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Question Answering archive 2025-07-28
SQuAD1.1 Benchmark (Question Answering)
Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
The archive carries no text for this table; the description above is the archive's text for the task Question Answering. archive 2025-07-28
Over time archive 2025-07-28
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Direction inferred from the metric name, not from the archive: F1 (higher is better). Not inferred (points only, no best-so-far line): EM, Hardware Burden, Exact Match, Operations per network pass. Points are placed at the row's paper date; 76 of 213 rows carry one.
Results archive 2025-07-28
Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.
| Paper | Code | Ran Syntology | Report | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | {ANNA} (single model) | 90.622 | 95.719 | ✓ | – | – | not matched | report | ||||
| 2 | LUKE (single model) | 90.202 | 95.379 | ✓ | – | – | not matched | report | ||||
| 3 | LUKE (single model) | 90.202 | 95.379 | – | Paper | Code | 2020 | 3 of 10 ran · 7 unverified | report | |||
| 4 | LUKE | 90.2 | – | Paper | Code | 2020 | 3 of 10 ran · 7 unverified | report | ||||
| 5 | XLNet (single model) | 89.898 | 95.080 | – | – | – | not matched | report | ||||
| 6 | XLNet (single model) | 89.898 | 95.080 | 46449G | ✓ | Paper | Code | 2019 | 10 of 24 ran · 14 unverified | report | ||
| 7 | XLNET-123++ (single model) | 89.856 | 94.903 | – | – | – | not matched | report | ||||
| 8 | XLNET-123+ (single model) | 89.709 | 94.859 | – | – | – | not matched | report | ||||
| 9 | XLNET-123 (single model) | 89.646 | 94.930 | – | – | – | not matched | report | ||||
| 10 | Unnamed submission by NMC | 88.912 | 94.584 | – | – | – | not matched | report | ||||
| 11 | BERTSP (single model) | 88.912 | 94.584 | – | – | – | not matched | report | ||||
| 12 | SpanBERT (single model) | 88.839 | 94.635 | – | – | – | not matched | report | ||||
| 13 | SpanBERT (single model) | 88.8 | 94.6 | 586G | – | Paper | Code | 2019 | 3 of 15 ran · 12 unverified | report | ||
| 14 | BERT+WWM+MT (single model) | 88.650 | 94.393 | – | – | – | not matched | report | ||||
| 15 | Tuned BERT-1seq Large Cased (single model) | 87.465 | 93.294 | – | – | – | not matched | report | ||||
| 16 | LinkBERT (large) | 87.45 | 92.7 | – | Paper | Code | 2022 | 0 of 14 ran · 14 unverified | report | |||
| 17 | BERT (ensemble) | 87.433 | 93.160 | – | Paper | Code | 2018 | 204 of 659 ran · 455 unverified | report | |||
| 18 | BERT-LARGE (Ensemble+TriviaQA) | 87.4 | 93.2 | – | Paper | Code | 2018 | 204 of 659 ran · 455 unverified | report | |||
| 19 | ATB (single model) | 86.940 | 92.641 | – | – | – | not matched | report | ||||
| 20 | Tuned BERT Large Cased (single model) | 86.521 | 92.617 | – | – | – | not matched | report | ||||
| 21 | BERT+MT (single model) | 86.458 | 92.645 | – | – | – | not matched | report | ||||
| 22 | Knowledge-enhanced BERT (single model) | 85.944 | 92.425 | – | – | – | not matched | report | ||||
| 23 | KT-NET (single model) | 85.944 | 92.425 | – | – | – | not matched | report | ||||
| 24 | ST_bl | 85.430 | 91.976 | – | – | – | not matched | report | ||||
| 25 | nlnet (ensemble) | 85.356 | 91.202 | – | – | – | not matched | report | ||||
| 26 | EL-BERT (single model) | 85.335 | 91.807 | – | – | – | not matched | report | ||||
| 27 | BISAN (single model) | 85.314 | 91.756 | – | – | – | not matched | report | ||||
| 28 | BERT+Sparse-Transformer | 85.125 | 91.623 | – | – | – | not matched | report | ||||
| 29 | BERT (single model) | 85.083 | 91.835 | ✓ | Paper | Code | 2018 | 204 of 659 ran · 455 unverified | report | |||
| 30 | DPN (single model) | 84.978 | 92.019 | – | – | – | not matched | report | ||||
| 31 | BERT-uncased (single model) | 84.926 | 91.932 | – | – | – | not matched | report | ||||
| 32 | WD (single model) | 84.402 | 90.561 | – | – | – | not matched | report | ||||
| 33 | Original BERT Large Cased (single model) | 84.328 | 91.281 | – | – | – | not matched | report | ||||
| 34 | MARS (ensemble) | 83.982 | 89.796 | – | – | – | not matched | report | ||||
| 35 | Common-sense Governed BERT-123 (single model) | 83.930 | 90.613 | – | – | – | not matched | report | ||||
| 36 | WD1 (single model) | 83.804 | 90.429 | – | – | – | not matched | report | ||||
| 37 | nlnet (single model) | 83.468 | 90.133 | – | – | – | not matched | report | ||||
| 38 | Pytalk + Stanza + BERT (single model) | 83.426 | 89.218 | – | – | – | not matched | report | ||||
| 39 | Reinforced Mnemonic Reader + A2D (ensemble model) | 82.849 | 88.764 | – | – | – | not matched | report | ||||
| 40 | BERT-Base mod (single model) | 82.681 | 89.379 | – | – | – | not matched | report | ||||
| 41 | r-net+ (ensemble) | 82.650 | 88.493 | – | – | – | not matched | report | ||||
| 42 | Hybrid AoA Reader (ensemble) | 82.482 | 89.281 | – | – | – | not matched | report | ||||
| 43 | QANet (single) | 82.471 | 89.306 | – | – | – | not matched | report | ||||
| 44 | SLQA+ (ensemble) | 82.440 | 88.607 | – | – | – | not matched | report | ||||
| 45 | Reinforced Mnemonic Reader (ensemble model) | 82.283 | 88.533 | ✓ | Paper | Code | 2017 | linked, not harvested | report | |||
| 46 | r-net (ensemble) | 82.136 | 88.126 | – | – | – | not matched | report | ||||
| 47 | BERT (single model) | 82.062 | 88.947 | – | – | – | not matched | report | ||||
| 48 | AttentionReader+ (ensemble) | 81.790 | 88.163 | – | – | – | not matched | report | ||||
| 49 | MMIPN | 81.580 | 88.948 | – | – | – | not matched | report | ||||
| 50 | BERT - 6 Layers | 81.5 | 88.5 | – | Paper | Code | 2021 | linked, not harvested | report | |||
| 51 | KACTEIL-MRC(GF-Net+) (ensemble) | 81.496 | 87.557 | – | – | – | not matched | report | ||||
| 52 | Reinforced Mnemonic Reader + A2D + DA (single model) | 81.401 | 88.122 | – | – | – | not matched | report | ||||
| 53 | ARSG-BERT (single model) | 81.307 | 88.909 | – | – | – | not matched | report | ||||
| 54 | BERT-COMPOUND-DSS (single model) | 81.045 | 87.999 | – | – | – | not matched | report | ||||
| 55 | BiDAF + Self Attention + ELMo (ensemble) | 81.003 | 87.432 | – | Paper | Code | 2018 | 23 of 58 ran · 35 unverified | report | |||
| 56 | BiDAF + Self Attention + ELMo (ensemble) | 81.003 | 87.432 | – | – | – | not matched | report | ||||
| 57 | BERT-COMPOUND (single model) | 80.720 | 87.758 | – | – | – | not matched | report | ||||
| 58 | mBERT + Task Adapter (Single) | 80.667 | 88.169 | – | – | – | not matched | report | ||||
| 59 | AVIQA+ (ensemble) | 80.615 | 87.311 | – | – | – | not matched | report | ||||
| 60 | Reinforced Mnemonic Reader + A2D (single model) | 80.489 | 87.454 | – | – | – | not matched | report | ||||
| 61 | SLQA+ | 80.436 | 87.021 | – | – | – | not matched | report | ||||
| 62 | {EAZI} (ensemble) | 80.436 | 86.912 | – | – | – | not matched | report | ||||
| 63 | EAZI+ (ensemble) | 80.426 | 86.912 | – | – | – | not matched | report | ||||
| 64 | DNET (ensemble) | 80.164 | 86.721 | – | – | – | not matched | report | ||||
| 65 | Hybrid AoA Reader (single model) | 80.027 | 87.288 | – | – | – | not matched | report | ||||
| 66 | BiDAF + Self Attention + ELMo + A2D (single model) | 79.996 | 86.711 | – | – | – | not matched | report | ||||
| 67 | r-net+ (single model) | 79.901 | 86.536 | – | – | – | not matched | report | ||||
| 68 | batch (single model) | 79.859 | 88.263 | – | – | – | not matched | report | ||||
| 69 | MAMCN+ (single model) | 79.692 | 86.727 | – | Paper | – | 2018 | no code linked | report | |||
| 70 | MAMCN+ (single model) | 79.692 | 86.727 | – | – | – | not matched | report | ||||
| 71 | SAN (ensemble model) | 79.608 | 86.496 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 72 | BERT-INDEPENDENT-DSS-FILTERED (single model) | 79.597 | 87.374 | – | – | – | not matched | report | ||||
| 73 | Reinforced Mnemonic Reader (single model) | 79.545 | 86.654 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 74 | SLQA+ (single model) | 79.199 | 86.590 | – | – | – | not matched | report | ||||
| 75 | Interactive AoA Reader+ (ensemble) | 79.083 | 86.450 | – | – | – | not matched | report | ||||
| 76 | MIR-MRC(F-Net) (single model) | 79.083 | 86.288 | – | – | – | not matched | report | ||||
| 77 | KACTEIL-MRC(GF-Net+Distillation) (single model) | 79.083 | 86.288 | – | – | – | not matched | report | ||||
| 78 | KACTEIL-MRC (GF-Net+Distillation) | 79.083 | 86.288 | – | – | – | not matched | report | ||||
| 79 | MDReader | 79.031 | 86.006 | – | – | – | not matched | report | ||||
| 80 | FusionNet (ensemble) | 78.978 | 86.016 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 81 | DCN+ (ensemble) | 78.852 | 85.996 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 82 | KACTEIL-MRC(GF-Net+) (single model) | 78.664 | 85.780 | – | – | – | not matched | report | ||||
| 83 | KACTEIL-MRC (GF-Net+) | 78.664 | 85.780 | – | – | – | not matched | report | ||||
| 84 | BERT-INDEPENDENT (single model) | 78.653 | 86.663 | – | – | – | not matched | report | ||||
| 85 | BiDAF + Self Attention + ELMo (single model) | 78.58 | 85.833 | – | Paper | Code | 2018 | 23 of 58 ran · 35 unverified | report | |||
| 86 | BiDAF + Self Attention + ELMo (single model) | 78.580 | 85.833 | – | – | – | not matched | report | ||||
| 87 | aviqa (ensemble) | 78.496 | 85.469 | – | – | – | not matched | report | ||||
| 88 | KakaoNet (single model) | 78.401 | 85.724 | – | – | – | not matched | report | ||||
| 89 | SLQA(ensemble) | 78.328 | 85.682 | – | – | – | not matched | report | ||||
| 90 | SLQA (ensemble) | 78.328 | 85.682 | – | – | – | not matched | report | ||||
| 91 | MEMEN (single model) | 78.234 | 85.344 | – | Paper | – | 2017 | no code linked | report | |||
| 92 | MEMEN (single model) | 78.234 | 85.344 | – | Paper | – | 2017 | no code linked | report | |||
| 93 | BiDAF++ with pair2vec (single model) | 78.223 | 85.535 | – | – | – | not matched | report | ||||
| 94 | MDReader0 | 78.171 | 85.543 | – | – | – | not matched | report | ||||
| 95 | test | 78.087 | 85.348 | – | – | – | not matched | report | ||||
| 96 | Interactive AoA Reader (ensemble) | 77.845 | 85.297 | – | – | – | not matched | report | ||||
| 97 | BERT - 3 Layers | 77.7 | 85.8 | – | Paper | Code | 2021 | linked, not harvested | report | |||
| 98 | DNET (single model) | 77.646 | 84.905 | – | – | – | not matched | report | ||||
| 99 | RaSoR + TR + LM (single model) | 77.583 | 84.163 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 100 | BiDAF++ (single model) | 77.573 | 84.858 | – | – | – | not matched | report | ||||
| 101 | AttentionReader+ (single) | 77.342 | 84.925 | – | – | – | not matched | report | ||||
| 102 | Jenga (ensemble) | 77.237 | 84.466 | – | – | – | not matched | report | ||||
| 103 | {gqa} (single model) | 77.090 | 83.931 | – | – | – | not matched | report | ||||
| 104 | Conductor-net (ensemble) | 76.996 | 84.630 | – | Paper | – | 2017 | no code linked | report | |||
| 105 | MARS (single model) | 76.859 | 84.739 | – | – | – | not matched | report | ||||
| 106 | SAN (single model) | 76.828 | 84.396 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 107 | VS^3-NET (single model) | 76.775 | 84.491 | – | – | – | not matched | report | ||||
| 108 | r-net (single model) | 76.461 | 84.265 | – | – | – | not matched | report | ||||
| 109 | r-net (single model) | 76.461 | 84.265 | – | Paper | – | 2017 | no code linked | report | |||
| 110 | FRC (single model) | 76.240 | 84.599 | – | – | – | not matched | report | ||||
| 111 | QANet + data augmentation ×3 | 76.2 | 84.6 | – | Paper | Code | 2018 | 7 of 19 ran · 12 unverified | report | |||
| 112 | Conductor-net (ensemble) | 76.146 | 83.991 | – | – | – | not matched | report | ||||
| 113 | KAR (single model) | 76.125 | 83.538 | – | Paper | – | 2018 | no code linked | report | |||
| 114 | smarnet (ensemble) | 75.989 | 83.475 | – | – | – | not matched | report | ||||
| 115 | FusionNet (single model) | 75.968 | 83.900 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 116 | AVIQA-v2 (single model) | 75.926 | 83.305 | – | – | – | not matched | report | ||||
| 117 | Interactive AoA Reader+ (single model) | 75.821 | 83.843 | – | – | – | not matched | report | ||||
| 118 | RaSoR + TR (single model) | 75.789 | 83.261 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 119 | MEMEN (ensemble) | 75.370 | 82.658 | – | Paper | – | 2017 | no code linked | report | |||
| 120 | Mixed model (ensemble) | 75.265 | 82.769 | – | – | – | not matched | report | ||||
| 121 | two-attention-self-attention (ensemble) | 75.223 | 82.716 | – | – | – | not matched | report | ||||
| 122 | Kbs (single model) | 75.034 | 83.405 | – | – | – | not matched | report | ||||
| 123 | ReasoNet (ensemble) | 75.034 | 82.552 | ✓ | Paper | – | 2016 | no code linked | report | |||
| 124 | EfficientQA 125M | 74.9 | 83.1 | – | Paper | – | 2021 | no code linked | report | |||
| 125 | DCN+ (single model) | 74.866 | 82.806 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 126 | eeAttNet (single model) | 74.604 | 82.501 | – | – | – | not matched | report | ||||
| 127 | SLQA (single model) | 74.489 | 82.815 | – | – | – | not matched | report | ||||
| 128 | Conductor-net (single model) | 74.405 | 82.742 | – | Paper | – | 2017 | no code linked | report | |||
| 129 | Mnemonic Reader (ensemble) | 74.268 | 82.371 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 130 | S^3-Net (ensemble) | 74.121 | 82.342 | – | – | – | not matched | report | ||||
| 131 | SEDT (ensemble model) | 74.090 | 81.761 | – | Paper | – | 2017 | no code linked | report | |||
| 132 | SSAE (ensemble) | 74.080 | 81.665 | – | – | – | not matched | report | ||||
| 133 | Multi-Perspective Matching (ensemble) | 73.765 | 81.257 | – | Paper | Code | 2016 | linked, not harvested | report | |||
| 134 | BiDAF (ensemble) | 73.744 | 81.525 | – | Paper | Code | 2016 | 8 of 11 ran · 3 unverified | report | |||
| 135 | SEDT+BiDAF (ensemble) | 73.723 | 81.530 | – | Paper | – | 2017 | no code linked | report | |||
| 136 | Interactive AoA Reader (single model) | 73.639 | 81.931 | – | – | – | not matched | report | ||||
| 137 | Jenga (single model) | 73.303 | 81.754 | – | – | – | not matched | report | ||||
| 138 | Conductor-net (single) | 73.240 | 81.933 | – | Paper | – | 2017 | no code linked | report | |||
| 139 | jNet (ensemble) | 73.010 | 81.517 | – | Paper | – | 2017 | no code linked | report | |||
| 140 | T-gating (ensemble) | 72.758 | 81.001 | – | – | – | not matched | report | ||||
| 141 | two-attention-self-attention (single model) | 72.600 | 81.011 | – | – | – | not matched | report | ||||
| 142 | Conductor-net (single) | 72.590 | 81.415 | – | – | – | not matched | report | ||||
| 143 | AVIQA (single model) | 72.485 | 80.550 | – | – | – | not matched | report | ||||
| 144 | BiDAF + Self Attention (single model) | 72.139 | 81.048 | – | Paper | Code | 2017 | 0 of 4 ran · 4 unverified | report | |||
| 145 | S^3-Net (single model) | 71.908 | 81.023 | – | – | – | not matched | report | ||||
| 146 | QFASE | 71.898 | 79.989 | – | – | – | not matched | report | ||||
| 147 | attention+self-attention (single model) | 71.698 | 80.462 | – | – | – | not matched | report | ||||
| 148 | Dynamic Coattention Networks (ensemble) | 71.625 | 80.383 | – | Paper | Code | 2016 | linked, not harvested | report | |||
| 149 | smarnet (single model) | 71.415 | 80.160 | – | Paper | – | 2017 | no code linked | report | |||
| 150 | SRU | 71.4 | 80.2 | 4G | – | Paper | Code | 2017 | 1 of 1 ran · 0 unverified | report | ||
| 151 | AttReader (single) | 71.373 | 79.725 | – | – | – | not matched | report | ||||
| 152 | DCN + Char + CoVe | 71.3 | 79.9 | – | Paper | Code | 2017 | 3 of 3 ran · 0 unverified | report | |||
| 153 | M-NET (single) | 71.016 | 79.835 | – | – | – | not matched | report | ||||
| 154 | Mnemonic Reader (single model) | 70.995 | 80.146 | – | Paper | Code | 2017 | linked, not harvested | report | |||
| 155 | MAMCN (single model) | 70.985 | 79.939 | – | – | – | not matched | report | ||||
| 156 | FastQAExt | 70.849 | 78.857 | – | Paper | Code | 2017 | 0 of 2 ran · 2 unverified | report | |||
| 157 | RaSoR (single model) | 70.849 | 78.741 | – | Paper | Code | 2016 | linked, not harvested | report | |||
| 158 | Document Reader (single model) | 70.733 | 79.353 | – | Paper | Code | 2017 | 1 of 1 ran · 0 unverified | report | |||
| 159 | Ruminating Reader (single model) | 70.639 | 79.456 | – | Paper | – | 2017 | no code linked | report | |||
| 160 | jNet (single model) | 70.607 | 79.821 | – | Paper | – | 2017 | no code linked | report | |||
| 161 | ReasoNet (single model) | 70.555 | 79.364 | – | Paper | – | 2016 | no code linked | report | |||
| 162 | Multi-Perspective Matching (single model) | 70.387 | 78.784 | – | Paper | Code | 2016 | linked, not harvested | report | |||
| 163 | SimpleBaseline (single model) | 69.600 | 78.236 | – | – | – | not matched | report | ||||
| 164 | SSR-BiDAF | 69.443 | 78.358 | – | – | – | not matched | report | ||||
| 165 | SEDT+BiDAF (single model) | 68.478 | 77.971 | – | Paper | – | 2017 | no code linked | report | |||
| 166 | FastQA | 68.436 | 77.070 | – | Paper | Code | 2017 | 0 of 2 ran · 2 unverified | report | |||
| 167 | PQMN (single model) | 68.331 | 77.783 | – | – | – | not matched | report | ||||
| 168 | SEDT (single model) | 68.163 | 77.527 | – | Paper | – | 2017 | no code linked | report | |||
| 169 | T-gating (single model) | 68.132 | 77.569 | – | – | – | not matched | report | ||||
| 170 | BiDAF (single model) | 67.974 | 77.323 | – | Paper | Code | 2016 | 8 of 11 ran · 3 unverified | report | |||
| 171 | Match-LSTM with Ans-Ptr (Boundary) (ensemble) | 67.901 | 77.022 | – | Paper | Code | 2016 | 3 of 3 ran · 0 unverified | report | |||
| 172 | FABIR | 67.744 | 77.605 | – | Paper | Code | 2018 | linked, not harvested | report | |||
| 173 | AllenNLP BiDAF (single model) | 67.618 | 77.151 | – | – | – | not matched | report | ||||
| 174 | BIDAF-COMPOUND-DSS (single model) | 67.544 | 76.429 | – | – | – | not matched | report | ||||
| 175 | Iterative Co-attention Network | 67.502 | 76.786 | – | – | – | not matched | report | ||||
| 176 | newtest | 66.527 | 75.787 | – | – | – | not matched | report | ||||
| 177 | BIDAF-INDEPENDENT-DSS (single model) | 66.516 | 76.349 | – | – | – | not matched | report | ||||
| 178 | Dynamic Coattention Networks (single model) | 66.233 | 75.896 | – | Paper | Code | 2016 | linked, not harvested | report | |||
| 179 | BIDAF-COMPOUND (single model) | 65.163 | 74.555 | – | – | – | not matched | report | ||||
| 180 | BIDAF-INDEPENDENT (single model) | 64.932 | 74.594 | – | – | – | not matched | report | ||||
| 181 | Match-LSTM with Bi-Ans-Ptr (Boundary) | 64.744 | 73.743 | – | Paper | Code | 2016 | 3 of 3 ran · 0 unverified | report | |||
| 182 | Unnamed submission by ravioncodalab | 64.439 | 73.921 | – | – | – | not matched | report | ||||
| 183 | OTF dict+spelling (single) | 64.083 | 73.056 | – | Paper | – | 2017 | no code linked | report | |||
| 184 | Attentive CNN context with LSTM | 63.306 | 73.463 | – | – | – | not matched | report | ||||
| 185 | OTF spelling (single) | 62.897 | 72.016 | – | Paper | – | 2017 | no code linked | report | |||
| 186 | OTF spelling+lemma (single) | 62.604 | 71.968 | – | Paper | – | 2017 | no code linked | report | |||
| 187 | Dynamic Chunk Reader | 62.499 | 70.956 | – | Paper | – | 2016 | no code linked | report | |||
| 188 | Fine-Grained Gating | 62.446 | 73.327 | – | Paper | Code | 2016 | linked, not harvested | report | |||
| 189 | RQA+IDR (single model) | 61.145 | 71.389 | – | – | – | not matched | report | ||||
| 190 | RQA+IDR (single model) | 61.145 | 71.389 | – | Paper | Code | 2020 | linked, not harvested | report | |||
| 191 | Match-LSTM with Ans-Ptr (Boundary) | 60.474 | 70.695 | – | Paper | Code | 2016 | 3 of 3 ran · 0 unverified | report | |||
| 192 | Unnamed submission by Will_Wu | 59.058 | 69.436 | – | – | – | not matched | report | ||||
| 193 | RQA (single model) | 55.827 | 65.467 | – | – | – | not matched | report | ||||
| 194 | RQA (single model) | 55.827 | 65.467 | – | Paper | Code | 2020 | linked, not harvested | report | |||
| 195 | Match-LSTM with Ans-Ptr (Sentence) | 54.505 | 67.748 | – | Paper | Code | 2016 | 3 of 3 ran · 0 unverified | report | |||
| 196 | UQA (single model) | 53.698 | 64.036 | – | – | – | not matched | report | ||||
| 197 | Unnamed submission by jinhyuklee | 52.544 | 62.780 | – | – | – | not matched | report | ||||
| 198 | Unnamed submission by minjoon | 52.533 | 62.757 | – | – | – | not matched | report | ||||
| 199 | UnsupervisedQA V1 (ensemble) | 47.341 | 56.436 | – | – | – | not matched | report | ||||
| 200 | UnsupervisedQA V1 (single model) | 44.215 | 54.723 | – | – | – | not matched | report | ||||
| 201 | QANet (single model) | 12.273 | 13.211 | – | – | – | not matched | report | ||||
| 202 | 0.000 | 6.907 | – | – | – | not matched | report | |||||
| 203 | QANet (ensemble) | 0.000 | 0.000 | – | – | – | not matched | report | ||||
| 204 | superman-new-des | 0.000 | 0.000 | – | – | – | not matched | report | ||||
| 205 | WAHnGREA | 0.000 | 0.000 | – | – | – | not matched | report | ||||
| 206 | superman-des | 0.000 | 0.000 | – | – | – | not matched | report | ||||
| 207 | XLNet-deep (ensemble) | 0.000 | 0.000 | – | – | – | not matched | report | ||||
| 208 | LUKE 483M | 95.4 | – | Paper | Code | 2020 | 3 of 10 ran · 7 unverified | report | ||||
| 209 | BART (TextBox 2.0) | 93.04 | 86.44 | – | Paper | Code | 2022 | 1 of 1 ran · 0 unverified | report | |||
| 210 | BERT-LARGE (Single+TriviaQA) | 91.8 | – | Paper | Code | 2018 | 204 of 659 ran · 455 unverified | report | ||||
| 211 | BERT-Large 32k batch size with AdamW | 91.58 | – | Paper | – | 2021 | no code linked | report | ||||
| 212 | DyREX | 91.01 | – | Paper | Code | 2022 | 2 of 3 ran · 1 unverified | report | ||||
| 213 | RuBERT | 84.6 | – | Paper | Code | 2019 | linked, not harvested | report |
All 213 rows shown. 76 link to a paper page on this site; 6 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28
Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 27 rows have a graph line, from 16 distinct papers; 23 rows (13 papers) have at least one sample that ran. Counting each paper once: Syntology ran 269 of 828 samples; 559 unverified. Separately, 199 of those 828 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections