Answer Generation

39 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering

Hanlard/Bert-for-WebQA 21 Jul 2016

While question answering (QA) with neural network, i. e. neural QA, has achieved promising results in recent years, lacking of large scale real-word QA dataset is still a challenge for developing and evaluating neural QA system.

VOGUE: Answer Verbalization through Multi-Task Learning

endrikacupaj/VOGUE 24 Jun 2021

The VOGUE framework attempts to generate a verbalized answer using a hybrid approach through a multi-task learning paradigm.

ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering System

umanlp/zusammenqa NAACL (MIA) 2022

This paper introduces our proposed system for the MIA Shared Task on Cross-lingual Open-retrieval Question Answering (COQA).

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

bangliu/ACS-QG 27 Jan 2020

In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.

LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering

Aishwarya-NR/LRTA_Perturbed_Dataset 21 Nov 2020

We show that LRTA makes a step towards truly understanding the question while the state-of-the-art model tends to learn superficial correlations from the training data.

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

WorkInTheDark/FairytaleQA_QAG_System 8 Sep 2021

Existing question answering (QA) techniques are created mainly to answer questions asked by humans.

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

uiucnlp/mumuqa 20 Dec 2021

Specifically, the task involves multi-hop questions that require reasoning over image-caption pairs to identify the grounded visual object being referred to and then predicting a span from the news body text to answer the question.

R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering

shuohangwang/mprc 31 Aug 2017

Second, we propose a novel method that jointly trains the Ranker along with an answer-generation Reader model, based on reinforcement learning.

Product-Aware Answer Generation in E-Commerce Question-Answering

gsh199449/productqa 23 Jan 2019

In this paper, we propose the task of product-aware answer generation, which tends to generate an accurate and complete answer from large-scale unlabeled e-commerce reviews and product attributes.