AIMC Topic: Comprehension

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Human cognition and the AI revolution.

Annals of the New York Academy of Sciences
Discovering the true nature of reality may ultimately hinge on grasping the nature and essence of human understanding. What are the fundamental elements or building blocks of human cognition? And how will the rise of superintelligent machines challen...

Meaning-driven syntactic predictions in a parallel processing architecture: Theory and algorithmic modeling of ERP effects.

Neuropsychologia
Syntactic and semantic information processing can interact selectively during language comprehension. However, the nature and extent of the interactions, in particular of semantic effects on syntax, remain to some extent elusive. We revisit an influe...

Scalable deep text comprehension for Cancer surveillance on high-performance computing.

BMC bioinformatics
BACKGROUND: Deep Learning (DL) has advanced the state-of-the-art capabilities in bioinformatics applications which has resulted in trends of increasingly sophisticated and computationally demanding models trained by larger and larger data sets. This ...

Building a knowledge base: Predicting self-derivation through integration in 6- to 10-year-olds.

Journal of experimental child psychology
Self-derivation of new factual knowledge through integration of separate episodes of learning is one means by which children build knowledge. Content generated in this manner becomes incorporated into the knowledge base and is retained over time; suc...

Confidence in uncertainty: Error cost and commitment in early speech hypotheses.

PloS one
Interactions with artificial agents often lack immediacy because agents respond slower than their users expect. Automatic speech recognisers introduce this delay by analysing a user's utterance only after it has been completed. Early, uncertain hypot...

Lost in translation.

F1000Research
Translation in cognitive neuroscience remains beyond the horizon, brought no closer by supposed major advances in our understanding of the brain. Unless our explanatory models descend to the individual level-a cardinal requirement for any interventio...

Predict, then simplify.

NeuroImage
The desire to understand a given phenomenon is at the core of a scientist's mission. Yet what is meant by "understanding"? As soon as we try to operationalize this concept, I argue that understanding amounts to building models of a set of related emp...

Predicting the sources of impaired wh-question comprehension in non-fluent aphasia: A cross-linguistic machine learning study on Turkish and German.

Cognitive neuropsychology
This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-po...

Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

Brain and language
Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks ...