Analysis of 2020 Accepted Papers(ACL, EMNLP) using N-Gram
NGram(paper_2020_list).ngram(2).gram_freq_sorted[:10] ('neural machine', 59),
('language models', 59),
('natural language', 50),
('question answering', 46),
('for neural', 32),
('learning to', 32),
('model for', 31),
('learning for', 30),
('text classification', 24)]
NGram(paper_2020_list,2).showTitles('generation with')[:3]['Diverse and Informative Dialogue Generation with Context-Specific Commonsense Knowledge Awareness',
'Diversifying Dialogue Generation with Non-Conversational Text',
'Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder']
MIT License