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KARNA at COIN Shared Task 1: Bidirectional Encoder Representations from Transformers with relational knowledge for machine comprehension with common sense

机译：Coin共享任务1：来自变压器的双向编码器表示具有常识机器理解的关系知识

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Yash Jain; Chinmay Singh;
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年度 2019
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1. Enhancing Transformer-based language models with commonsense representations for knowledge-driven machine comprehension [J] . Li Ronghan, Jiang Zejun, Wang Lifang, Knowledge-Based Systems . 2021,第MAYa23期

机译：通过用于知识驱动的机器理解的致致通知表示，增强基于变压器的语言模型
2. Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study [J] . Klaus Kades, Jan Sellner, Gregor Koehler, JMIR Medical Informatics . 2021,第2期

机译：使用变压器（BERT）的双向编码器表示来评估临床语义文本相似性：算法开发和验证研究
3. Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers [J] . Nakamura Yuta, Hanaoka Shouhei, Nomura Yukihiro, BMC Medical Informatics and Decision Making . 2021,第1期

机译：使用来自变压器的双向编码器表示的自动检测可操作放射学报告
4. KARNA at COIN Shared Task 1: Bidirectional Encoder Representations from Transformers with relational knowledge for machine comprehension with common sense [C] . Yash Jain, Chinmay Singh Workshop on Commonsense inference in natural language processing . 2019

机译：KARNA在COIN上共享任务1：来自变压器的双向编码器表示，具有相关知识，具有常识性的机器理解
5. Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization [O] . Dongfang Xu, Manoj Gopale, Jiacheng Zhang, 2020

机译：统一的医疗语言系统资源改善了从变压器（BERT）的基于筛的生成和双向编码器表示为概念标准化排名
6. Pingan Smart Health and SJTU at COIN - Shared Task: utilizing Pre-trained Language Models and Common-sense Knowledge in Machine Reading Tasks [O] . Xiepeng Li, Zhexi Zhang, Wei Zhu, 2019

机译：COIN共享任务的平安智能健康与SJTU：利用预先训练的语言模型和机器阅读任务中的常见知识
7. The Representation and Selection of Commonsense Knowledge for Natural Language Comprehension. [R] . Rieger, C. 1976

机译：自然语言理解常识知识的表征与选择。

KARNA at COIN Shared Task 1: Bidirectional Encoder Representations from Transformers with relational knowledge for machine comprehension with common sense

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