[PDF] Top 20 Multi Task Learning with Language Modeling for Question Generation
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Multi Task Learning with Language Modeling for Question Generation
... our multi-task learn- ing model: with/without language modeling and with/without ...the language modeling consistently yields ob- vious performance gain over baselines, for all ... See full document
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Code Switching Language Modeling using Syntax Aware Multi Task Learning
... First, multi-task learning model is pro- posed to jointly learn language modeling task and POS sequence tagging task on code-switched ut- ...incorporate language ... See full document
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Multi task Learning for Natural Language Generation in Task Oriented Dialogue
... the language modeling task as an ablation study, denoted by w/o ...guage modeling can improve the result by ...of multi-task ... See full document
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Multi Task Learning for Coherence Modeling
... its modeling is essen- tial in many NLP applications, including sum- marization (Barzilay et ...2016), question-answering (Verberne et al., 2007), question generation (Desai et ... See full document
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Soft Layer Specific Multi Task Summarization with Entailment and Question Generation
... via multi-task learning with the auxiliary tasks of question generation and entailment generation, where the former teaches the summarization model how to look for salient ... See full document
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Dialog Generation Using Multi Turn Reasoning Neural Networks
... 2015). Learning-to-rank approaches were applied to compute the similarity scores of between (query, context) and indexed candidate (question, answer) pairs to return the optimal “an- swer” to the ...source ... See full document
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Pentagon at MEDIQA 2019: Multi task Learning for Filtering and Re ranking Answers using Language Inference and Question Entailment
... shared task leader- board. For Task 1, i.e. the NLI task, we achieved an accuracy of ...For Task 2, i.e. the RQE task, we observed that the test set var- ied greatly as compared to the ... See full document
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DUT NLP at MEDIQA 2019: An Adversarial Multi Task Network to Jointly Model Recognizing Question Entailment and Question Answering
... Adversarial Multi-Task Network (AMTN) for jointly modeling Recognizing Question Entailment (RQE) and medical Question Answering (QA) ...different task through parameter sharing ... See full document
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Question Generation for Language Learning: From ensuring texts are read to supporting learning
... Second Language Acquisi- tion (SLA) research since the 90s has emphasized that language input and meaning-based tasks alone are not sufficient to ensure successful language ...the language as ... See full document
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ELI5: Long Form Question Answering
... The multi- task Seq2Seq experiment, in which the Seq2Seq decoder is trained to predict the question and the document, in addition to the answer, can reach the same perplexity as the language ... See full document
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MappSent at IJCNLP 2017 Task 5: A Textual Similarity Approach Applied to Multi choice Question Answering in Examinations
... natural language processing (NLP) ...the language in terms of lexical, semantic and pragmatic ...deep learning approaches ranging from a word level embedding representation (Bengio et ... See full document
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The First Question Generation Shared Task Evaluation Challenge
... Shared Task Evaluation Challenge on Question Generation (QG-STEC) follows a long tradition of STECs in Natural Language Processing (see the annual tasks run by the Conference on Natural ... See full document
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Language Modeling for Document Selection in Question Answering
... all question classes, which could be sub-optimal lo- cally, ...this question class by almost 3% of ...each question class) seemed then to be more ... See full document
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Mobile Edge Computing Task Placement Strategy Based on NSGA II
... based task placement strategy in the same environment, this paper uses two strategies to place experiments on 100 ...the task placement strategy based on NSGA-II is better able to determine the current load ... See full document
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Interactive Language Learning by Question Answering
... Templated Language: As QAit is based on TextWorld, it has the obvious limitation of us- ing templated ...natural language, on which we can isolate the learning of useful behaviors like infor- mation ... See full document
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Learning to Automatically Generate Fill In The Blank Quizzes
... fill-in-the-blank question genera- tion has been studied in the past by several ...cloze question generation system which focuses on distractor generation us- ing search engines to ... See full document
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Mandarin Students' Perceptions of Smartphone Applications in Mandarin Learning
... where learning happens ...mobile-assisted language learning (MALL) encourages personalized learning is the ...Mandarin learning tools have not yet explored ...and learning based ... See full document
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Hierarchical Reinforcement Learning and Hidden Markov Models for Task Oriented Natural Language Generation
... Natural Language Generation (NLG) system are often made accord- ing to a language model of the domain (Langkilde and Knight, 1998; Bangalore and Rambow, 2000; Oh and Rudnicky, 2000; White, 2004; ... See full document
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YNUDLG at IJCNLP 2017 Task 5: A CNN LSTM Model with Attention for Multi choice Question Answering in Examinations
... a question answer learning model, CNN-LSTM with attention for Multi-choice in ...True question answer is complex, there is a need to take into account other features such similarity overlap ... See full document
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A Multi task Learning Approach to Adapting Bilingual Word Embeddings for Cross lingual Named Entity Recognition
... Cross-lingual transfer is an important technique for building natural language processing (NLP) systems for low-resource languages, where la- beled examples are scarce. The main idea is to transfer labels or ... See full document
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