judgments-the “logic-belief effect” -is considered evidence of intuitive logic. However, recent studies…
Seyyedeh Fatemeh Seyyed Hashemi, Reza Khosrowabadi, Mohsen Karimi
The rule-matching bias is a common error during conditional reasoning tasks, which refers to a tendency to match responses with the lexical context in the conditional rule and leads to incorrect responses. Conditional reasoning is one of the higher-level cognitive abilities affected by many cognitive skills. We aimed…
Florian Richter
The difference between object-language and metalanguage is crucial for logical analysis, but has yet not been examined for the field of computer science. In this paper the difference is examined with regard to inferential relations. It is argued that inferential relations in a metalanguage (like a calculus for…
Francisco Salto, Carmen Requena, Paula Álvarez-Merino, Luís F. Antón-Toro + 1 more
'Luís F. Antón-Toro' 'Fernando Maestú'] Neuroscience has studied deductive reasoning over the last 20 years under the assumption that deductive inferences are not only de jure but also de facto distinct from other forms of inference. The objective of this research is to verify if logically valid deductions leave any…
Walter Schroyens, Lieve Fleerackers, Sunile Maes
reasoning about probable but false antecedent to consequent relations Authors: ['Walter Schroyens' 'Lieve Fleerackers' 'Sunile Maes'] Two experiments (N1 = 117 and N2 = 245) on reasoning with knowledge-rich conditionals showed a main effect of logical validity, which was due to the negative effect of counter-examples…
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Artificial intelligence, represented by large language models (LLMs), has demonstrated tremendous capabilities in natural language recognition and extraction. To further evaluate the performance of various LLMs in extracting information from academic papers, this study explores the application of LLMs in reticular…
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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…
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In philosophy and science, a first principle is a basic proposition or assumption that cannot be deduced from any other proposition or assumption. Ancient Greek philosophy Aristotle defined the first principle as “the first basis from which a thing is known.” First principles thinking (or reasoning from first…
Tianfan Jin, Brett M Savoie
Contemporary machine learning algorithms have largely succeeded in automating the development of mathematical models from data. Although this is a striking accomplishment, it leaves unaddressed the multitude of scenarios, especially across the chemical sciences and engineering, where deductive, rather than inductive…
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Nuclear Magnetic Resonance (NMR) structure determination is an important problem in education, industry, and research. Solving NMR spectra requires expert knowledge, critical thinking, and careful evaluation of multiple features of spectral data. This study explores the capabilities of large language models (LLMs) for…
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The scarcity and expense of fatigue data limits optimal design of components and constrains companies to a few well qualified materials when safety-critical applications are concerned. This research investigates different strategies to improve extraction of structured information from unstructured scientific…