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Found 10 papers, 0 papers with code
Decoding Brain Activity Associated with Literal and Metaphoric Sentence Comprehension Using Distributional Semantic Models
We evaluate a range of semantic models (word embeddings, compositional, and visual models) in their ability to decode brain activity associated with reading of both literal and metaphoric sentences.
Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models
Recent work shows that distributional semantic models can be used to decode patterns of brain activity associated with individual words and sentence meanings.
Deconstructing multimodality: visual properties and visual context in human semantic processing
Multimodal semantic models that extend linguistic representations with additional perceptual input have proved successful in a range of natural language processing (NLP) tasks.
Grasping the Finer Point: A Supervised Similarity Network for Metaphor Detection
The ubiquity of metaphor in our everyday communication makes it an important problem for natural language understanding.
Speaking, Seeing, Understanding: Correlating semantic models with conceptual representation in the brain
Research in computational semantics is increasingly guided by our understanding of human semantic processing.
Learning to Negate Adjectives with Bilinear Models
We learn a mapping that negates adjectives by predicting an adjective{'}s antonym in an arbitrary word embedding model.
Modelling metaphor with attribute-based semantics
One of the key problems in computational metaphor modelling is finding the optimal level of abstraction of semantic representations, such that these are able to capture and generalise metaphorical mechanisms.
Virtual Embodiment: A Scalable Long-Term Strategy for Artificial Intelligence Research
Meaning has been called the "holy grail" of a variety of scientific disciplines, ranging from linguistics to philosophy, psychology and the neurosciences.
