Search Results for author: Haejun Lee

Found 8 papers, 2 papers with code

Learning to Generate Questions by Recovering Answer-containing Sentences

no code implementations1 Jan 2021 Seohyun Back, Akhil Kedia, Sai Chetan Chinthakindi, Haejun Lee, Jaegul Choo

We evaluate our method against existing ones in terms of the quality of generated questions as well as the fine-tuned MRC model accuracy after training on the data synthetically generated by our method.

Ranked #4 on Question Generation on SQuAD1.1 (using extra training data)

Machine Reading Comprehension Question Answering +1

SLM: Learning a Discourse Language Representation with Sentence Unshuffling

no code implementations EMNLP 2020 Haejun Lee, Drew A. Hudson, Kangwook Lee, Christopher D. Manning

We introduce Sentence-level Language Modeling, a new pre-training objective for learning a discourse language representation in a fully self-supervised manner.

Language Modelling

NeurQuRI: Neural Question Requirement Inspector for Answerability Prediction in Machine Reading Comprehension

no code implementations ICLR 2020 Seohyun Back, Sai Chetan Chinthakindi, Akhil Kedia, Haejun Lee, Jaegul Choo

Real-world question answering systems often retrieve potentially relevant documents to a given question through a keyword search, followed by a machine reading comprehension (MRC) step to find the exact answer from them.

Machine Reading Comprehension Question Answering

On-Device Neural Language Model Based Word Prediction

1 code implementation COLING 2018 Seunghak Yu, Nilesh Kulkarni, Haejun Lee, Jihie Kim

Recent developments in deep learning with application to language modeling have led to success in tasks of text processing, summarizing and machine translation.

Language Modelling Machine Translation +3

Syllable-level Neural Language Model for Agglutinative Language

no code implementations WS 2017 Seunghak Yu, Nilesh Kulkarni, Haejun Lee, Jihie Kim

Language models for agglutinative languages have always been hindered in past due to myriad of agglutinations possible to any given word through various affixes.

Language Modelling

An Embedded Deep Learning based Word Prediction

1 code implementation6 Jul 2017 Seunghak Yu, Nilesh Kulkarni, Haejun Lee, Jihie Kim

Recent developments in deep learning with application to language modeling have led to success in tasks of text processing, summarizing and machine translation.

Language Modelling Machine Translation

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