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Papers Question-Answer-Generation

“Question-Answer-Generation” 태그가 달린 논문 37편 · 필터 해제

Conversational QA Dataset Generation with Answer Revision

2022-09-23 · COLING 2022 10 · Seonjeong Hwang, Gary Geunbae Lee

Conversational question--answer generation is a task that automatically generates a large-scale conversational question answering dataset based on input passages. In this paper, we introduce a novel framework that extrac…

Answer GenerationConversational Question AnsweringDataset GenerationDomain Adaptation+2

TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation

2022-08-03 · Jun Wang, Mingfei Gao, Yuqian Hu, Ramprasaath R. Selvaraju 외

Text-VQA aims at answering questions that require understanding the textual cues in an image. Despite the great progress of existing Text-VQA methods, their performance suffers from insufficient human-labeled question-an…

Answer GenerationQuestion-Answer-GenerationScene UnderstandingTAG+2

It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books

2022-05-01 · ACL 2022 5 · Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang 외

Existing question answering (QA) techniques are created mainly to answer questions asked by humans. But in educational applications, teachers often need to decide what questions they should ask, in order to help students…

Answer GenerationQuestion-Answer-GenerationQuestion Answering

Improving Data Augmentation in Low-resource Question Answering with Active Learning in Multiple Stages

2022-01-16 · ACL ARR January 2022 1 · Anonymous

Neural approaches have become very popular in the domain of Question Answering, however they require a large amount of annotated data. Furthermore, they often yield very good performance but only in the domain they were …

Active LearningAnswer GenerationData AugmentationQuestion-Answer-Generation+1

MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding

2021-12-20 · Revanth Gangi Reddy, Xilin Rui, Manling Li, Xudong Lin 외

Recently, there has been an increasing interest in building question answering (QA) models that reason across multiple modalities, such as text and images. However, QA using images is often limited to just picking the an…

Answer GenerationArticlesData AugmentationQuestion-Answer-Generation+1

Change Detection Meets Visual Question Answering

2021-12-12 · Zhenghang Yuan, Lichao Mou, Zhitong Xiong, Xiaoxiang Zhu

The Earth's surface is continually changing, and identifying changes plays an important role in urban planning and sustainability. Although change detection techniques have been successfully developed for many years, the…

Answer GenerationChange DetectionQuestion-Answer-GenerationQuestion Answering+2

It is AI’s Turn to Ask Human a Question: Question and Answer Pair Generation for Children Storybooks in FairytaleQA Dataset

2021-11-16 · ACL ARR November 2021 11 · Anonymous

Existing question answering (QA) techniques are created mainly to answer questions asked by humans. But in educational applications, teachers and parents sometimes may not know what questions they should ask best help ch…

Answer GenerationQuestion-Answer-GenerationQuestion Answering

CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization

2021-11-01 · EMNLP 2021 11 · Arjun Akula, Soravit Changpinyo, Boqing Gong, Piyush Sharma 외

One challenge in evaluating visual question answering (VQA) models in the cross-dataset adaptation setting is that the distribution shifts are multi-modal, making it difficult to identify if it is the shifts in visual or…

Answer GenerationQuestion-Answer-GenerationQuestion AnsweringVisual Question Answering+1

Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark

2021-10-22 · Pritish Sahu, Karan Sikka, Ajay Divakaran

We focus on Multimodal Machine Reading Comprehension (M3C) where a model is expected to answer questions based on given passage (or context), and the context and the questions can be in different modalities. Previous wor…

Answer GenerationMachine Reading ComprehensionMemorizationQuestion-Answer-Generation+1

It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Books

2021-09-08 · Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang 외

Existing question answering (QA) techniques are created mainly to answer questions asked by humans. But in educational applications, teachers often need to decide what questions they should ask, in order to help students…

Answer GenerationData AugmentationLanguage ModellingQuestion-Answer-Generation+1

Towards Solving Multimodal Comprehension

2021-04-20 · Pritish Sahu, Karan Sikka, Ajay Divakaran

This paper targets the problem of procedural multimodal machine comprehension (M3C). This task requires an AI to comprehend given steps of multimodal instructions and then answer questions. Compared to vanilla machine co…

16kAnswer GenerationQuestion-Answer-GenerationQuestion Answering+1

Quiz-Style Question Generation for News Stories

2021-02-18 · Adam D. Lelkes, Vinh Q. Tran, Cong Yu

A large majority of American adults get at least some of their news from the Internet. Even though many online news products have the goal of informing their users about the news, they lack scalable and reliable tools fo…

Answer GenerationDistractor GenerationMultiple-choiceQuestion-Answer-Generation+2

End-to-End Video Question-Answer Generation with Generator-Pretester Network

2021-01-05 · Hung-Ting Su, Chen-Hsi Chang, Po-Wei Shen, Yu-Siang Wang 외

We study a novel task, Video Question-Answer Generation (VQAG), for challenging Video Question Answering (Video QA) task in multimedia. Due to expensive data annotation costs, many widely used, large-scale Video QA datas…

Answer GenerationQuestion-Answer-GenerationQuestion AnsweringQuestion Generation+3

Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs

2020-05-28 · ACL 2020 6 · Dong Bok Lee, Seanie Lee, Woo Tae Jeong, Donghwan Kim 외

One of the most crucial challenges in question answering (QA) is the scarcity of labeled data, since it is costly to obtain question-answer (QA) pairs for a target text domain with human annotation. An alternative approa…

Question-Answer-GenerationQuestion AnsweringQuestion Generation

Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

2020-01-27 · Bang Liu, Haojie Wei, Di Niu, Haolan Chen 외

The ability to ask questions is important in both human and machine intelligence. Learning to ask questions helps knowledge acquisition, improves question-answering and machine reading comprehension tasks, and helps a ch…

Answer GenerationChatbotMachine Reading ComprehensionQuestion-Answer-Generation+4

Deep Bayesian Active Learning for Multiple Correct Outputs

2019-12-02 · Khaled Jedoui, Ranjay Krishna, Michael Bernstein, Li Fei-Fei

Typical active learning strategies are designed for tasks, such as classification, with the assumption that the output space is mutually exclusive. The assumption that these tasks always have exactly one correct answer h…

Active LearningAnswer GenerationImage CaptioningQuestion-Answer-Generation+3

Training IBM Watson using Automatically Generated Question-Answer Pairs

2016-11-12 · Jangho Lee, Gyuwan Kim, Jaeyoon Yoo, Changwoo Jung 외

IBM Watson is a cognitive computing system capable of question answering in natural languages. It is believed that IBM Watson can understand large corpora and answer relevant questions more effectively than any other que…

Answer GenerationQuestion-Answer-GenerationQuestion Answering
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