natural-language-processing-7

Cloze Test

3260 papers • 126 benchmarks • 313 datasets

The cloze task refers to infilling individual words.

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Benchmarks

These leaderboards are used to track progress in cloze-test-7

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CodeXGLUE - CT-all

CodeXGLUE - CT-maxmin

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CodeXGLUE

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Most implemented papers

Bidirectional Attention Flow for Machine Comprehension

Ali Farhadi, Aniruddha Kembhavi, Minjoon Seo, Hannaneh Hajishirzi•Thu Nov 03 2016

The BIDAF network is introduced, a multi-stage hierarchical process that represents the context at different levels of granularity and uses bi-directional attention flow mechanism to obtain a query-aware context representation without early summarization.

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ERNIE: Enhanced Representation through Knowledge Integration

Hua Wu, Shuohuan Wang, Yu Sun, Hao Tian, Han Zhang, Yukun Li, Shikun Feng, Xuyi Chen, Xin Tian, Danxiang Zhu•Thu Apr 18 2019

Experimental results show that ERNIE outperforms other baseline methods, achieving new state-of-the-art results on five Chinese natural language processing tasks including natural language inference, semantic similarity, named entity recognition, sentiment analysis and question answering.

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CPM: A Large-scale Generative Chinese Pre-trained Language Model

Jie Tang, Xu Han, Minlie Huang, Zhiyuan Liu, Juan-Zi Li, Hao Zhou, Xiaoyan Zhu, Maosong Sun, Fanchao Qi, Jian Guan, Xiaozhi Wang, Yujia Qin, Pei Ke, Yuxian Gu, Guoyang Zeng, Deming Ye, Yanan Zheng, Zhengyan Zhang, Yusheng Su, Haozhe Ji, Huanqi Cao, S. Chen, Daixuan Li, Zhenbo Sun, Wentao Han•Mon Nov 30 2020

CPM, with 2.6 billion parameters and 100GB Chinese training data, is the largest Chinese pre-trained language model, which could facilitate several downstream Chinese NLP tasks, such as conversation, essay generation, cloze test, and language understanding.

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CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin B. Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, Shujie Liu•Mon Feb 08 2021

This paper introduces CodeXGLUE, a benchmark dataset to foster machine learning research for program understanding and generation that includes a collection of 10 tasks across 14 datasets and a platform for model evaluation and comparison.

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LSDSem 2017: Exploring Data Generation Methods for the Story Cloze Test

Iryna Gurevych, Maxime Peyrard, M. Bugert, Yevgeniy Puzikov, Andrea Rückle, Judith Eckle-Kohler, Teresa Martin, Eugenio Martínez-Cámara, Daniil Sorokin•Fri Mar 31 2017

This work presents a system based on a deep learning architecture combined with a rich set of manually-crafted linguistic features that outperforms all known baselines for the Story Cloze test, suggesting that the chosen approach is promising.

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Narrative Modeling with Memory Chains and Semantic Supervision

Timothy Baldwin, Trevor Cohn, Fei Liu•Mon Apr 30 2018

A novel method, tracking various semantic aspects with external neural memory chains while encouraging each to focus on a particular semantic aspect of the narrative, demonstrates superior performance to a collection of competitive baselines, setting a new state of the art.

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Chengyu Cloze Test

Lifu Huang, Boliang Zhang, Heng Ji, Zhiying Jiang•Thu May 31 2018

A neural recommendation model for Chengyu, which is a special type of Chinese idiom, is presented, which achieves 89.5% accuracy on cloze test and outperforms human subjects who attended competitive universities in China.

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Asking the Right Question: Inferring Advice-Seeking Intentions from Personal Narratives

Liye Fu, Jonathan P. Chang, Cristian Danescu-Niculescu-Mizil•Sun Mar 31 2019

This work introduces the new task of inferring what is the advice-seeking goal behind a personal narrative, and uses human annotation to determine the degree to which the task relies on common sense and social intuition in addition to a semantic understanding of the narrative.

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ChID: A Large-scale Chinese IDiom Dataset for Cloze Test

Aixin Sun, Minlie Huang, Chujie Zheng•Mon Jun 03 2019

A large-scale Chinese cloze test dataset ChID is proposed, which studies the comprehension of idiom, a unique language phenomenon in Chinese, in which the idioms in a passage are replaced by blank symbols and the correct answer needs to be chosen from well-designed candidate idioms.

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