Papers by Nikos Athanasiou

2 papers
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activations (C18-1)

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Challenge: Neural activation models have been proposed to map word semantics to localized neural activations.
Approach: They propose a computational model that estimates semantic similarity in the neural activation space and investigate its performance for various natural language processing tasks.
Outcome: The proposed model performs better than state-of-the-art word embeddings for the task of semantic similarity estimation between very similar or very dissimilar words while performing well on other tasks such as entailment and word categorization.
Cross-Topic Distributional Semantic Representations Via Unsupervised Mappings (N19-1)

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Challenge: Existing distributional semantic models cannot capture the distinct meanings of polysemous words, resulting in conflated word representations of diverse contextual semantics.
Approach: They propose a distributional semantic model that learns multiple representations of a word based on different topics.
Outcome: The proposed model outperforms single-prototype models on NLP downstream tasks.

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