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Language Models Explain Word Reading Times Better Than Empirical Predictability ...
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SCoT: Sense Clustering over Time: a tool for the analysis of lexical change ...
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Language Models Explain Word Reading Times Better Than Empirical Predictability
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In: Front Artif Intell (2022)
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Probing Pre-trained Language Models for Semantic Attributes and their Values ...
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Comparison of Different Lexical Resources With Respect to the Tip-of-the-Tongue Problem
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In: ISSN: 1598-2327 ; EISSN: 1976-6939 ; Journal of Cognitive Science ; https://hal.archives-ouvertes.fr/hal-03168850 ; Journal of Cognitive Science, Institute for Cognitive Science, Seoul National University, 2020, 21 (2), pp.193-252. ⟨10.17791/jcs.2020.21.2.193⟩ (2020)
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Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and Datasets ...
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Individual corpora predict fast memory retrieval during reading ...
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HHMM at SemEval-2019 Task 2: Unsupervised frame induction using contextualized word embeddings
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Watset: Local-global graph clustering with applications in sense and frame induction
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Between the Lines: Machine Learning for Prediction of Psychological Traits - A Survey
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In: Lecture Notes in Computer Science ; 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE) ; https://hal.inria.fr/hal-02060047 ; 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2018, Hamburg, Germany. pp.192-211, ⟨10.1007/978-3-319-99740-7_13⟩ (2018)
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Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction ...
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An unsupervised word sense disambiguation system for under-resourced languages
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Unsupervised, Knowledge-Free, and Interpretable Word Sense Disambiguation ...
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Negative Sampling Improves Hypernymy Extraction Based on Projection Learning ...
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Watset: Automatic Induction of Synsets from a Graph of Synonyms ...
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Human and Machine Judgements for Russian Semantic Relatedness ...
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Unsupervised does not mean uninterpretable : the case for word sense induction and disambiguation
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Unsupervised, knowledge-free, and interpretable word sense disambiguation
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The ContrastMedium algorithm : taxonomy induction from noisy knowledge graphs with just a few links
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