Results 181 to 190 of about 89,998 (313)
Arabic Aphasia Research Through a Clinical and Linguistic Lens: A Systematic Review of Current Limitations and Future Directions. [PDF]
Khwaileh T +4 more
europepmc +1 more source
Beyond the Adult Mind: A Developmental Framework for Predictive Processing in Infancy
Abstract Predictive Processing has been proposed as the single unifying computation underlying all of cognition, and proponents argue that all psychological phenomena can be explained as consequences of this principle. This theoretical framework has inspired many cognitive scientists and neuroscientists, but it currently has no developmental mechanism ...
Emma K. Ward +4 more
wiley +1 more source
Editorial: Reviews in psychology of language. [PDF]
Benítez-Burraco A, Bova A, Spalding TL.
europepmc +1 more source
Visual Moral Inference and Communication
Abstract Humans can make moral inferences from multiple sources of input. In contrast, computational moral inference in artificial intelligence typically relies on language models with textual input. However, morality is conveyed through modalities beyond language.
Warren Zhu, Aida Ramezani, Yang Xu
wiley +1 more source
Seeing Through an Ant's Eyes: Do Entomopathogenic Fungi Extend Their Cognition to Their Hosts?
Abstract Post‐cognitivist approaches recognize cognition as a phenomenon that involves not just brains but all the sensorimotor apparatus of organisms. This means that brains are not always required for the emergence of cognition and that every organism can, in principle, be cognitive, unlocking a theoretical framework to explain the complex adaptive ...
André Geremia Parise +2 more
wiley +1 more source
AI‐Enhanced Semantic Feature Norms for 786 Concepts
Abstract Semantic feature norms have been foundational in the study of human conceptual knowledge, yet traditional methods face trade‐offs between concept/feature coverage and verifiability of quality due to the labor‐intensive nature of norming studies.
Siddharth Suresh +6 more
wiley +1 more source
AIPsychoBench: Understanding the Psychometric Differences Between LLMs and Humans
Abstract Large Language Models (LLMs) with hundreds of billions of parameters have exhibited human‐like intelligence by learning from vast amounts of internet‐scale data. However, the uninterpretability of large‐scale neural networks raises concerns about the reliability of LLM.
Wei Xie +7 more
wiley +1 more source

