Titlebook: Chinese ComputationalLinguistics; 20th China National Sheng Li,Maosong Sun,Gaoqi Rao Conference proceedings 2021 Springer Nature Switzerla

種子

From Learning-to-Match to Learning-to-Discriminate: Global Prototype Learning for Few-shot Relation on classification. Most previous works on few-shot relation classification are based on learning-to-match paradigms, which focus on learning an effective universal matcher between the query and . target class prototype based on inner-class support sets. However, the learning-to-match paradigm focuse

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后天習(xí)得

Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domains clustering. A group of people tend to express their opinion or report news around one topic. Having realized this, we propose a novel method that utilizes the topic knowledge implied by the clustered messages to aid in the comprehension of those short messages. The experiments on TweetQA datasets demonstrate the effectiveness of our method.

帶子

Conference proceedings 2021s, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications. .

中古

0302-9743 nt Analysis, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications. .978-3-030-84185-0978-3-030-84186-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Reducing Length Bias in Scoring Neural Machine Translation via a Causal Inference Methodupervised, which is adaptive to any NMT model and test dataset. We conduct the experiments on three translation tasks with different scales of datasets. Experimental results and further analyses show that our approaches gain comparable performance with the empirical baseline methods.

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