SQuAD2.0

The Stanford Question Answering Dataset

What is SQuAD?

Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.


SQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but also determine when no answer is supported by the paragraph and abstain from answering.

Explore SQuAD2.0 and model predictionsSQuAD2.0 paper (Rajpurkar & Jia et al. '18)

SQuAD 1.1, the previous version of the SQuAD dataset, contains 100,000+ question-answer pairs on 500+ articles.

Explore SQuAD1.1 and model predictionsSQuAD1.0 paper (Rajpurkar et al. '16)

Getting Started

We've built a few resources to help you get started with the dataset.

Download a copy of the dataset (distributed under the CC BY-SA 4.0 license):

To evaluate your models, we have also made available the evaluation script we will use for official evaluation, along with a sample prediction file that the script will take as input. To run the evaluation, use python evaluate-v2.0.py <path_to_dev-v2.0> <path_to_predictions>.

Once you have a built a model that works to your expectations on the dev set, you submit it to get official scores on the dev and a hidden test set. To preserve the integrity of test results, we do not release the test set to the public. Instead, we require you to submit your model so that we can run it on the test set for you. Here's a tutorial walking you through official evaluation of your model:

Submission Tutorial

Because SQuAD is an ongoing effort, we expect the dataset to evolve.

To keep up to date with major changes to the dataset, please subscribe:

Have Questions?

Ask us questions at our google group or at pranavsr@stanford.edu and robinjia@stanford.edu.

Star

Leaderboard

SQuAD2.0 tests the ability of a system to not only answer reading comprehension questions, but also abstain when presented with a question that cannot be answered based on the provided paragraph.

RankModelEMF1
Human Performance

Stanford University

(Rajpurkar & Jia et al. '18)
86.83189.452

1

Nov 06, 2019
ALBERT + DAAF + Verifier (ensemble)

PINGAN Omni-Sinitic

90.00292.425

2

Sep 18, 2019
ALBERT (ensemble model)

Google Research & TTIC

https://arxiv.org/abs/1909.11942
89.73192.215

3

Jul 22, 2019
XLNet + DAAF + Verifier (ensemble)

PINGAN Omni-Sinitic

88.59290.859

3

Nov 22, 2019
albert+verifier (single model)

Ping An Life Insurance Company AI Team

88.35591.019

4

Sep 16, 2019
ALBERT (single model)

Google Research & TTIC

https://arxiv.org/abs/1909.11942
88.10790.902

4

Jul 26, 2019
UPM (ensemble)

Anonymous

88.23190.713

5

Aug 04, 2019
XLNet + SG-Net Verifier (ensemble)

Shanghai Jiao Tong University & CloudWalk

https://arxiv.org/abs/1908.05147
88.17490.702

6

Nov 15, 2019
XLNet (single model)

Google Brain & CMU

87.92690.689

7

Aug 04, 2019
XLNet + SG-Net Verifier++ (single model)

Shanghai Jiao Tong University & CloudWalk

https://arxiv.org/abs/1908.05147
87.23890.071

8

Jul 26, 2019
UPM (single model)

Anonymous

87.19389.934

8

Nov 27, 2019
RoBERTa+Verify (ensemble)

CW

86.93390.037

8

Mar 20, 2019
BERT + DAE + AoA (ensemble)

Joint Laboratory of HIT and iFLYTEK Research

87.14789.474

8

Jul 20, 2019
RoBERTa (single model)

Facebook AI

86.82089.795

9

Sep 12, 2019
RoBERTa+Span (ensemble)

CW

86.65189.595

10

Nov 12, 2019
RoBERTa+Verify (single model)

CW

86.44889.586

10

Mar 15, 2019
BERT + ConvLSTM + MTL + Verifier (ensemble)

Layer 6 AI

86.73089.286

11

Mar 05, 2019
BERT + N-Gram Masking + Synthetic Self-Training (ensemble)

Google AI Language

https://github.com/google-research/bert
86.67389.147

12

Oct 16, 2019
Xlnet+Verifier

single model

86.59489.082

13

Aug 30, 2019
Xlnet+Verifier (single model)

Ping An Life Insurance Company AI Team

86.57289.063

13

Sep 30, 2019
XLNET-123 (single model)

MST/EOI

http://tia.today
86.43689.086

13

May 21, 2019
XLNet (single model)

Google Brain & CMU

86.34689.133

14

May 14, 2019
SG-Net (ensemble)

Shanghai Jiao Tong University

https://arxiv.org/abs/1908.05147
86.21188.848

14

Apr 13, 2019
SemBERT (ensemble)

Shanghai Jiao Tong University

https://arxiv.org/abs/1909.02209
86.16688.886

14

Sep 29, 2019
BERTSP (single model)

NEUKG

http://www.techkg.cn/--please
85.83888.921

15

Oct 14, 2019
SENSEFORTH + XLNet (single model)

Senseforth AI Research

https://www.senseforth.ai
85.82788.699

15

Mar 16, 2019
BERT + DAE + AoA (single model)

Joint Laboratory of HIT and iFLYTEK Research

85.88488.621

15

Jul 22, 2019
SpanBERT (single model)

FAIR & UW

85.74888.709

16

May 14, 2019
SG-Net (single model)

Shanghai Jiao Tong University

https://arxiv.org/abs/1908.05147
85.22987.926

16

Mar 13, 2019
BERT + ConvLSTM + MTL + Verifier (single model)

Layer 6 AI

84.92488.204

16

Mar 05, 2019
BERT + N-Gram Masking + Synthetic Self-Training (single model)

Google AI Language

https://github.com/google-research/bert
85.15087.715

16

Jun 19, 2019
BNDVnet (single model)

PAOS

85.00387.833

16

Jan 15, 2019
BERT + MMFT + ADA (ensemble)

Microsoft Research Asia

85.08287.615

16

Apr 11, 2019
SemBERT (single model)

Shanghai Jiao Tong University

https://arxiv.org/abs/1909.02209
84.80087.864

16

Sep 13, 2019
xlnet (single model)

VerifiedXiaoPAI

84.64288.000

16

Apr 16, 2019
Insight-baseline-BERT (single model)

PAII Insight Team

84.83487.644

17

Sep 03, 2019
Hanvon_model (single model)

Hanvon_WuHan

84.72187.117

18

Jan 10, 2019
BERT + Synthetic Self-Training (ensemble)

Google AI Language

https://github.com/google-research/bert
84.29286.967

19

Nov 08, 2019
BERT + Multiple-CNN (ensemble)

Kyonggi University (ICL) & KISTI

84.20286.767

20

Jul 22, 2019
Tuned BERT-1seq Large Cased (single model)

FAIR & UW

83.75186.594

21

Mar 20, 2019
Bert-raw (ensemble)

None

83.60486.036

21

Dec 13, 2018
BERT finetune baseline (ensemble)

Anonymous

83.53686.096

21

Dec 21, 2018
PAML+BERT (ensemble model)

PINGAN GammaLab

83.45786.122

21

Dec 16, 2018
Lunet + Verifier + BERT (ensemble)

Layer 6 AI NLP Team

83.46986.043

22

Dec 15, 2018
Lunet + Verifier + BERT (single model)

Layer 6 AI NLP Team

82.99586.035

22

Jun 20, 2019
SENSEFORTH + BERT

single

https://senseforth.ai
83.14285.873

22

Jan 14, 2019
BERT + MMFT + ADA (single model)

Microsoft Research Asia

83.04085.892

22

May 14, 2019
ATB (single model)

Anonymous

82.88286.002

22

Feb 16, 2019
Bert-raw (ensemble)

None

83.17585.635

22

Feb 26, 2019
BERT with Something (ensemble)

Anonymous

83.05185.737

22

Jan 10, 2019
BERT + Synthetic Self-Training (single model)

Google AI Language

https://github.com/google-research/bert
82.97285.810

22

Jul 22, 2019
Tuned BERT Large Cased (single model)

FAIR & UW

82.80385.863

22

Mar 11, 2019
Bert-raw (ensemble)

None

83.11985.510

22

Feb 15, 2019
BERT + NeurQuRI (ensemble)

2SAH

82.80385.703

23

Feb 27, 2019
BERT + NeurQuRI (ensemble)

2SAH

82.71385.584

23

May 13, 2019
BERT-Base + QA Pre-training (single model)

Anonymous

82.72485.491

23

Dec 16, 2018
PAML+BERT (single model)

PINGAN GammaLab

82.57785.603

24

Nov 16, 2018
AoA + DA + BERT (ensemble)

Joint Laboratory of HIT and iFLYTEK Research

82.37485.310

25

Dec 12, 2018
BERT finetune baseline (single model)

Anonymous

82.12684.820

25

Feb 28, 2019
BERT_s (single model)

Anonymous

81.97984.846

25

Dec 10, 2018
Candi-Net+BERT (ensemble)

42Maru NLP Team

82.12684.624

26

Feb 28, 2019
BERT-large+UBFT (single model)

anonymous

81.57384.535

27

Feb 15, 2019
BERT + NeurQuRI (single model)

2SAH

81.25784.342

27

Feb 25, 2019
BERT with Something (single model)

Anonymous

81.11084.386

27

Nov 16, 2018
AoA + DA + BERT (single model)

Joint Laboratory of HIT and iFLYTEK Research

81.17884.251

28

Mar 20, 2019
Bert-raw (single)

None

80.69383.922

28

Mar 07, 2019
BERT + UnAnsQ (single model)

Anonymous

80.74983.851

29

Dec 19, 2018
Candi-Net+BERT (single model)

42Maru NLP Team

80.65983.562

30

Jan 22, 2019
BERT + NeurQuRI (single model)

2SAH

80.59183.391

30

Nov 11, 2019
BERTlarge (ensemble)

SAIL

80.45683.509

31

Mar 11, 2019
Bert-raw (single)

None

80.41183.457

32

Feb 16, 2019
Bert-raw (single model)

None

80.34383.243

32

May 28, 2019
Bert

Single Model

https://senseforth.ai
80.42283.118

32

Apr 04, 2019
BISAN-CC (single model)

Seoul National University & Hyundai Motors

80.20883.149

32

Dec 03, 2018
PwP+BERT (single model)

AITRICS

80.11783.189

32

Dec 05, 2018
Candi-Net+BERT (single model)

42Maru NLP Team

80.38882.908

32

Jul 22, 2019
Original BERT Large Cased (single model)

FAIR & UW

79.97183.266

32

Feb 19, 2019
BERT + UDA (single model)

Anonymous

80.00583.208

33

Apr 10, 2019
bert (single model)

vinda msqjmxx

79.97183.184

33

Feb 28, 2019
ST_bl

single model

80.14082.962

33

Nov 08, 2018
BERT (single model)

Google AI Language

80.00583.061

34

Feb 12, 2019
BERT + Sparse-Transformer

single model

79.94883.023

35

Mar 07, 2019
BERT uncased (single model)

Anonymous

79.74583.020

35

Dec 06, 2018
NEXYS_BASE (single model)

NEXYS, DGIST R7

79.77982.912

36

Feb 01, 2019
{bert-finetuning} (single model)

ksai

79.63282.852

37

Nov 09, 2018
L6Net + BERT (single model)

Layer 6 AI

79.18182.259

37

Mar 14, 2019
{Anonymous} (single model)

Anonymous

78.87682.524

38

Apr 24, 2019
BERT + WIAN (ensemble)

Infosys Limited

78.65081.497

38

Nov 11, 2019
BERTlarge (single model)

SAIL

78.65081.474

38

Mar 14, 2019
BISAN (single model)

Seoul National University & Hyundai Motors

78.48181.531

39

Dec 14, 2018
BERT+AC (single model)

Hithink RoyalFlush

78.05281.174

40

Nov 06, 2018
SLQA+BERT (single model)

Alibaba DAMO NLP

http://www.aclweb.org/anthology/P18-1158
77.00380.209

41

Jan 05, 2019
synss (single model)

bert_finetune

76.05579.329

42

Dec 18, 2018
ARSG-BERT (single model)

TRINITI RESEARCH LABS, Active.ai

https://active.ai
74.74678.227

42

Nov 05, 2018
MIR-MRC(F-Net) (single model)

Kangwon National University, Natural Language Processing Lab. & ForceWin, KP Lab.

74.79177.988

43

May 23, 2019
{BERTcw} (single model)

private

74.38577.308

44

Sep 13, 2018
nlnet (single model)

Microsoft Research Asia

74.27277.052

45

Dec 29, 2018
MMIPN

Single

73.50576.424

46

Apr 20, 2019
BERT-Base (single model)

Dining Philosophers

73.09976.236

47

Oct 12, 2018
YARCS (ensemble)

IBM Research AI

72.67075.507

48

Nov 14, 2018
BERT+Answer Verifier (single model)

Pingan Tech Olatop Lab

71.66675.457

49

Sep 17, 2018
Unet (ensemble)

Fudan University & Liulishuo Lab

https://arxiv.org/abs/1810.06638
71.41774.869

49

Apr 24, 2019
BERT-Base (single)

GreenflyAI

https://greenfly.ai
71.69974.430

49

Aug 15, 2018
Reinforced Mnemonic Reader + Answer Verifier (single model)

NUDT

https://arxiv.org/abs/1808.05759
71.76774.295

49

Aug 28, 2018
SLQA+ (single model)

Alibaba DAMO NLP

http://www.aclweb.org/anthology/P18-1158
71.46274.434

49

Jan 19, 2019
{BERT-base} (single-model)

Anonymous

70.76374.449

49

Sep 14, 2018
SAN (ensemble model)

Microsoft Business Applications AI Research

https://arxiv.org/abs/1712.03556
71.31673.704

50

Aug 21, 2018
FusionNet++ (ensemble)

Microsoft Business Applications Group AI Research

https://arxiv.org/abs/1711.07341
70.30072.484

50

Sep 26, 2018
Multi-Level Attention Fusion(MLAF) (single model)

Chonbuk National University, Cognitive Computing Lab.

69.47672.857

51

Sep 14, 2018
Unet (single model)

Fudan University & Liulishuo Lab

69.26272.642

52

Dec 20, 2018
DocQA + NeurQuRI (single model)

2SAH

68.76671.662

53

Aug 21, 2018
SAN (single model)

Microsoft Business Applications AI Research

https://arxiv.org/abs/1712.03556
68.65371.439

53

Sep 13, 2018
BiDAF++ with pair2vec (single model)

UW and FAIR

68.02171.583

53

Jun 24, 2018
KACTEIL-MRC(GFN-Net) (single model)

Kangwon National University, Natural Language Processing Lab.

68.21370.878

53

Jul 13, 2018
VS^3-NET (single model)

Kangwon National University in South Korea

67.89770.884

54

Jan 01, 2019
EBB-Net (single model)

Enliple AI

66.61070.303

55

Jun 25, 2018
KakaoNet2 (single model)

Kakao NLP Team

65.71969.381

56

Sep 13, 2018
BiDAF++ (single model)

UW and FAIR

65.65168.866

56

Jul 11, 2018
abcNet (single model)

Fudan University & Liulishuo AI Lab

65.25669.206

57

Jun 27, 2018
BSAE AddText (single model)

reciTAL.ai

63.33867.422

58

Aug 14, 2018
eeAttNet (single model)

BBD NLP Team

https://www.bbdservice.com
63.32766.633

58

May 30, 2018
BiDAF + Self Attention + ELMo (single model)

Allen Institute for Artificial Intelligence [modified by Stanford]

63.37266.251

59

May 30, 2018
BiDAF + Self Attention (single model)

Allen Institute for Artificial Intelligence [modified by Stanford]

59.33262.305

60

May 30, 2018
BiDAF-No-Answer (single model)

University of Washington [modified by Stanford]

59.17462.093

60

Nov 27, 2018
Tree-LSTM + BiDAF + ELMo (single model)

Carnegie Mellon University

57.70762.341

SQuAD1.1 Leaderboard

Here are the ExactMatch (EM) and F1 scores evaluated on the test set of SQuAD v1.1.

RankModelEMF1
Human Performance

Stanford University

(Rajpurkar et al. '16)
82.30491.221

1

May 21, 2019
XLNet (single model)

Google Brain & CMU

89.89895.080

2

Aug 11, 2019
XLNET-123 (single model)

MST/EOI

89.64694.930

2

Sep 12, 2019
XLNET-123+ (single model)

MST/EOI

http://tia.today
89.70994.859

3

Sep 25, 2019
BERTSP (single model)

NEUKG

http://www.techkg.cn/
88.91294.584

3

Jul 21, 2019
SpanBERT (single model)

FAIR & UW

88.83994.635

4

Jul 03, 2019
BERT+WWM+MT (single model)

Xiaoi Research

88.65094.393

5

Jul 21, 2019
Tuned BERT-1seq Large Cased (single model)

FAIR & UW

87.46593.294

6

Oct 05, 2018
BERT (ensemble)

Google AI Language

https://arxiv.org/abs/1810.04805
87.43393.160

7

May 14, 2019
ATB (single model)

Anonymous

86.94092.641

8

Jul 21, 2019
Tuned BERT Large Cased (single model)

FAIR & UW

86.52192.617

8

Jul 04, 2019
BERT+MT (single model)

Xiaoi Research

86.45892.645

9

Feb 14, 2019
KT-NET (single model)

Baidu NLP

85.94492.425

9

Sep 26, 2018
nlnet (ensemble)

Microsoft Research Asia

85.95491.677

9

Feb 28, 2019
ST_bl

single model

85.43091.976

10

Mar 14, 2019
BISAN (single model)

Seoul National University & Hyundai Motors

85.31491.756

10

Jun 03, 2019
DPN (single model)

Anonymous

84.97892.019

10

Oct 05, 2018
BERT (single model)

Google AI Language

https://arxiv.org/abs/1810.04805
85.08391.835

10

Jul 10, 2019
BERT-uncased (single model)

Anonymous

84.92691.932

10

Feb 16, 2019
BERT+Sparse-Transformer

single model

85.12591.623

10

Sep 09, 2018
nlnet (ensemble)

Microsoft Research Asia

85.35691.202

10

Jul 21, 2019
Original BERT Large Cased (single model)

FAIR & UW

84.32891.281

10

Feb 19, 2019
WD (single model)

Anonymous

84.40290.561

10

Jul 11, 2018
QANet (ensemble)

Google Brain & CMU

84.45490.490

10

Apr 21, 2019
Common-sense Governed BERT-123 (single model)

Jerry AGI Ragtag

83.93090.613

11

Feb 21, 2019
WD1 (single model)

Anonymous

83.80490.429

11

Jul 08, 2018
r-net (ensemble)

Microsoft Research Asia

84.00390.147

11

May 08, 2019
Common-sense Governed BERT-123 (single model)

MST/EOI

82.94391.074

11

Jun 20, 2018
MARS (ensemble)

YUANFUDAO research NLP

83.98289.796

12

Mar 19, 2018
QANet (ensemble)

Google Brain & CMU

83.87789.737

12

Sep 09, 2018
nlnet (single model)

Microsoft Research Asia

83.46890.133

13

Sep 01, 2018
MARS (single model)

YUANFUDAO research NLP

83.18589.547

14

Jun 21, 2018
MARS (single model)

YUANFUDAO research NLP

83.12289.224

15

Mar 06, 2018
QANet (ensemble)

Google Brain & CMU

82.74489.045

15

Jun 20, 2018
QANet (single)

Google Brain & CMU

82.47189.306

15

Jan 22, 2018
Hybrid AoA Reader (ensemble)

Joint Laboratory of HIT and iFLYTEK Research

82.48289.281

15

Feb 19, 2018
Reinforced Mnemonic Reader + A2D (ensemble model)

Microsoft Research Asia & NUDT

82.84988.764

15

May 09, 2018
MARS (single model)

YUANFUDAO research NLP

82.58788.880

15

Jan 03, 2018
r-net+ (ensemble)

Microsoft Research Asia

82.65088.493

15

Jan 05, 2018
SLQA+ (ensemble)

Alibaba iDST NLP

82.44088.607

15

Jul 14, 2019
BERT (single model)

KTNET

82.06288.947

15

Feb 27, 2018
QANet (single model)

Google Brain & CMU

82.20988.608

15

Feb 02, 2018
Reinforced Mnemonic Reader (ensemble model)

NUDT and Fudan University

https://arxiv.org/abs/1705.02798
82.28388.533

15

Dec 23, 2018
MMIPN

Single

81.58088.948

15

Dec 17, 2017
r-net (ensemble)

Microsoft Research Asia

http://aka.ms/rnet
82.13688.126

15

Dec 17, 2018
ARSG-BERT (single model)

TRINITI RESEARCH LABS, Active.ai

https://active.ai
81.30788.909

15

Dec 22, 2017
AttentionReader+ (ensemble)

Tencent DPDAC NLP

81.79088.163

16

May 09, 2018
Reinforced Mnemonic Reader + A2D (single model)

Microsoft Research Asia & NUDT

81.53888.130

16

Apr 23, 2018
r-net (single model)

Microsoft Research Asia

81.39188.170

16

May 09, 2018
Reinforced Mnemonic Reader + A2D + DA (single model)

Microsoft Research Asia & NUDT

81.40188.122

16

Apr 03, 2018
KACTEIL-MRC(GF-Net+) (ensemble)

Kangwon National University, Natural Language Processing Lab.

81.49687.557

16

Feb 27, 2018
QANet (single model)

Google Brain & CMU

80.92987.773

16

Nov 17, 2017
BiDAF + Self Attention + ELMo (ensemble)

Allen Institute for Artificial Intelligence

81.00387.432

16

Feb 19, 2018
Reinforced Mnemonic Reader + A2D (single model)

Microsoft Research Asia & NUDT

80.91987.492

17

Feb 12, 2018
Reinforced Mnemonic Reader + A2D (single model)

Microsoft Research Asia & NUDT

80.48987.454

17

Apr 12, 2018
AVIQA+ (ensemble)

aviqa team

80.61587.311

18

Jan 13, 2018
SLQA+

single model

80.43687.021

18

Jan 04, 2018
{EAZI} (ensemble)

Yiwise NLP Group

80.43686.912

18

Jan 12, 2018
EAZI+ (ensemble)

Yiwise NLP Group

80.42686.912

18

Jan 22, 2018
Hybrid AoA Reader (single model)

Joint Laboratory of HIT and iFLYTEK Research

80.02787.288

18

Mar 20, 2018
DNET (ensemble)

QA geeks

80.16486.721

19

Feb 12, 2018
BiDAF + Self Attention + ELMo + A2D (single model)

Microsoft Research Asia & NUDT

79.99686.711

20

Jan 03, 2018
r-net+ (single model)

Microsoft Research Asia

79.90186.536

20

Feb 23, 2018
MAMCN+ (single model)

Samsung Research

79.69286.727

21

Jan 29, 2018
Reinforced Mnemonic Reader (single model)

NUDT and Fudan University

https://arxiv.org/abs/1705.02798
79.54586.654

21

Dec 05, 2017
SAN (ensemble model)

Microsoft Business AI Solutions Team

https://arxiv.org/abs/1712.03556
79.60886.496

21

Dec 28, 2017
SLQA+ (single model)

Alibaba iDST NLP

79.19986.590

22

Oct 17, 2017
Interactive AoA Reader+ (ensemble)

Joint Laboratory of HIT and iFLYTEK

79.08386.450

22

Nov 05, 2018
MIR-MRC(F-Net) (single model)

ForceWin, KP Lab.

79.08386.288

23

Jun 01, 2018
MDReader

single model

79.03186.006

23

Oct 24, 2017
FusionNet (ensemble)

Microsoft Business AI Solutions Team

https://arxiv.org/abs/1711.07341
78.97886.016

24

Oct 22, 2017
DCN+ (ensemble)

Salesforce Research

https://arxiv.org/abs/1711.00106
78.85285.996

25

Mar 29, 2018
KACTEIL-MRC(GF-Net+) (single model)

Kangwon National University, Natural Language Processing Lab.

78.66485.780

25

Nov 03, 2017
BiDAF + Self Attention + ELMo (single model)

Allen Institute for Artificial Intelligence

78.58085.833

26

May 09, 2018
KakaoNet (single model)

Kakao NLP Team

78.40185.724

27

Nov 30, 2017
SLQA (ensemble)

Alibaba iDST NLP

78.32885.682

27

Mar 19, 2018
aviqa (ensemble)

aviqa team

78.49685.469

27

Jan 02, 2018
Conductor-net (ensemble)

CMU

https://arxiv.org/abs/1710.10504
78.43385.517

27

Sep 18, 2018
BiDAF++ with pair2vec (single model)

UW and FAIR

78.22385.535

27

Jun 01, 2018
MDReader0

single model

78.17185.543

27

Jan 03, 2018
MEMEN (single model)

Zhejiang University

https://arxiv.org/abs/1707.09098
78.23485.344

27

Jan 29, 2018
test

single

78.08785.348

28

Jul 25, 2017
Interactive AoA Reader (ensemble)

Joint Laboratory of HIT and iFLYTEK Research

77.84585.297

29

Mar 20, 2018
DNET (single model)

QA geeks

77.64684.905

30

Sep 18, 2018
BiDAF++ (single model)

UW and FAIR

77.57384.858

30

Dec 06, 2017
AttentionReader+ (single)

Tencent DPDAC NLP

77.34284.925

30

Dec 13, 2017
RaSoR + TR + LM (single model)

Tel-Aviv University

https://arxiv.org/abs/1712.03609
77.58384.163

30

Dec 21, 2017
Jenga (ensemble)

Facebook AI Research

77.23784.466

30

Nov 06, 2017
Conductor-net (ensemble)

CMU

https://arxiv.org/abs/1710.10504
76.99684.630

30

Jan 23, 2018
MARS (single model)

YUANFUDAO research NLP

76.85984.739

31

May 14, 2018
VS^3-NET (single model)

Kangwon National University in South Korea

76.77584.491

31

Nov 01, 2017
SAN (single model)

Microsoft Business AI Solutions Team

https://arxiv.org/abs/1712.03556
76.82884.396

31

Sep 26, 2018
{gqa} (single model)

FAIR

77.09083.931

31

Dec 19, 2017
FRC (single model)

in review

76.24084.599

31

Oct 13, 2017
r-net (single model)

Microsoft Research Asia

http://aka.ms/rnet
76.46184.265

32

Oct 22, 2017
Conductor-net (ensemble)

CMU

76.14683.991

33

Sep 08, 2017
FusionNet (single model)

Microsoft Business AI Solutions team

https://arxiv.org/abs/1711.07341
75.96883.900

34

Oct 22, 2017
Interactive AoA Reader+ (single model)

Joint Laboratory of HIT and iFLYTEK

75.82183.843

34

Oct 18, 2018
KAR (single model)

York University

https://arxiv.org/abs/1809.03449
76.12583.538

35

Jul 14, 2017
smarnet (ensemble)

Eigen Technology & Zhejiang University

75.98983.475

36

Mar 15, 2018
AVIQA-v2 (single model)

aviqa team

75.92683.305

37

Aug 18, 2017
RaSoR + TR (single model)

Tel-Aviv University

https://arxiv.org/abs/1712.03609
75.78983.261

38

Oct 23, 2017
DCN+ (single model)

Salesforce Research

https://arxiv.org/abs/1711.00106
75.08783.081

38

Nov 01, 2017
Mixed model (ensemble)

Sean

75.26582.769

38

May 21, 2017
MEMEN (ensemble)

Eigen Technology & Zhejiang University

https://arxiv.org/abs/1707.09098
75.37082.658

38

Nov 17, 2017
two-attention-self-attention (ensemble)

guotong1988

75.22382.716

38

Jul 10, 2017
DCN+ (single model)

Salesforce Research

https://arxiv.org/abs/1711.00106
74.86682.806

38

Mar 09, 2017
ReasoNet (ensemble)

MSR Redmond

https://arxiv.org/abs/1609.05284
75.03482.552

38

Oct 31, 2017
SLQA (single model)

Alibaba iDST NLP

74.48982.815

38

Feb 06, 2018
Jenga (single model)

Facebook AI Research

74.37382.845

38

Jan 02, 2018
Conductor-net (single model)

CMU

https://arxiv.org/abs/1710.10504
74.40582.742

38

Aug 14, 2018
eeAttNet (single model)

BBD NLP Team

https://www.bbdservice.com
74.60482.501

39

Feb 13, 2018
SSR-BiDAF

ensemble model

74.54182.477

40

Jul 14, 2017
Mnemonic Reader (ensemble)

NUDT and Fudan University

https://arxiv.org/abs/1705.02798
74.26882.371

41

Dec 23, 2017
S^3-Net (ensemble)

Kangwon National University in South Korea

74.12182.342

42

Jul 29, 2017
SEDT (ensemble model)

CMU

https://arxiv.org/abs/1703.00572
74.09081.761

43

Jul 06, 2017
SSAE (ensemble)

Tsinghua University

74.08081.665

43

Jul 25, 2017
Interactive AoA Reader (single model)

Joint Laboratory of HIT and iFLYTEK Research

73.63981.931

43

Feb 22, 2017
BiDAF (ensemble)

Allen Institute for AI & University of Washington

https://arxiv.org/abs/1611.01603
73.74481.525

43

Apr 22, 2017
SEDT+BiDAF (ensemble)

CMU

https://arxiv.org/abs/1703.00572
73.72381.530

43

Nov 06, 2017
Conductor-net (single)

CMU

https://arxiv.org/abs/1710.10504
73.24081.933

43

Dec 14, 2017
Jenga (single model)

Facebook AI Research

73.30381.754

43

Jan 24, 2017
Multi-Perspective Matching (ensemble)

IBM Research

https://arxiv.org/abs/1612.04211
73.76581.257

43

May 01, 2017
jNet (ensemble)

USTC & National Research Council Canada & York University

https://arxiv.org/abs/1703.04617
73.01081.517

44

Oct 22, 2017
Conductor-net (single)

CMU

72.59081.415

44

Apr 12, 2017
T-gating (ensemble)

Peking University

72.75881.001

44

Nov 16, 2017
two-attention-self-attention (single model)

guotong1988

72.60081.011

44

Sep 20, 2017
BiDAF + Self Attention (single model)

Allen Institute for Artificial Intelligence

https://arxiv.org/abs/1710.10723
72.13981.048

44

Mar 03, 2018
AVIQA (single model)

aviqa team

72.48580.550

44

Dec 15, 2017
S^3-Net (single model)

Kangwon National University in South Korea

71.90881.023

45

Nov 06, 2017
attention+self-attention (single model)

guotong1988

71.69880.462

46

Nov 01, 2016
Dynamic Coattention Networks (ensemble)

Salesforce Research

https://arxiv.org/abs/1611.01604
71.62580.383

46

Apr 13, 2017
QFASE

NUS

71.89879.989

46

Jul 14, 2017
smarnet (single model)

Eigen Technology & Zhejiang University

https://arxiv.org/abs/1710.02772
71.41580.160

47

Jul 14, 2017
Mnemonic Reader (single model)

NUDT and Fudan University

https://arxiv.org/abs/1705.02798
70.99580.146

47

May 23, 2018
AttReader (single)

College of Computer & Information Science, SouthWest University, Chongqing, China

71.37379.725

47

Apr 22, 2018
MAMCN (single model)

Samsung Research

70.98579.939

47

Oct 27, 2017
M-NET (single)

UFL

71.01679.835

48

Mar 24, 2017
jNet (single model)

USTC & National Research Council Canada & York University

https://arxiv.org/abs/1703.04617
70.60779.821

48

Apr 02, 2017
Ruminating Reader (single model)

New York University

https://arxiv.org/abs/1704.07415
70.63979.456

48

Mar 14, 2017
Document Reader (single model)

Facebook AI Research

https://arxiv.org/abs/1704.00051
70.73379.353

48

Mar 08, 2017
ReasoNet (single model)

MSR Redmond

https://arxiv.org/abs/1609.05284
70.55579.364

48

Dec 28, 2016
FastQAExt

German Research Center for Artificial Intelligence

https://arxiv.org/abs/1703.04816
70.84978.857

48

May 13, 2017
RaSoR (single model)

Google NY, Tel-Aviv University

https://arxiv.org/abs/1611.01436
70.84978.741

48

Apr 14, 2017
Multi-Perspective Matching (single model)

IBM Research

https://arxiv.org/abs/1612.04211
70.38778.784

49

Aug 30, 2017
SimpleBaseline (single model)

Technical University of Vienna

69.60078.236

49

Feb 05, 2018
SSR-BiDAF

single model

69.44378.358

50

Apr 12, 2017
SEDT+BiDAF (single model)

CMU

https://arxiv.org/abs/1703.00572
68.47877.971

51

Jun 25, 2017
PQMN (single model)

KAIST & AIBrain & Crosscert

68.33177.783

52

Apr 12, 2017
T-gating (single model)

Peking University

68.13277.569

52

Jul 29, 2017
SEDT (single model)

CMU

https://arxiv.org/abs/1703.00572
68.16377.527

52

Dec 28, 2016
FastQA

German Research Center for Artificial Intelligence

https://arxiv.org/abs/1703.04816
68.43677.070

52

Jan 22, 2018
FABIR

Single Model

https://arxiv.org/abs/1810.09580
67.74477.605

52

Nov 28, 2016
BiDAF (single model)

Allen Institute for AI & University of Washington

https://arxiv.org/abs/1611.01603
67.97477.323

53

Oct 26, 2016
Match-LSTM with Ans-Ptr (Boundary) (ensemble)

Singapore Management University

https://arxiv.org/abs/1608.07905
67.90177.022

53

Sep 19, 2017
AllenNLP BiDAF (single model)

Allen Institute for AI

http://allennlp.org/
67.61877.151

54

Feb 05, 2017
Iterative Co-attention Network

Fudan University

67.50276.786

55

Jan 03, 2018
newtest

single model

66.52775.787

55

Nov 01, 2016
Dynamic Coattention Networks (single model)

Salesforce Research

https://arxiv.org/abs/1611.01604
66.23375.896

56

Oct 26, 2016
Match-LSTM with Bi-Ans-Ptr (Boundary)

Singapore Management University

https://arxiv.org/abs/1608.07905
64.74473.743

57

Sep 21, 2017
OTF dict+spelling (single)

University of Montreal

https://arxiv.org/abs/1706.00286
64.08373.056

57

Feb 19, 2017
Attentive CNN context with LSTM

NLPR, CASIA

63.30673.463

58

Nov 02, 2016
Fine-Grained Gating

Carnegie Mellon University

https://arxiv.org/abs/1611.01724
62.44673.327

58

Sep 21, 2017
OTF spelling (single)

University of Montreal

https://arxiv.org/abs/1706.00286
62.89772.016

59

Sep 21, 2017
OTF spelling+lemma (single)

University of Montreal

https://arxiv.org/abs/1706.00286
62.60471.968

60

Sep 28, 2016
Dynamic Chunk Reader

IBM

https://arxiv.org/abs/1610.09996
62.49970.956

60

Nov 15, 2019
RQA+IDR (single model)

Anonymous

61.14571.389

61

Aug 27, 2016
Match-LSTM with Ans-Ptr (Boundary)

Singapore Management University

https://arxiv.org/abs/1608.07905
60.47470.695

62

Aug 27, 2016
Match-LSTM with Ans-Ptr (Sentence)

Singapore Management University

https://arxiv.org/abs/1608.07905
54.50567.748

62

Nov 15, 2019
RQA (single model)

Anonymous

55.82765.467

63

Aug 22, 2019
UQA (single model)

Anonymous

53.69864.036