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Found 15 papers, 3 papers with code
Language Models Explain Word Reading Times Better Than Empirical Predictability
(3) In recurrent neural networks (RNNs), the subsymbolic units are trained to predict the next word, given all preceding words in the sentences.
Word Sense Disambiguation for 158 Languages using Word Embeddings Only
We use this method to induce a collection of sense inventories for 158 languages on the basis of the original pre-trained fastText word embeddings by Grave et al. (2018), enabling WSD in these languages.
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
Since vectors of the same word type can vary depending on the respective context, they implicitly provide a model for word sense disambiguation (WSD).
Hierarchical Multi-label Classification of Text with Capsule Networks
Capsule networks have been shown to demonstrate good performance on structured data in the area of visual inference.
LT Expertfinder: An Evaluation Framework for Expert Finding Methods
Particularly for dynamic systems, where topics are not predefined but formulated as a search query, we believe a more informative approach is to perform user studies for directly comparing different methods in the same view.
Entity-Centric Information Access with Human in the Loop for the Biomedical Domain
In this paper, we describe the concept of entity-centric information access for the biomedical domain.
Domain-Specific Corpus Expansion with Focused Webcrawling
This work presents a straightforward method for extending or creating in-domain web corpora by focused webcrawling.
