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

Jan 10, 2020		Retro-Reader on ALBERT (ensemble)

Shanghai Jiao Tong University

90.11592.580

2

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

PINGAN Omni-Sinitic

90.00292.425

3

Sep 18, 2019		ALBERT (ensemble model)

Google Research & TTIC

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

4

Dec 08, 2019		ALBERT+Entailment DA (ensemble)

CloudWalk

88.76191.745

5

Jan 19, 2020		Retro-Reader on ALBERT (single model)

Shanghai Jiao Tong University

88.10791.419

5

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

PINGAN Omni-Sinitic

88.59290.859

5

Nov 22, 2019		albert+verifier (single model)

Ping An Life Insurance Company AI Team

88.35591.019

6

Jan 15, 2020		{alber_m_transfor} (single model)

QIANXIN

88.18690.939

6

Dec 08, 2019		ALBERT+Entailment DA Verifier (single model)

CloudWalk

87.84791.265

6

Jan 08, 2020		ALBert (single-model)

huahua

88.05091.036

6

Jan 07, 2020		ALBERT + SFVerifier (single model)

Senseforth AI Research

https://www.senseforth.ai/		88.19790.830

6

Sep 16, 2019		ALBERT (single model)

Google Research & TTIC

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

6

Jul 26, 2019		UPM (ensemble)

Anonymous

88.23190.713

7

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

Shanghai Jiao Tong University & CloudWalk

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

8

Nov 15, 2019		XLNet (single model)

Google Brain & CMU

87.92690.689

9

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

Shanghai Jiao Tong University & CloudWalk

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

10

Jul 26, 2019		UPM (single model)

Anonymous

87.19389.934

10

Nov 27, 2019		RoBERTa+Verify (ensemble)

CW

86.93390.037

10

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

Joint Laboratory of HIT and iFLYTEK Research

87.14789.474

10

Jul 20, 2019		RoBERTa (single model)

Facebook AI

86.82089.795

11

Nov 12, 2019		RoBERTa+Verify (single model)

CW

86.44889.586

11

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

Layer 6 AI

86.73089.286

12

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

Google AI Language

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

13

Oct 16, 2019		Xlnet+Verifier

single model

86.59489.082

14

Aug 30, 2019		Xlnet+Verifier (single model)

Ping An Life Insurance Company AI Team

86.57289.063

14

Dec 09, 2019		XLNET-V2-123+ (single model)

MST/EOI

http://tia.today		86.40389.148

15

May 21, 2019		XLNet (single model)

Google Brain & CMU

86.34689.133

16

May 14, 2019		SG-Net (ensemble)

Shanghai Jiao Tong University

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

16

Apr 13, 2019		SemBERT (ensemble)

Shanghai Jiao Tong University

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

16

Sep 29, 2019		BERTSP (single model)

NEUKG

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

16

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

Joint Laboratory of HIT and iFLYTEK Research

85.88488.621

16

Jul 22, 2019		SpanBERT (single model)

FAIR & UW

85.74888.709

17

May 14, 2019		SG-Net (single model)

Shanghai Jiao Tong University

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

17

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

Layer 6 AI

84.92488.204

17

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

Google AI Language

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

17

Jun 19, 2019		BNDVnet (single model)

PAOS

85.00387.833

17

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

Microsoft Research Asia

85.08287.615

17

Apr 11, 2019		SemBERT (single model)

Shanghai Jiao Tong University

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

17

Sep 13, 2019		xlnet (single model)

VerifiedXiaoPAI

84.64288.000

17

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

PAII Insight Team

84.83487.644

18

Sep 03, 2019		Hanvon_model (single model)

Hanvon_WuHan

84.72187.117

19

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

Google AI Language

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

20

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

Kyonggi University (ICL) & KISTI

84.20286.767

21

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

FAIR & UW

83.75186.594

22

Mar 20, 2019		Bert-raw (ensemble)

None

83.60486.036

22

Dec 13, 2018		BERT finetune baseline (ensemble)

Anonymous

83.53686.096

22

Dec 21, 2018		PAML+BERT (ensemble model)

PINGAN GammaLab

83.45786.122

22

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

Layer 6 AI NLP Team

83.46986.043

23

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

Layer 6 AI NLP Team

82.99586.035

23

Jun 20, 2019		SENSEFORTH + BERT

single

https://senseforth.ai		83.14285.873

23

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

Microsoft Research Asia

83.04085.892

23

May 14, 2019		ATB (single model)

Anonymous

82.88286.002

23

Feb 16, 2019		Bert-raw (ensemble)

None

83.17585.635

23

Feb 26, 2019		BERT with Something (ensemble)

Anonymous

83.05185.737

23

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

Google AI Language

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

23

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

FAIR & UW

82.80385.863

23

Mar 11, 2019		Bert-raw (ensemble)

None

83.11985.510

23

Feb 15, 2019		BERT + NeurQuRI (ensemble)

2SAH

82.80385.703

24

Feb 27, 2019		BERT + NeurQuRI (ensemble)

2SAH

82.71385.584

24

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

Anonymous

82.72485.491

24

Dec 16, 2018		PAML+BERT (single model)

PINGAN GammaLab

82.57785.603

25

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

Joint Laboratory of HIT and iFLYTEK Research

82.37485.310

26

Dec 12, 2018		BERT finetune baseline (single model)

Anonymous

82.12684.820

26

Feb 28, 2019		BERT_s (single model)

Anonymous

81.97984.846

26

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

42Maru NLP Team

82.12684.624

27

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

anonymous

81.57384.535

28

Feb 15, 2019		BERT + NeurQuRI (single model)

2SAH

81.25784.342

28

Feb 25, 2019		BERT with Something (single model)

Anonymous

81.11084.386

28

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

Joint Laboratory of HIT and iFLYTEK Research

81.17884.251

29

Mar 20, 2019		Bert-raw (single)

None

80.69383.922

29

Mar 07, 2019		BERT + UnAnsQ (single model)

Anonymous

80.74983.851

30

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

42Maru NLP Team

80.65983.562

31

Jan 22, 2019		BERT + NeurQuRI (single model)

2SAH

80.59183.391

31

Nov 11, 2019		BERTlarge (ensemble)

SAIL

80.45683.509

32

Mar 11, 2019		Bert-raw (single)

None

80.41183.457

33

Feb 16, 2019		Bert-raw (single model)

None

80.34383.243

33

May 28, 2019		Bert

Single Model

https://senseforth.ai		80.42283.118

33

Apr 04, 2019		BISAN-CC (single model)

Seoul National University & Hyundai Motors

80.20883.149

33

Dec 03, 2018		PwP+BERT (single model)

AITRICS

80.11783.189

33

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

42Maru NLP Team

80.38882.908

33

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

FAIR & UW

79.97183.266

33

Feb 19, 2019		BERT + UDA (single model)

Anonymous

80.00583.208

34

Apr 10, 2019		bert (single model)

vinda msqjmxx

79.97183.184

34

Feb 28, 2019		ST_bl

single model

80.14082.962

34

Nov 08, 2018		BERT (single model)

Google AI Language

80.00583.061

35

Feb 12, 2019		BERT + Sparse-Transformer

single model

79.94883.023

36

Mar 07, 2019		BERT uncased (single model)

Anonymous

79.74583.020

36

Dec 06, 2018		NEXYS_BASE (single model)

NEXYS, DGIST R7

79.77982.912

37

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

ksai

79.63282.852

38

Nov 09, 2018		L6Net + BERT (single model)

Layer 6 AI

79.18182.259

38

Mar 14, 2019		{Anonymous} (single model)

Anonymous

78.87682.524

39

Apr 24, 2019		BERT + WIAN (ensemble)

Infosys Limited

78.65081.497

39

Nov 11, 2019		BERTlarge (single model)

SAIL

78.65081.474

39

Mar 14, 2019		BISAN (single model)

Seoul National University & Hyundai Motors

78.48181.531

40

Dec 26, 2019		BERT-Large-Cased (single model)

sysu

78.35781.500

41

Dec 14, 2018		BERT+AC (single model)

Hithink RoyalFlush

78.05281.174

42

Nov 06, 2018		SLQA+BERT (single model)

Alibaba DAMO NLP

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

43

Jan 05, 2019		synss (single model)

bert_finetune

76.05579.329

44

Dec 18, 2018		ARSG-BERT (single model)

TRINITI RESEARCH LABS, Active.ai

https://active.ai		74.74678.227

44

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

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

74.79177.988

45

May 23, 2019		{BERTcw} (single model)

private

74.38577.308

46

Sep 13, 2018		nlnet (single model)

Microsoft Research Asia

74.27277.052

47

Jan 12, 2020		batch2 (single model)

THU

73.74276.858

48

Dec 29, 2018		MMIPN

Single

73.50576.424

49

Apr 20, 2019		BERT-Base (single model)

Dining Philosophers

73.09976.236

50

Oct 12, 2018		YARCS (ensemble)

IBM Research AI

72.67075.507

51

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

Pingan Tech Olatop Lab

71.66675.457

52

Sep 17, 2018		Unet (ensemble)

Fudan University & Liulishuo Lab

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

52

Apr 24, 2019		BERT-Base (single)

GreenflyAI

https://greenfly.ai		71.69974.430

52

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

NUDT

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

52

Aug 28, 2018		SLQA+ (single model)

Alibaba DAMO NLP

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

52

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

Anonymous

70.76374.449

52

Sep 14, 2018		SAN (ensemble model)

Microsoft Business Applications AI Research

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

53

Aug 21, 2018		FusionNet++ (ensemble)

Microsoft Business Applications Group AI Research

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

53

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

Chonbuk National University, Cognitive Computing Lab.

69.47672.857

54

Sep 14, 2018		Unet (single model)

Fudan University & Liulishuo Lab

69.26272.642

55

Dec 20, 2018		DocQA + NeurQuRI (single model)

2SAH

68.76671.662

56

Aug 21, 2018		SAN (single model)

Microsoft Business Applications AI Research

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

56

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

UW and FAIR

68.02171.583

56

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

Kangwon National University, Natural Language Processing Lab.

68.21370.878

56

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

Kangwon National University in South Korea

67.89770.884

57

Jan 01, 2019		EBB-Net (single model)

Enliple AI

66.61070.303

58

Jun 25, 2018		KakaoNet2 (single model)

Kakao NLP Team

65.71969.381

59

Sep 13, 2018		BiDAF++ (single model)

UW and FAIR

65.65168.866

59

Jul 11, 2018		abcNet (single model)

Fudan University & Liulishuo AI Lab

65.25669.206

60

Jun 27, 2018		BSAE AddText (single model)

reciTAL.ai

63.33867.422

61

Aug 14, 2018		eeAttNet (single model)

BBD NLP Team

https://www.bbdservice.com		63.32766.633

61

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

Allen Institute for Artificial Intelligence [modified by Stanford]

63.37266.251

62

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

Allen Institute for Artificial Intelligence [modified by Stanford]

59.33262.305

63

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

University of Washington [modified by Stanford]

59.17462.093

63

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

Dec 11, 2019		XLNET-123++ (single model)

MST/EOI

http://tia.today		89.85694.903

2

Aug 11, 2019		XLNET-123 (single model)

MST/EOI

89.64694.930

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

Nov 21, 2019		EL-BERT (single model)

YeonTaek Oh

85.33591.807

11

Mar 14, 2019		BISAN (single model)

Seoul National University & Hyundai Motors

85.31491.756

11

Jun 03, 2019		DPN (single model)

Anonymous

84.97892.019

11

Oct 05, 2018		BERT (single model)

Google AI Language

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

11

Jul 10, 2019		BERT-uncased (single model)

Anonymous

84.92691.932

11

Feb 16, 2019		BERT+Sparse-Transformer

single model

85.12591.623

11

Sep 09, 2018		nlnet (ensemble)

Microsoft Research Asia

85.35691.202

11

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

FAIR & UW

84.32891.281

11

Feb 19, 2019		WD (single model)

Anonymous

84.40290.561

11

Jul 11, 2018		QANet (ensemble)

Google Brain & CMU

84.45490.490

11

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

Jerry AGI Ragtag

83.93090.613

12

Feb 21, 2019		WD1 (single model)

Anonymous

83.80490.429

12

Jul 08, 2018		r-net (ensemble)

Microsoft Research Asia

84.00390.147

12

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

MST/EOI

82.94391.074

12

Jun 20, 2018		MARS (ensemble)

YUANFUDAO research NLP

83.98289.796

13

Mar 19, 2018		QANet (ensemble)

Google Brain & CMU

83.87789.737

13

Sep 09, 2018		nlnet (single model)

Microsoft Research Asia

83.46890.133

14

Sep 01, 2018		MARS (single model)

YUANFUDAO research NLP

83.18589.547

15

Jun 21, 2018		MARS (single model)

YUANFUDAO research NLP

83.12289.224

16

Mar 06, 2018		QANet (ensemble)

Google Brain & CMU

82.74489.045

16

Jun 20, 2018		QANet (single)

Google Brain & CMU

82.47189.306

16

Jan 22, 2018		Hybrid AoA Reader (ensemble)

Joint Laboratory of HIT and iFLYTEK Research

82.48289.281

16

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

Microsoft Research Asia & NUDT

82.84988.764

16

May 09, 2018		MARS (single model)

YUANFUDAO research NLP

82.58788.880

16

Jan 03, 2018		r-net+ (ensemble)

Microsoft Research Asia

82.65088.493

16

Jan 05, 2018		SLQA+ (ensemble)

Alibaba iDST NLP

82.44088.607

16

Jul 14, 2019		BERT (single model)

KTNET

82.06288.947

16

Feb 27, 2018		QANet (single model)

Google Brain & CMU

82.20988.608

16

Feb 02, 2018		Reinforced Mnemonic Reader (ensemble model)

NUDT and Fudan University

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

16

Dec 23, 2018		MMIPN

Single

81.58088.948

16

Dec 17, 2017		r-net (ensemble)

Microsoft Research Asia

http://aka.ms/rnet		82.13688.126

16

Dec 17, 2018		ARSG-BERT (single model)

TRINITI RESEARCH LABS, Active.ai

https://active.ai		81.30788.909

16

Dec 22, 2017		AttentionReader+ (ensemble)

Tencent DPDAC NLP

81.79088.163

17

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

Microsoft Research Asia & NUDT

81.53888.130

17

Apr 23, 2018		r-net (single model)

Microsoft Research Asia

81.39188.170

17

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

Microsoft Research Asia & NUDT

81.40188.122

17

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

Kangwon National University, Natural Language Processing Lab.

81.49687.557

17

Jan 06, 2020		BERT-COMPOUND-DSS (single model)

Brno University of Technology

81.04587.999

18

Feb 27, 2018		QANet (single model)

Google Brain & CMU

80.92987.773

19

Jan 06, 2020		BERT-COMPOUND (single model)

Brno University of Technology

80.72087.758

19

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

Allen Institute for Artificial Intelligence

81.00387.432

19

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

Microsoft Research Asia & NUDT

80.91987.492

20

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

Microsoft Research Asia & NUDT

80.48987.454

20

Apr 12, 2018		AVIQA+ (ensemble)

aviqa team

80.61587.311

21

Jan 13, 2018		SLQA+

single model

80.43687.021

21

Jan 04, 2018		{EAZI} (ensemble)

Yiwise NLP Group

80.43686.912

21

Jan 12, 2018		EAZI+ (ensemble)

Yiwise NLP Group

80.42686.912

21

Jan 22, 2018		Hybrid AoA Reader (single model)

Joint Laboratory of HIT and iFLYTEK Research

80.02787.288

21

Mar 20, 2018		DNET (ensemble)

QA geeks

80.16486.721

22

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

Microsoft Research Asia & NUDT

79.99686.711

23

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

Microsoft Research Asia

79.90186.536

23

Feb 23, 2018		MAMCN+ (single model)

Samsung Research

79.69286.727

24

Jan 29, 2018		Reinforced Mnemonic Reader (single model)

NUDT and Fudan University

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

24

Dec 05, 2017		SAN (ensemble model)

Microsoft Business AI Solutions Team

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

24

Dec 28, 2017		SLQA+ (single model)

Alibaba iDST NLP

79.19986.590

25

Oct 17, 2017		Interactive AoA Reader+ (ensemble)

Joint Laboratory of HIT and iFLYTEK

79.08386.450

25

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

ForceWin, KP Lab.

79.08386.288

25

Jan 06, 2020		BERT-INDEPENDENT (single model)

Brno University of Technology

78.65386.663

25

Jun 01, 2018		MDReader

single model

79.03186.006

25

Oct 24, 2017		FusionNet (ensemble)

Microsoft Business AI Solutions Team

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

26

Oct 22, 2017		DCN+ (ensemble)

Salesforce Research

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

27

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

Kangwon National University, Natural Language Processing Lab.

78.66485.780

27

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

Allen Institute for Artificial Intelligence

78.58085.833

28

May 09, 2018		KakaoNet (single model)

Kakao NLP Team

78.40185.724

29

Nov 30, 2017		SLQA (ensemble)

Alibaba iDST NLP

78.32885.682

29

Mar 19, 2018		aviqa (ensemble)

aviqa team

78.49685.469

29

Jan 02, 2018		Conductor-net (ensemble)

CMU

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

29

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

UW and FAIR

78.22385.535

29

Jun 01, 2018		MDReader0

single model

78.17185.543

29

Jan 03, 2018		MEMEN (single model)

Zhejiang University

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

29

Jan 29, 2018		test

single

78.08785.348

30

Jul 25, 2017		Interactive AoA Reader (ensemble)

Joint Laboratory of HIT and iFLYTEK Research

77.84585.297

31

Mar 20, 2018		DNET (single model)

QA geeks

77.64684.905

32

Sep 18, 2018		BiDAF++ (single model)

UW and FAIR

77.57384.858

32

Dec 06, 2017		AttentionReader+ (single)

Tencent DPDAC NLP

77.34284.925

32

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

Tel-Aviv University

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

32

Dec 21, 2017		Jenga (ensemble)

Facebook AI Research

77.23784.466

32

Nov 06, 2017		Conductor-net (ensemble)

CMU

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

32

Jan 23, 2018		MARS (single model)

YUANFUDAO research NLP

76.85984.739

33

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

Kangwon National University in South Korea

76.77584.491

33

Nov 01, 2017		SAN (single model)

Microsoft Business AI Solutions Team

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

33

Sep 26, 2018		{gqa} (single model)

FAIR

77.09083.931

33

Dec 19, 2017		FRC (single model)

in review

76.24084.599

33

Oct 13, 2017		r-net (single model)

Microsoft Research Asia

http://aka.ms/rnet		76.46184.265

34

Oct 22, 2017		Conductor-net (ensemble)

CMU

76.14683.991

35

Sep 08, 2017		FusionNet (single model)

Microsoft Business AI Solutions team

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

36

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

Joint Laboratory of HIT and iFLYTEK

75.82183.843

36

Oct 18, 2018		KAR (single model)

York University

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

37

Jul 14, 2017		smarnet (ensemble)

Eigen Technology & Zhejiang University

75.98983.475

38

Mar 15, 2018		AVIQA-v2 (single model)

aviqa team

75.92683.305

39

Aug 18, 2017		RaSoR + TR (single model)

Tel-Aviv University

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

40

Oct 23, 2017		DCN+ (single model)

Salesforce Research

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

40

Nov 01, 2017		Mixed model (ensemble)

Sean

75.26582.769

40

May 21, 2017		MEMEN (ensemble)

Eigen Technology & Zhejiang University

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

40

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

guotong1988

75.22382.716

40

Jul 10, 2017		DCN+ (single model)

Salesforce Research

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

40

Mar 09, 2017		ReasoNet (ensemble)

MSR Redmond

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

40

Oct 31, 2017		SLQA (single model)

Alibaba iDST NLP

74.48982.815

40

Feb 06, 2018		Jenga (single model)

Facebook AI Research

74.37382.845

40

Jan 02, 2018		Conductor-net (single model)

CMU

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

40

Aug 14, 2018		eeAttNet (single model)

BBD NLP Team

https://www.bbdservice.com		74.60482.501

41

Feb 13, 2018		SSR-BiDAF

ensemble model

74.54182.477

42

Jul 14, 2017		Mnemonic Reader (ensemble)

NUDT and Fudan University

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

43

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

Kangwon National University in South Korea

74.12182.342

44

Jul 29, 2017		SEDT (ensemble model)

CMU

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

45

Jul 06, 2017		SSAE (ensemble)

Tsinghua University

74.08081.665

45

Jul 25, 2017		Interactive AoA Reader (single model)

Joint Laboratory of HIT and iFLYTEK Research

73.63981.931

45

Feb 22, 2017		BiDAF (ensemble)

Allen Institute for AI & University of Washington

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

45

Apr 22, 2017		SEDT+BiDAF (ensemble)

CMU

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

45

Nov 06, 2017		Conductor-net (single)

CMU

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

45

Dec 14, 2017		Jenga (single model)

Facebook AI Research

73.30381.754

45

Jan 24, 2017		Multi-Perspective Matching (ensemble)

IBM Research

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

45

May 01, 2017		jNet (ensemble)

USTC & National Research Council Canada & York University

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

46

Oct 22, 2017		Conductor-net (single)

CMU

72.59081.415

46

Apr 12, 2017		T-gating (ensemble)

Peking University

72.75881.001

46

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

guotong1988

72.60081.011

46

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

Allen Institute for Artificial Intelligence

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

46

Mar 03, 2018		AVIQA (single model)

aviqa team

72.48580.550

46

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

Kangwon National University in South Korea

71.90881.023

47

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

guotong1988

71.69880.462

48

Nov 01, 2016		Dynamic Coattention Networks (ensemble)

Salesforce Research

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

48

Apr 13, 2017		QFASE

NUS

71.89879.989

48

Jul 14, 2017		smarnet (single model)

Eigen Technology & Zhejiang University

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

49

Jul 14, 2017		Mnemonic Reader (single model)

NUDT and Fudan University

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

49

May 23, 2018		AttReader (single)

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

71.37379.725

49

Apr 22, 2018		MAMCN (single model)

Samsung Research

70.98579.939

49

Oct 27, 2017		M-NET (single)

UFL

71.01679.835

50

Mar 24, 2017		jNet (single model)

USTC & National Research Council Canada & York University

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

50

Apr 02, 2017		Ruminating Reader (single model)

New York University

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

50

Mar 14, 2017		Document Reader (single model)

Facebook AI Research

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

50

Mar 08, 2017		ReasoNet (single model)

MSR Redmond

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

50

Dec 28, 2016		FastQAExt

German Research Center for Artificial Intelligence

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

50

May 13, 2017		RaSoR (single model)

Google NY, Tel-Aviv University

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

50

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

IBM Research

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

51

Aug 30, 2017		SimpleBaseline (single model)

Technical University of Vienna

69.60078.236

51

Feb 05, 2018		SSR-BiDAF

single model

69.44378.358

52

Apr 12, 2017		SEDT+BiDAF (single model)

CMU

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

53

Jun 25, 2017		PQMN (single model)

KAIST & AIBrain & Crosscert

68.33177.783

54

Apr 12, 2017		T-gating (single model)

Peking University

68.13277.569

54

Jul 29, 2017		SEDT (single model)

CMU

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

54

Dec 28, 2016		FastQA

German Research Center for Artificial Intelligence

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

54

Jan 22, 2018		FABIR

Single Model

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

54

Nov 28, 2016		BiDAF (single model)

Allen Institute for AI & University of Washington

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

55

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

Singapore Management University

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

55

Sep 19, 2017		AllenNLP BiDAF (single model)

Allen Institute for AI

http://allennlp.org/		67.61877.151

56

Feb 05, 2017		Iterative Co-attention Network

Fudan University

67.50276.786

56

Jan 06, 2020		BIDAF-COMPOUND-DSS (single model)

Brno University of Technology

67.54476.429

57

Jan 06, 2020		BIDAF-INDEPENDENT-DSS (single model)

Brno University of Technology

66.51676.349

57

Jan 03, 2018		newtest

single model

66.52775.787

57

Nov 01, 2016		Dynamic Coattention Networks (single model)

Salesforce Research

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

58

Jan 06, 2020		BIDAF-COMPOUND (single model)

Brno University of Technology

65.16374.555

58

Jan 06, 2020		BIDAF-INDEPENDENT (single model)

Brno University of Technology

64.93274.594

59

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

Singapore Management University

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

60

Sep 21, 2017		OTF dict+spelling (single)

University of Montreal

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

60

Feb 19, 2017		Attentive CNN context with LSTM

NLPR, CASIA

63.30673.463

61

Nov 02, 2016		Fine-Grained Gating

Carnegie Mellon University

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

61

Sep 21, 2017		OTF spelling (single)

University of Montreal

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

62

Sep 21, 2017		OTF spelling+lemma (single)

University of Montreal

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

63

Sep 28, 2016		Dynamic Chunk Reader

IBM

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

63

Nov 15, 2019		RQA+IDR (single model)

Anonymous

61.14571.389

64

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

Singapore Management University

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

65

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

Singapore Management University

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

65

Nov 15, 2019		RQA (single model)

Anonymous

55.82765.467

66

Aug 22, 2019		UQA (single model)

Anonymous

53.69864.036