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Hits 821 – 830 of 830

821
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ...
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822
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little ...
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823
A Data Bootstrapping Recipe for Low-Resource Multilingual Relation Classification ...
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824
SOM-NCSCM : An Efficient Neural Chinese Sentence Compression Model Enhanced with Self-Organizing Map ...
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825
The Low-Dimensional Linear Geometry of Contextualized Word Representations ...
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826
Data Collection vs. Knowledge Graph Completion: What is Needed to Improve Coverage? ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.501/ Abstract: This survey/position paper discusses ways to improve coverage of resources such as WordNet. Rapp estimated correlations, ρ, between corpus statistics and psycholinguistic norms. ρ improves with quantity (corpus size) and quality (balance). 1M words are enough for simple estimates (unigram frequencies), but at least 100M are required for pairs of words (word associations, edges). Knowledge Graph Completion (KGC) attempts to learn missing links in WN18. Unfortunately, WN18 is flawed with information leaking from train to test. More seriously, WN18 is based on SemCor (just 200k words) and dated (collected in 1960s). KGC cannot learn anything that happened since the 1960s, or associations requiring 100M words. ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/dye9-zt51
https://underline.io/lecture/38098-data-collection-vs.-knowledge-graph-completion-what-is-needed-to-improve-coveragequestion
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827
Linguistic Dependencies and Statistical Dependence ...
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828
Does referent predictability affect the choice of referential form? A computational approach using masked coreference resolution ...
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829
Coreference-aware Surprisal Predicts Brain Response ...
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830
Pragmatic competence of pre-trained language models through the lens of discourse connectives ...
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