sample_id stringlengths 14 14 | doc_id stringlengths 10 10 | mode stringclasses 2
values | image_width int64 112 6.8k | image_height int64 95 9.07k | bbox listlengths 4 4 | answer stringlengths 1 434 | level int64 1 4 | target_index int64 0 44 | num_context_images int64 1 55 | context_img_paths listlengths 1 55 | language stringclasses 22
values | mask_ratio float64 0 0.14 | char_length int64 1 434 | file_name stringlengths 41 43 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
sample_0001701 | doc_001817 | single | 1,039 | 391 | [
0.169,
0.53,
0.244,
0.647
] | जयपुर | 1 | 0 | 1 | [
"images/doc_001817/doc_001817_image0001.png"
] | Hindi | 0.008763 | 5 | images/doc_001817/doc_001817_image0001.png |
sample_0001702 | doc_001866 | single | 2,160 | 1,256 | [
0.479,
0.259,
0.722,
0.326
] | UNE INCONNUE | 2 | 0 | 1 | [
"images/doc_001866/doc_001866_image0001.png"
] | French | 0.016535 | 12 | images/doc_001866/doc_001866_image0001.png |
sample_0001703 | doc_001419 | single | 1,192 | 706 | [
0.154,
0.596,
0.406,
0.647
] | Turn into a carousel | 2 | 0 | 1 | [
"images/doc_001419/doc_001419_image0001.png"
] | English | 0.012972 | 20 | images/doc_001419/doc_001419_image0001.png |
sample_0001704 | doc_001148 | single | 802 | 565 | [
0.033,
0.847,
0.421,
0.921
] | 镜头之下，是永不褪色的历史记忆 | 3 | 0 | 1 | [
"images/doc_001148/doc_001148_image0001.png"
] | Chinese | 0.028735 | 15 | images/doc_001148/doc_001148_image0001.png |
sample_0001705 | doc_001774 | single | 1,269 | 727 | [
0.184,
0.673,
0.285,
0.728
] | ヒトES細胞 | 2 | 0 | 1 | [
"images/doc_001774/doc_001774_image0001.png"
] | Japanese | 0.005564 | 6 | images/doc_001774/doc_001774_image0001.png |
sample_0001706 | doc_001392 | single | 858 | 573 | [
0.385,
0.624,
0.677,
0.678
] | Between group variance | 2 | 0 | 1 | [
"images/doc_001392/doc_001392_image0001.png"
] | English | 0.015641 | 22 | images/doc_001392/doc_001392_image0001.png |
sample_0001707 | doc_001978 | single | 795 | 832 | [
0.396,
0.579,
0.646,
0.611
] | Korean Red Makeup | 2 | 0 | 1 | [
"images/doc_001978/doc_001978_image0001.png"
] | English | 0.007905 | 17 | images/doc_001978/doc_001978_image0001.png |
sample_0001708 | doc_001930 | single | 963 | 597 | [
0.55,
0.254,
0.655,
0.287
] | Infographic type | 2 | 0 | 1 | [
"images/doc_001930/doc_001930_image0001.png"
] | English | 0.003478 | 16 | images/doc_001930/doc_001930_image0001.png |
sample_0001709 | doc_001462 | single | 1,290 | 548 | [
0.056,
0.726,
0.11,
0.773
] | 诗意作画 | 2 | 0 | 1 | [
"images/doc_001462/doc_001462_image0001.png"
] | Chinese | 0.00252 | 4 | images/doc_001462/doc_001462_image0001.png |
sample_0001710 | doc_001353 | single | 711 | 528 | [
0.325,
0.87,
0.54,
0.949
] | Use a Chinese Calligraphy Brush | 2 | 0 | 1 | [
"images/doc_001353/doc_001353_image0001.png"
] | English | 0.017049 | 31 | images/doc_001353/doc_001353_image0001.png |
sample_0001711 | doc_001775 | single | 776 | 776 | [
0.02,
0.364,
0.216,
0.39
] | 会見で謝罪する中部電力 | 3 | 0 | 1 | [
"images/doc_001775/doc_001775_image0001.png"
] | Japanese | 0.005169 | 11 | images/doc_001775/doc_001775_image0001.png |
sample_0001712 | doc_001425 | single | 950 | 616 | [
0.298,
0.854,
0.407,
0.898
] | Pixel perfection | 2 | 0 | 1 | [
"images/doc_001425/doc_001425_image0001.png"
] | English | 0.004791 | 16 | images/doc_001425/doc_001425_image0001.png |
sample_0001713 | doc_001886 | single | 1,155 | 856 | [
0.246,
0.766,
0.315,
0.799
] | Getriebe | 1 | 0 | 1 | [
"images/doc_001886/doc_001886_image0001.png"
] | German | 0.002241 | 8 | images/doc_001886/doc_001886_image0001.png |
sample_0001714 | doc_001915 | single | 793 | 948 | [
0.054,
0.648,
0.427,
0.754
] | Explore
business opportunities
for Creative IPs | 3 | 0 | 1 | [
"images/doc_001915/doc_001915_image0001.png"
] | English | 0.039602 | 47 | images/doc_001915/doc_001915_image0001.png |
sample_0001715 | doc_001814 | single | 1,343 | 740 | [
0.378,
0.681,
0.651,
0.796
] | जनता पार्टी कहा | 2 | 0 | 1 | [
"images/doc_001814/doc_001814_image0001.png"
] | Hindi | 0.031683 | 15 | images/doc_001814/doc_001814_image0001.png |
sample_0001716 | doc_001496 | single | 1,253 | 594 | [
0.076,
0.587,
0.191,
0.659
] | 如何激活门票? | 2 | 0 | 1 | [
"images/doc_001496/doc_001496_image0001.png"
] | Chinese | 0.008215 | 7 | images/doc_001496/doc_001496_image0001.png |
sample_0001717 | doc_001935 | single | 700 | 627 | [
0.285,
0.303,
0.619,
0.341
] | Here's how to make it work | 3 | 0 | 1 | [
"images/doc_001935/doc_001935_image0001.png"
] | English | 0.012377 | 26 | images/doc_001935/doc_001935_image0001.png |
sample_0001718 | doc_001079 | single | 408 | 654 | [
0.035,
0.381,
0.465,
0.424
] | 国产劳斯莱斯，库里南! | 3 | 0 | 1 | [
"images/doc_001079/doc_001079_image0001.png"
] | Chinese | 0.018764 | 11 | images/doc_001079/doc_001079_image0001.png |
sample_0001719 | doc_001982 | single | 661 | 648 | [
0.049,
0.359,
0.177,
0.403
] | 适配机器 | 2 | 0 | 1 | [
"images/doc_001982/doc_001982_image0001.png"
] | Chinese | 0.005673 | 4 | images/doc_001982/doc_001982_image0001.png |
sample_0001720 | doc_002095 | single | 573 | 502 | [
0.202,
0.751,
0.295,
0.796
] | Mirror | 1 | 0 | 1 | [
"images/doc_002095/doc_002095_image0001.png"
] | English | 0.004139 | 6 | images/doc_002095/doc_002095_image0001.png |
sample_0001721 | doc_001801 | single | 1,166 | 1,193 | [
0.695,
0.101,
0.858,
0.15
] | 1. مرحلة البحث | 2 | 0 | 1 | [
"images/doc_001801/doc_001801_image0001.png"
] | Arabic | 0.008013 | 14 | images/doc_001801/doc_001801_image0001.png |
sample_0001722 | doc_002114 | single | 1,313 | 604 | [
0.735,
0.616,
0.786,
0.644
] | recovery | 1 | 0 | 1 | [
"images/doc_002114/doc_002114_image0001.png"
] | English | 0.001465 | 8 | images/doc_002114/doc_002114_image0001.png |
sample_0001723 | doc_001777 | single | 1,752 | 1,266 | [
0.05,
0.339,
0.116,
0.361
] | Забыли пароль | 2 | 0 | 1 | [
"images/doc_001777/doc_001777_image0001.png"
] | Russian | 0.001424 | 13 | images/doc_001777/doc_001777_image0001.png |
sample_0001724 | doc_001447 | single | 1,469 | 601 | [
0.027,
0.388,
0.291,
0.488
] | 视频翻译：AI生成字幕， | 3 | 0 | 1 | [
"images/doc_001447/doc_001447_image0001.png"
] | Chinese | 0.026381 | 12 | images/doc_001447/doc_001447_image0001.png |
sample_0001725 | doc_001275 | single | 329 | 798 | [
0.05,
0.516,
0.243,
0.54
] | 涨 1544 家 | 2 | 0 | 1 | [
"images/doc_001275/doc_001275_image0001.png"
] | Chinese | 0.004627 | 8 | images/doc_001275/doc_001275_image0001.png |
sample_0001726 | doc_001287 | single | 1,028 | 607 | [
0.099,
0.825,
0.195,
0.857
] | 流动性的保护 | 2 | 0 | 1 | [
"images/doc_001287/doc_001287_image0001.png"
] | Chinese | 0.003052 | 6 | images/doc_001287/doc_001287_image0001.png |
sample_0001727 | doc_001846 | single | 1,160 | 855 | [
0.554,
0.888,
0.64,
0.917
] | ASIE-PACIFIQUE | 2 | 0 | 1 | [
"images/doc_001846/doc_001846_image0001.png"
] | French | 0.002455 | 14 | images/doc_001846/doc_001846_image0001.png |
sample_0001728 | doc_001471 | single | 576 | 778 | [
0.002,
0.519,
0.425,
0.559
] | 既然你要打价格战，那我就把利润表炸掉。 | 3 | 0 | 1 | [
"images/doc_001471/doc_001471_image0001.png"
] | Chinese | 0.016821 | 19 | images/doc_001471/doc_001471_image0001.png |
sample_0001729 | doc_001929 | single | 1,414 | 707 | [
0.822,
0.488,
0.907,
0.526
] | Scan business card | 2 | 0 | 1 | [
"images/doc_001929/doc_001929_image0001.png"
] | English | 0.003209 | 18 | images/doc_001929/doc_001929_image0001.png |
sample_0001730 | doc_001226 | single | 1,005 | 836 | [
0.209,
0.121,
0.307,
0.145
] | Chromebook | 1 | 0 | 1 | [
"images/doc_001226/doc_001226_image0001.png"
] | English | 0.002335 | 10 | images/doc_001226/doc_001226_image0001.png |
sample_0001731 | doc_002017 | single | 1,462 | 1,404 | [
0.446,
0.43,
0.545,
0.477
] | Desynchronized risk-averse | 2 | 0 | 1 | [
"images/doc_002017/doc_002017_image0001.png"
] | English | 0.004547 | 26 | images/doc_002017/doc_002017_image0001.png |
sample_0001732 | doc_001117 | single | 719 | 849 | [
0.013,
0.095,
0.996,
0.164
] | 能研究机构。然而，此后双方关系逐渐恶化，二人不仅在社交媒体上相互攻讦，还
在法律文件中互相指责。马斯克于 2018 年退出 OpenAI 董事会，并于 2023 年创立 | 4 | 0 | 1 | [
"images/doc_001117/doc_001117_image0001.png"
] | Chinese | 0.067899 | 84 | images/doc_001117/doc_001117_image0001.png |
sample_0001733 | doc_002038 | single | 1,226 | 1,736 | [
0.2,
0.615,
0.496,
0.637
] | Surrogate trajectory of the resolved | 2 | 0 | 1 | [
"images/doc_002038/doc_002038_image0001.png"
] | English | 0.006308 | 36 | images/doc_002038/doc_002038_image0001.png |
sample_0001734 | doc_001288 | single | 663 | 709 | [
0.256,
0.266,
0.373,
0.301
] | 市盈率(TTM) | 2 | 0 | 1 | [
"images/doc_001288/doc_001288_image0001.png"
] | Chinese | 0.00416 | 8 | images/doc_001288/doc_001288_image0001.png |
sample_0001735 | doc_001438 | single | 499 | 660 | [
0.258,
0.831,
0.429,
0.876
] | BORDER MANAGEMENT | 2 | 0 | 1 | [
"images/doc_001438/doc_001438_image0001.png"
] | English | 0.007801 | 17 | images/doc_001438/doc_001438_image0001.png |
sample_0001736 | doc_001830 | single | 772 | 738 | [
0.255,
0.758,
0.866,
0.806
] | ซึ่งอาจทำลายเซลล์กระดูกอ่อนและเพิ่มความเสี่ยงต่อข้ออักเสบ | 2 | 0 | 1 | [
"images/doc_001830/doc_001830_image0001.png"
] | Thai | 0.029028 | 57 | images/doc_001830/doc_001830_image0001.png |
sample_0001737 | doc_001786 | single | 1,472 | 646 | [
0.523,
0.332,
0.617,
0.38
] | Это все изменит | 2 | 0 | 1 | [
"images/doc_001786/doc_001786_image0001.png"
] | Russian | 0.00456 | 15 | images/doc_001786/doc_001786_image0001.png |
sample_0001738 | doc_002562 | single | 780 | 600 | [
0.612,
0.201,
0.927,
0.275
] | Earning a doctorate in a structured
program (newer model) | 2 | 0 | 1 | [
"images/doc_002562/doc_002562_image0001.png"
] | English | 0.023488 | 57 | images/doc_002562/doc_002562_image0001.png |
sample_0001739 | doc_001820 | single | 1,450 | 1,168 | [
0.063,
0.972,
0.157,
0.995
] | रॉयल चैलेंजर्स बेंगलोर | 2 | 0 | 1 | [
"images/doc_001820/doc_001820_image0001.png"
] | Hindi | 0.002122 | 22 | images/doc_001820/doc_001820_image0001.png |
sample_0001740 | doc_001381 | single | 1,010 | 556 | [
0.01,
0.259,
0.309,
0.422
] | Gen Z puts crypto on holiday wish lists | 2 | 0 | 1 | [
"images/doc_001381/doc_001381_image0001.png"
] | English | 0.048759 | 39 | images/doc_001381/doc_001381_image0001.png |
sample_0001741 | doc_001808 | single | 1,205 | 857 | [
0.191,
0.877,
0.253,
0.902
] | पर ले आएं | 2 | 0 | 1 | [
"images/doc_001808/doc_001808_image0001.png"
] | Hindi | 0.001594 | 9 | images/doc_001808/doc_001808_image0001.png |
sample_0001742 | doc_002113 | single | 1,233 | 924 | [
0.387,
0.257,
0.461,
0.281
] | Main Trend | 2 | 0 | 1 | [
"images/doc_002113/doc_002113_image0001.png"
] | English | 0.001767 | 10 | images/doc_002113/doc_002113_image0001.png |
sample_0001743 | doc_001902 | single | 1,232 | 781 | [
0.324,
0.498,
0.602,
0.548
] | CÁN CÂN THANH TOÁN QUỐC TẾ | 2 | 0 | 1 | [
"images/doc_001902/doc_001902_image0001.png"
] | Vietnamese | 0.013954 | 3 | images/doc_001902/doc_001902_image0001.png |
sample_0001744 | doc_002019 | single | 1,164 | 1,532 | [
0.573,
0.703,
0.839,
0.723
] | Bounded composition of the MRM | 2 | 0 | 1 | [
"images/doc_002019/doc_002019_image0001.png"
] | English | 0.005439 | 30 | images/doc_002019/doc_002019_image0001.png |
sample_0001745 | doc_001946 | single | 851 | 942 | [
0.097,
0.747,
0.437,
0.781
] | Lave bem com água após o uso. | 2 | 0 | 1 | [
"images/doc_001946/doc_001946_image0001.png"
] | Portuguese | 0.011561 | 29 | images/doc_001946/doc_001946_image0001.png |
sample_0001746 | doc_001996 | single | 1,447 | 1,080 | [
0.054,
0.424,
0.422,
0.453
] | As IT infrastructures become more dynamic and data-intensive, | 3 | 0 | 1 | [
"images/doc_001996/doc_001996_image0001.png"
] | English | 0.010846 | 61 | images/doc_001996/doc_001996_image0001.png |
sample_0001747 | doc_002030 | single | 1,198 | 1,546 | [
0.568,
0.745,
0.703,
0.76
] | Molecular perturbation | 2 | 0 | 1 | [
"images/doc_002030/doc_002030_image0001.png"
] | English | 0.001999 | 22 | images/doc_002030/doc_002030_image0001.png |
sample_0001748 | doc_002032 | single | 1,312 | 1,164 | [
0.163,
0.819,
0.877,
0.848
] | At initialization, all external knowledge embeddings are reduced to a shared dimension via | 3 | 0 | 1 | [
"images/doc_002032/doc_002032_image0001.png"
] | English | 0.020841 | 90 | images/doc_002032/doc_002032_image0001.png |
sample_0001749 | doc_002112 | single | 1,511 | 1,047 | [
0.258,
0.325,
0.383,
0.355
] | Bias Amplification | 2 | 0 | 1 | [
"images/doc_002112/doc_002112_image0001.png"
] | English | 0.003782 | 18 | images/doc_002112/doc_002112_image0001.png |
sample_0001750 | doc_001907 | single | 458 | 591 | [
0.054,
0.354,
0.296,
0.411
] | Hồ Chí Minh | 2 | 0 | 1 | [
"images/doc_001907/doc_001907_image0001.png"
] | Vietnamese | 0.013766 | 11 | images/doc_001907/doc_001907_image0001.png |
sample_0001751 | doc_002063 | single | 720 | 925 | [
0.127,
0.862,
0.422,
0.88
] | Equatorial slices of key hydrodynamic | 2 | 0 | 1 | [
"images/doc_002063/doc_002063_image0001.png"
] | English | 0.005313 | 37 | images/doc_002063/doc_002063_image0001.png |
sample_0001752 | doc_002127 | single | 1,022 | 1,099 | [
0.315,
0.761,
0.44,
0.794
] | Accept Framing | 2 | 0 | 1 | [
"images/doc_002127/doc_002127_image0001.png"
] | English | 0.004113 | 14 | images/doc_002127/doc_002127_image0001.png |
sample_0001753 | doc_002050 | single | 1,249 | 519 | [
0.587,
0.16,
0.625,
0.198
] | Data | 1 | 0 | 1 | [
"images/doc_002050/doc_002050_image0001.png"
] | English | 0.001476 | 4 | images/doc_002050/doc_002050_image0001.png |
sample_0001754 | doc_002080 | single | 524 | 996 | [
0.17,
0.253,
0.933,
0.286
] | Hybrid architecture of the Legal AI system | 2 | 0 | 1 | [
"images/doc_002080/doc_002080_image0001.png"
] | English | 0.025148 | 42 | images/doc_002080/doc_002080_image0001.png |
sample_0001755 | doc_002048 | single | 619 | 832 | [
0.261,
0.416,
0.522,
0.442
] | Mapping network | 2 | 0 | 1 | [
"images/doc_002048/doc_002048_image0001.png"
] | English | 0.006761 | 15 | images/doc_002048/doc_002048_image0001.png |
sample_0001756 | doc_001365 | single | 731 | 654 | [
0.105,
0.022,
0.726,
0.065
] | Paste the path of the desired image into the src="". | 3 | 0 | 1 | [
"images/doc_001365/doc_001365_image0001.png"
] | English | 0.026914 | 52 | images/doc_001365/doc_001365_image0001.png |
sample_0001757 | doc_002074 | single | 823 | 787 | [
0.254,
0.505,
0.584,
0.538
] | Four different asymptotic regions given | 2 | 0 | 1 | [
"images/doc_002074/doc_002074_image0001.png"
] | English | 0.010872 | 39 | images/doc_002074/doc_002074_image0001.png |
sample_0001758 | doc_002103 | single | 1,340 | 1,019 | [
0.768,
0.773,
0.842,
0.792
] | Discriminator | 1 | 0 | 1 | [
"images/doc_002103/doc_002103_image0001.png"
] | English | 0.001356 | 13 | images/doc_002103/doc_002103_image0001.png |
sample_0001759 | doc_002040 | single | 1,176 | 1,480 | [
0.028,
0.62,
0.416,
0.647
] | Safety constraint threshold selection. | 2 | 0 | 1 | [
"images/doc_002040/doc_002040_image0001.png"
] | English | 0.01038 | 38 | images/doc_002040/doc_002040_image0001.png |
sample_0001760 | doc_002104 | single | 901 | 1,089 | [
0.088,
0.215,
0.467,
0.237
] | High-level aspects of our replacement strategy | 3 | 0 | 1 | [
"images/doc_002104/doc_002104_image0001.png"
] | English | 0.008301 | 46 | images/doc_002104/doc_002104_image0001.png |
sample_0001761 | doc_002116 | single | 1,325 | 820 | [
0.248,
0.253,
0.315,
0.281
] | Respirations | 1 | 0 | 1 | [
"images/doc_002116/doc_002116_image0001.png"
] | English | 0.001879 | 12 | images/doc_002116/doc_002116_image0001.png |
sample_0001762 | doc_002097 | single | 791 | 1,022 | [
0.057,
0.133,
0.235,
0.152
] | Factorized Inference | 2 | 0 | 1 | [
"images/doc_002097/doc_002097_image0001.png"
] | English | 0.003344 | 20 | images/doc_002097/doc_002097_image0001.png |
sample_0001763 | doc_002033 | single | 1,646 | 760 | [
0.402,
0.647,
0.604,
0.685
] | Subject-wise Latent Alignment Layers | 3 | 0 | 1 | [
"images/doc_002033/doc_002033_image0001.png"
] | English | 0.007631 | 36 | images/doc_002033/doc_002033_image0001.png |
sample_0001764 | doc_002129 | single | 496 | 712 | [
0.145,
0.67,
0.315,
0.696
] | Steering Vector | 2 | 0 | 1 | [
"images/doc_002129/doc_002129_image0001.png"
] | English | 0.004404 | 15 | images/doc_002129/doc_002129_image0001.png |
sample_0001765 | doc_002069 | single | 793 | 1,204 | [
0.825,
0.298,
0.919,
0.316
] | enzymes | 1 | 0 | 1 | [
"images/doc_002069/doc_002069_image0001.png"
] | English | 0.001694 | 7 | images/doc_002069/doc_002069_image0001.png |
sample_0001766 | doc_002130 | single | 1,020 | 868 | [
0.573,
0.332,
0.687,
0.358
] | Loss-Scaling | 2 | 0 | 1 | [
"images/doc_002130/doc_002130_image0001.png"
] | English | 0.002963 | 12 | images/doc_002130/doc_002130_image0001.png |
sample_0001767 | doc_002090 | single | 1,109 | 756 | [
0.249,
0.367,
0.347,
0.427
] | Vulnerability Dataset | 2 | 0 | 1 | [
"images/doc_002090/doc_002090_image0001.png"
] | English | 0.005871 | 21 | images/doc_002090/doc_002090_image0001.png |
sample_0001768 | doc_002123 | single | 697 | 1,062 | [
0.558,
0.015,
0.758,
0.033
] | Knowledge Graph Builder | 2 | 0 | 1 | [
"images/doc_002123/doc_002123_image0001.png"
] | English | 0.003603 | 23 | images/doc_002123/doc_002123_image0001.png |
sample_0001769 | doc_002025 | single | 1,732 | 1,192 | [
0.457,
0.538,
0.578,
0.563
] | Immunogenicity Risk | 2 | 0 | 1 | [
"images/doc_002025/doc_002025_image0001.png"
] | English | 0.002953 | 19 | images/doc_002025/doc_002025_image0001.png |
sample_0001770 | doc_002094 | single | 920 | 1,124 | [
0.619,
0.617,
0.946,
0.638
] | d) Benchmark Construction Pipeline Overview | 3 | 0 | 1 | [
"images/doc_002094/doc_002094_image0001.png"
] | English | 0.006729 | 43 | images/doc_002094/doc_002094_image0001.png |
sample_0001771 | doc_002044 | single | 1,378 | 738 | [
0.255,
0.599,
0.59,
0.655
] | Examples of block, tree and chain graphs | 3 | 0 | 1 | [
"images/doc_002044/doc_002044_image0001.png"
] | English | 0.018765 | 40 | images/doc_002044/doc_002044_image0001.png |
sample_0001772 | doc_002124 | single | 839 | 1,173 | [
0.015,
0.155,
0.22,
0.173
] | Handling the missing data | 2 | 0 | 1 | [
"images/doc_002124/doc_002124_image0001.png"
] | English | 0.003678 | 25 | images/doc_002124/doc_002124_image0001.png |
sample_0001773 | doc_002079 | single | 1,167 | 802 | [
0.155,
0.381,
0.592,
0.419
] | retrieved candidates to incorporate more discriminative information | 3 | 0 | 1 | [
"images/doc_002079/doc_002079_image0001.png"
] | English | 0.016384 | 67 | images/doc_002079/doc_002079_image0001.png |
sample_0001774 | doc_002051 | single | 720 | 727 | [
0.527,
0.931,
0.906,
0.951
] | matching sources are marked in the upper panel | 2 | 0 | 1 | [
"images/doc_002051/doc_002051_image0001.png"
] | English | 0.007401 | 46 | images/doc_002051/doc_002051_image0001.png |
sample_0001775 | doc_002059 | single | 638 | 868 | [
0.57,
0.419,
0.803,
0.462
] | generation to test backend electronics | 2 | 0 | 1 | [
"images/doc_002059/doc_002059_image0001.png"
] | English | 0.009882 | 38 | images/doc_002059/doc_002059_image0001.png |
sample_0001776 | doc_002089 | single | 1,766 | 839 | [
0.4,
0.562,
0.502,
0.615
] | Communication Infrastructure | 2 | 0 | 1 | [
"images/doc_002089/doc_002089_image0001.png"
] | English | 0.005444 | 28 | images/doc_002089/doc_002089_image0001.png |
sample_0001777 | doc_002111 | single | 1,021 | 848 | [
0.129,
0.261,
0.277,
0.281
] | Psychological Analyst | 2 | 0 | 1 | [
"images/doc_002111/doc_002111_image0001.png"
] | English | 0.002956 | 21 | images/doc_002111/doc_002111_image0001.png |
sample_0001778 | doc_002119 | single | 1,348 | 791 | [
0.129,
0.747,
0.33,
0.781
] | Overview of the Proposed EvaPose | 3 | 0 | 1 | [
"images/doc_002119/doc_002119_image0001.png"
] | English | 0.006889 | 32 | images/doc_002119/doc_002119_image0001.png |
sample_0001779 | doc_002071 | single | 435 | 843 | [
0.137,
0.886,
0.546,
0.909
] | Potential energy landscape | 2 | 0 | 1 | [
"images/doc_002071/doc_002071_image0001.png"
] | English | 0.009652 | 26 | images/doc_002071/doc_002071_image0001.png |
sample_0001780 | doc_002024 | single | 1,808 | 1,376 | [
0.767,
0.443,
0.881,
0.468
] | Multi-Modal Omics | 2 | 0 | 1 | [
"images/doc_002024/doc_002024_image0001.png"
] | English | 0.002817 | 17 | images/doc_002024/doc_002024_image0001.png |
sample_0001781 | doc_002029 | single | 1,440 | 1,304 | [
0.174,
0.627,
0.539,
0.653
] | Typical Agent Behavior: Maximize Efficacy Only | 3 | 0 | 1 | [
"images/doc_002029/doc_002029_image0001.png"
] | English | 0.009691 | 46 | images/doc_002029/doc_002029_image0001.png |
sample_0001782 | doc_002061 | single | 1,237 | 953 | [
0.666,
0.932,
0.778,
0.967
] | a curved slice | 2 | 0 | 1 | [
"images/doc_002061/doc_002061_image0001.png"
] | English | 0.003881 | 14 | images/doc_002061/doc_002061_image0001.png |
sample_0001783 | doc_002023 | single | 1,324 | 714 | [
0.353,
0.7,
0.516,
0.735
] | Latent Cellular Transport Module | 3 | 0 | 1 | [
"images/doc_002023/doc_002023_image0001.png"
] | English | 0.005673 | 32 | images/doc_002023/doc_002023_image0001.png |
sample_0001784 | doc_002060 | single | 1,375 | 916 | [
0.614,
0.82,
0.671,
0.859
] | RF Power Combiner | 2 | 0 | 1 | [
"images/doc_002060/doc_002060_image0001.png"
] | English | 0.002185 | 17 | images/doc_002060/doc_002060_image0001.png |
sample_0001785 | doc_002108 | single | 877 | 1,118 | [
0.065,
0.844,
0.447,
0.873
] | Regularization via View Cycle Consistency | 2 | 0 | 1 | [
"images/doc_002108/doc_002108_image0001.png"
] | English | 0.011051 | 41 | images/doc_002108/doc_002108_image0001.png |
sample_0001786 | doc_002021 | single | 1,334 | 1,632 | [
0.68,
0.056,
0.851,
0.072
] | Temporal Encoding with Mamba | 2 | 0 | 1 | [
"images/doc_002021/doc_002021_image0001.png"
] | English | 0.002688 | 28 | images/doc_002021/doc_002021_image0001.png |
sample_0001787 | doc_002035 | single | 2,126 | 1,298 | [
0.394,
0.416,
0.623,
0.461
] | Post-hoc dynamical analysis | 2 | 0 | 1 | [
"images/doc_002035/doc_002035_image0001.png"
] | English | 0.010232 | 27 | images/doc_002035/doc_002035_image0001.png |
sample_0001788 | doc_002093 | single | 1,160 | 1,004 | [
0.157,
0.265,
0.283,
0.287
] | Magnitude Spectrum | 2 | 0 | 1 | [
"images/doc_002093/doc_002093_image0001.png"
] | English | 0.002729 | 18 | images/doc_002093/doc_002093_image0001.png |
sample_0001789 | doc_002121 | single | 712 | 982 | [
0.79,
0.267,
0.956,
0.289
] | Policy Orchestrator | 2 | 0 | 1 | [
"images/doc_002121/doc_002121_image0001.png"
] | English | 0.003519 | 19 | images/doc_002121/doc_002121_image0001.png |
sample_0001790 | doc_002115 | single | 1,039 | 1,062 | [
0.605,
0.083,
0.679,
0.101
] | Task History | 2 | 0 | 1 | [
"images/doc_002115/doc_002115_image0001.png"
] | English | 0.001405 | 12 | images/doc_002115/doc_002115_image0001.png |
sample_0001791 | doc_002084 | single | 1,095 | 1,131 | [
0.036,
0.114,
0.12,
0.141
] | Speech Token | 2 | 0 | 1 | [
"images/doc_002084/doc_002084_image0001.png"
] | English | 0.002236 | 12 | images/doc_002084/doc_002084_image0001.png |
sample_0001792 | doc_002083 | single | 1,185 | 756 | [
0.06,
0.115,
0.236,
0.15
] | Stage 2: Dashboard Design | 3 | 0 | 1 | [
"images/doc_002083/doc_002083_image0001.png"
] | English | 0.006148 | 25 | images/doc_002083/doc_002083_image0001.png |
sample_0001793 | doc_002075 | single | 643 | 860 | [
0.206,
0.253,
0.372,
0.286
] | Spectral Curve | 2 | 0 | 1 | [
"images/doc_002075/doc_002075_image0001.png"
] | English | 0.005609 | 14 | images/doc_002075/doc_002075_image0001.png |
sample_0001794 | doc_002087 | single | 1,501 | 928 | [
0.446,
0.646,
0.645,
0.678
] | Secure Model Engineering | 2 | 0 | 1 | [
"images/doc_002087/doc_002087_image0001.png"
] | English | 0.006483 | 24 | images/doc_002087/doc_002087_image0001.png |
sample_0001795 | doc_002034 | single | 1,966 | 1,250 | [
0.624,
0.065,
0.877,
0.112
] | Physically Constrained Flow Matching | 3 | 0 | 1 | [
"images/doc_002034/doc_002034_image0001.png"
] | English | 0.011919 | 36 | images/doc_002034/doc_002034_image0001.png |
sample_0001796 | doc_002039 | single | 1,104 | 1,568 | [
0.089,
0.58,
0.495,
0.599
] | Percentages of the 50 training parameter candidates | 3 | 0 | 1 | [
"images/doc_002039/doc_002039_image0001.png"
] | English | 0.00799 | 51 | images/doc_002039/doc_002039_image0001.png |
sample_0001797 | doc_002058 | single | 730 | 689 | [
0.097,
0.09,
0.229,
0.116
] | RFoF Module | 2 | 0 | 1 | [
"images/doc_002058/doc_002058_image0001.png"
] | English | 0.003535 | 11 | images/doc_002058/doc_002058_image0001.png |
sample_0001798 | doc_002105 | single | 858 | 1,078 | [
0.047,
0.693,
0.395,
0.715
] | Components of the Agentic Workflow | 2 | 0 | 1 | [
"images/doc_002105/doc_002105_image0001.png"
] | English | 0.007653 | 34 | images/doc_002105/doc_002105_image0001.png |
sample_0001799 | doc_002042 | single | 1,282 | 514 | [
0.064,
0.821,
0.226,
0.884
] | Local road network | 2 | 0 | 1 | [
"images/doc_002042/doc_002042_image0001.png"
] | English | 0.010104 | 18 | images/doc_002042/doc_002042_image0001.png |
sample_0001800 | doc_002049 | single | 1,305 | 638 | [
0.12,
0.799,
0.599,
0.852
] | Mismatch distributions for the model-generated waveforms. | 3 | 0 | 1 | [
"images/doc_002049/doc_002049_image0001.png"
] | English | 0.025231 | 57 | images/doc_002049/doc_002049_image0001.png |
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