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H05-1115
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C90-3046
train
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INTERSPEECH_2008_21_abs
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A92-1026
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P02-1060
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H93-1076
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ECCV_2014_47_abs
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IJCAI_2003_15_abs
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E06-1045
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CVPR_2010_11_abs
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A92-1027
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I08-1027
train
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A94-1037
train
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P05-1069
train
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P05-1032
train
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H94-1102
train
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P06-2110
train
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H05-1012
train
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N03-3010
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I05-2044
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C80-1039
train
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I05-5009
train
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H90-1016
train
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CVPR_2015_300_abs
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INTERSPEECH_2007_21_abs
train
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C88-2086
train
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E99-1029
train
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NIPS_2002_10_abs
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P02-1059
train
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W02-1404
train
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P05-2008
train
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CVPR_2013_10_abs
train
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C86-1132
train
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P80-1026
train
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H01-1001
train
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I05-4008
train
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J87-3001
train
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I05-3022
train
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P05-3025
train
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H91-1077
train
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C86-1021
train
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C92-1052
train
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C02-1071
train
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ECCV_2016_215_abs
train
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A92-1010
train
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P03-1058
train
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E95-1036
train
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P06-1112
train
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A92-1023
train
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CVPR_2014_21_abs
train
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ICASSP_2011_587_abs
train
[{"sentence": "In this paper , we propose a novel algorithm to detect/compensate on-line interference effects when integrating Global Navigation Satellite System -LRB- GNSS -RRB- and Inertial Navigation System -LRB- INS -RRB- .", "entities": [{"text": "algorithm", "type": "Generic"}, {"text": "on-line interference effe...
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CVPR_2012_11_abs
train
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ECCV_2016_205_abs
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CVPR_2009_21_abs
train
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AAAI_2015_11_abs
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C90-3007
train
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AAAI_2008_262_abs
train
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ECCV_2012_37_abs
train
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[[[6, 6], [30, 30]]]
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A97-1050
train
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W04-1307
train
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ICML_2006_122_abs
train
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C88-2166
train
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N01-1003
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H92-1036
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C94-1088
train
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N03-1001
train
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IJCAI_2013_15_abs
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E93-1043
train
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P08-2034
train
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P06-1052
train
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E87-1037
train
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W02-1403
train
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N03-2006
train
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ECCV_2016_107_abs
train
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ICCV_2015_50_abs
train
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I05-2014
train
[{"sentence": "Automatic evaluation metrics for Machine Translation -LRB- MT -RRB- systems , such as BLEU or NIST , are now well established .", "entities": [{"text": "Automatic evaluation metrics", "type": "Metric"}, {"text": "Machine Translation -LRB- MT -RRB- systems", "type": "Task"}, {"text": "BLEU", "type": "Metr...
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C82-1054
train
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INTERSPEECH_2014_28_abs
train
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IJCAI_2013_4_abs
train
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INTERSPEECH_2014_31_abs
train
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E89-1040
train
[{"sentence": "Theoretical research in the area of machine translation usually involves the search for and creation of an appropriate formalism .", "entities": [{"text": "machine translation", "type": "Task"}, {"text": "formalism", "type": "Generic"}], "relations": [{"head": "formalism", "tail": "machine translation", ...
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CVPR_2006_11_abs
train
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INTERSPEECH_2001_31_abs
train
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[[[10, 11], [70, 71]], [[0, 1], [153, 153]], [[107, 108], [147, 148]]]
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C88-2162
train
[{"sentence": "Computer programs so far have not fared well in modeling language acquisition .", "entities": [{"text": "Computer programs", "type": "Generic"}, {"text": "language acquisition", "type": "Task"}], "relations": []}, {"sentence": "For one thing , learning methodology applicable in general domains does not r...
[[[5, 7], [53, 54], [79, 79], [94, 94]], [[13, 13], [39, 39]]]
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P04-2010
train
[{"sentence": "This paper presents a novel ensemble learning approach to resolving German pronouns .", "entities": [{"text": "ensemble learning approach", "type": "Method"}, {"text": "German pronouns", "type": "OtherScientificTerm"}], "relations": [{"head": "ensemble learning approach", "tail": "German pronouns", "labe...
[[[11, 12], [36, 38], [48, 48]], [[20, 23], [30, 33]], [[58, 59], [81, 82], [112, 113], [119, 120]]]
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P06-2067
train
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P05-1058
train
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P06-1088
train
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CVPR_1996_15_abs
train
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[[[0, 0], [38, 38], [64, 64], [100, 101], [125, 126]]]
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INTERSPEECH_2001_21_abs
train
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[[[36, 36], [68, 69]], [[12, 13], [33, 34], [79, 79]], [[3, 6], [54, 54], [91, 91]]]
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ICCV_2003_150_abs
train
[{"sentence": "We present a single-image highlight removal method that incorporates illumination-based constraints into image in-painting .", "entities": [{"text": "single-image highlight removal method", "type": "Method"}, {"text": "illumination-based constraints", "type": "OtherScientificTerm"}, {"text": "image in-pa...
[[[8, 8], [11, 17], [97, 97], [114, 114]]]
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CVPR_2001_111_abs
train
[{"sentence": "In this paper , we propose a novel method , called local non-negative matrix factorization -LRB- LNMF -RRB- , for learning spatially localized , parts-based subspace representation of visual patterns .", "entities": [{"text": "method", "type": "Generic"}, {"text": "local non-negative matrix factorization...
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IJCAI_2001_5_abs
train
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[[[15, 16], [42, 42], [61, 61]]]
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P06-2001
train
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[[[63, 67], [75, 75]]]
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L08-1050
train
[{"sentence": "The present paper reports on a preparatory research for building a language corpus annotation scenario capturing the discourse relations in Czech .", "entities": [{"text": "language corpus annotation scenario", "type": "Material"}, {"text": "discourse relations", "type": "OtherScientificTerm"}, {"text": ...
[[[22, 23], [60, 60], [99, 100]], [[109, 114], [142, 142]]]
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ICCV_2013_50_abs
train
[{"sentence": "Regression-based techniques have shown promising results for people counting in crowded scenes .", "entities": [{"text": "Regression-based techniques", "type": "Method"}, {"text": "people counting in crowded scenes", "type": "Task"}], "relations": [{"head": "Regression-based techniques", "tail": "people ...
[]
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CVPR_2001_110_abs
train
[{"sentence": "Representing images with layers has many important applications , such as video compression , motion analysis , and 3D scene analysis .", "entities": [{"text": "Representing images with layers", "type": "Method"}, {"text": "applications", "type": "Generic"}, {"text": "video compression", "type": "Task"},...
[[[13, 13], [29, 29]], [[80, 81], [96, 96]], [[123, 124], [140, 140], [148, 148]]]
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AAAI_2008_254_abs
train
[{"sentence": "The construction of causal graphs from non-experimental data rests on a set of constraints that the graph structure imposes on all probability distributions compatible with the graph .", "entities": [{"text": "construction of causal graphs", "type": "Task"}, {"text": "non-experimental data", "type": "Mat...
[[[35, 35], [37, 41], [129, 129], [132, 132], [151, 151], [199, 202]]]
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CVPR_2016_405_abs
train
[{"sentence": "With the recent popularity of animated GIFs on social media , there is need for ways to index them with rich meta-data .", "entities": [{"text": "animated GIFs", "type": "Material"}, {"text": "social media", "type": "Material"}, {"text": "rich meta-data", "type": "Material"}], "relations": [{"head": "soc...
[[[29, 29], [35, 38], [49, 49], [61, 62]], [[6, 8], [32, 33], [79, 80]], [[0, 1], [16, 16]]]
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E85-1037
train
[{"sentence": "Systemic grammar has been used for AI text generation work in the past , but the implementations have tended be ad hoc or inefficient .", "entities": [{"text": "Systemic grammar", "type": "Method"}, {"text": "AI text generation", "type": "Task"}, {"text": "implementations", "type": "Generic"}], "relation...