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Making Neural QA as Simple as Possible but not Simpler

Making Neural QA as Simple as Possible but not Simpler

14 March 2017
Dirk Weissenborn
Georg Wiese
Laura Seiffe
ArXivPDFHTML

Papers citing "Making Neural QA as Simple as Possible but not Simpler"

35 / 35 papers shown
Title
TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya
TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya
Hailay Teklehaymanot
Dren Fazlija
Niloy Ganguly
Gourab K. Patro
Wolfgang Nejdl
34
0
0
26 Apr 2024
How the Advent of Ubiquitous Large Language Models both Stymie and
  Turbocharge Dynamic Adversarial Question Generation
How the Advent of Ubiquitous Large Language Models both Stymie and Turbocharge Dynamic Adversarial Question Generation
Yoo Yeon Sung
Ishani Mondal
Jordan L. Boyd-Graber
30
0
0
20 Jan 2024
Self-Supervised Position Debiasing for Large Language Models
Self-Supervised Position Debiasing for Large Language Models
Zhongkun Liu
Zheng Chen
Mengqi Zhang
Zhaochun Ren
Pengjie Ren
Zhumin Chen
36
1
0
02 Jan 2024
Learning to Generalize for Cross-domain QA
Learning to Generalize for Cross-domain QA
Yingjie Niu
Linyi Yang
Ruihai Dong
Yue Zhang
18
6
0
14 May 2023
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on
  Multi-hop Machine Reading Comprehension
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension
Peng Gao
Feng Gao
Jiancheng Ni
Yu Wang
Fei-Yue Wang
22
2
0
19 Dec 2022
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about
  Negation
CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation
Abhilasha Ravichander
Matt Gardner
Ana Marasović
33
34
0
01 Nov 2022
To Answer or Not to Answer? Improving Machine Reading Comprehension
  Model with Span-based Contrastive Learning
To Answer or Not to Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning
Yunjie Ji
Liangyu Chen
Chenxiao Dou
Baochang Ma
Xiangang Li
43
5
0
02 Aug 2022
Design and Development of Rule-based open-domain Question-Answering
  System on SQuAD v2.0 Dataset
Design and Development of Rule-based open-domain Question-Answering System on SQuAD v2.0 Dataset
Pragya Katyayan
Nisheeth Joshi
18
6
0
27 Mar 2022
An Automated Question-Answering Framework Based on Evolution Algorithm
An Automated Question-Answering Framework Based on Evolution Algorithm
Sinan Tan
Hui Xue
Qiyu Ren
Huaping Liu
Jing Bai
16
0
0
26 Jan 2022
Models in the Loop: Aiding Crowdworkers with Generative Annotation
  Assistants
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants
Max Bartolo
Tristan Thrush
Sebastian Riedel
Pontus Stenetorp
Robin Jia
Douwe Kiela
24
33
0
16 Dec 2021
QuALITY: Question Answering with Long Input Texts, Yes!
QuALITY: Question Answering with Long Input Texts, Yes!
Richard Yuanzhe Pang
Alicia Parrish
Nitish Joshi
Nikita Nangia
Jason Phang
...
Vishakh Padmakumar
Johnny Ma
Jana Thompson
He He
Sam Bowman
RALM
25
141
0
16 Dec 2021
Interactive Machine Comprehension with Dynamic Knowledge Graphs
Interactive Machine Comprehension with Dynamic Knowledge Graphs
Xingdi Yuan
34
3
0
31 Aug 2021
Biomedical Question Answering: A Survey of Approaches and Challenges
Biomedical Question Answering: A Survey of Approaches and Challenges
Qiao Jin
Zheng Yuan
Guangzhi Xiong
Qian Yu
Huaiyuan Ying
Chuanqi Tan
Mosha Chen
Songfang Huang
Xiaozhong Liu
Sheng Yu
23
95
0
10 Feb 2021
ERICA: Improving Entity and Relation Understanding for Pre-trained
  Language Models via Contrastive Learning
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning
Yujia Qin
Yankai Lin
Ryuichi Takanobu
Zhiyuan Liu
Peng Li
Heng Ji
Minlie Huang
Maosong Sun
Jie Zhou
55
125
0
30 Dec 2020
Tradeoffs in Sentence Selection Techniques for Open-Domain Question
  Answering
Tradeoffs in Sentence Selection Techniques for Open-Domain Question Answering
Shih-Ting Lin
Greg Durrett
28
1
0
18 Sep 2020
MA-DST: Multi-Attention Based Scalable Dialog State Tracking
MA-DST: Multi-Attention Based Scalable Dialog State Tracking
Adarsh Kumar
Peter Ku
Anuj Kumar Goyal
A. Metallinou
Dilek Z. Hakkani-Tür
27
58
0
07 Feb 2020
Beat the AI: Investigating Adversarial Human Annotation for Reading
  Comprehension
Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension
Max Bartolo
A. Roberts
Johannes Welbl
Sebastian Riedel
Pontus Stenetorp
AAML
26
167
0
02 Feb 2020
A Survey on Machine Reading Comprehension Systems
A Survey on Machine Reading Comprehension Systems
Razieh Baradaran
Razieh Ghiasi
Hossein Amirkhani
FaML
13
85
0
06 Jan 2020
Contextualized Sparse Representations for Real-Time Open-Domain Question
  Answering
Contextualized Sparse Representations for Real-Time Open-Domain Question Answering
Jinhyuk Lee
Minjoon Seo
Hannaneh Hajishirzi
Jaewoo Kang
RALM
LRM
13
31
0
07 Nov 2019
What Question Answering can Learn from Trivia Nerds
What Question Answering can Learn from Trivia Nerds
Jordan L. Boyd-Graber
Benjamin Borschinger
21
36
0
31 Oct 2019
An Empirical Study of Content Understanding in Conversational Question
  Answering
An Empirical Study of Content Understanding in Conversational Question Answering
Ting-Rui Chiang
Hao-Tong Ye
Yun-Nung (Vivian) Chen
ELM
23
8
0
24 Sep 2019
Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with
  Multi-lingual Language Representation Model
Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model
Tsung-Yuan Hsu
Chi-Liang Liu
Hung-yi Lee
26
60
0
15 Sep 2019
ELI5: Long Form Question Answering
ELI5: Long Form Question Answering
Angela Fan
Yacine Jernite
Ethan Perez
David Grangier
Jason Weston
Michael Auli
AI4MH
ELM
17
592
0
22 Jul 2019
Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop
  Reading Comprehension
Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
Yichen Jiang
Nitish Joshi
Yen-Chun Chen
Joey Tianyi Zhou
RALM
13
39
0
12 Jun 2019
Neural Approaches to Conversational AI
Neural Approaches to Conversational AI
Jianfeng Gao
Michel Galley
Lihong Li
37
668
0
21 Sep 2018
Multi-task Learning with Sample Re-weighting for Machine Reading
  Comprehension
Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension
Yichong Xu
Xiaodong Liu
Yelong Shen
Jingjing Liu
Jianfeng Gao
19
51
0
18 Sep 2018
The price of debiasing automatic metrics in natural language evaluation
The price of debiasing automatic metrics in natural language evaluation
Arun Tejasvi Chaganty
Stephen Mussmann
Percy Liang
11
113
0
06 Jul 2018
Jack the Reader - A Machine Reading Framework
Jack the Reader - A Machine Reading Framework
Dirk Weissenborn
Pasquale Minervini
Tim Dettmers
Isabelle Augenstein
Johannes Welbl
...
Matko Bosnjak
Jeff Mitchell
Thomas Demeester
Pontus Stenetorp
Sebastian Riedel
14
13
0
20 Jun 2018
QANet: Combining Local Convolution with Global Self-Attention for
  Reading Comprehension
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension
Adams Wei Yu
David Dohan
Minh-Thang Luong
Rui Zhao
Kai Chen
Mohammad Norouzi
Quoc V. Le
RALM
AIMat
35
1,091
0
23 Apr 2018
FusionNet: Fusing via Fully-Aware Attention with Application to Machine
  Comprehension
FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension
Hsin-Yuan Huang
Chenguang Zhu
Yelong Shen
Weizhu Chen
FedML
30
183
0
16 Nov 2017
Dynamic Fusion Networks for Machine Reading Comprehension
Dynamic Fusion Networks for Machine Reading Comprehension
Yichong Xu
Jingjing Liu
Jianfeng Gao
Yelong Shen
Xiaodong Liu
AIMat
AI4CE
39
29
0
14 Nov 2017
Adversarial Examples for Evaluating Reading Comprehension Systems
Adversarial Examples for Evaluating Reading Comprehension Systems
Robin Jia
Percy Liang
AAML
ELM
95
1,578
0
23 Jul 2017
Neural Domain Adaptation for Biomedical Question Answering
Neural Domain Adaptation for Biomedical Question Answering
Georg Wiese
Dirk Weissenborn
Mariana Neves
MedIm
OOD
35
112
0
12 Jun 2017
Reinforced Mnemonic Reader for Machine Reading Comprehension
Reinforced Mnemonic Reader for Machine Reading Comprehension
Minghao Hu
Yuxing Peng
Zhen Huang
Xipeng Qiu
Furu Wei
Ming Zhou
RALM
AIMat
19
69
0
08 May 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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