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TR-13923
[ "A", "series", "of", "experiments", "demonstrated", "that", "neurons", "in", "the", "human", "medial", "temporal", "lobe", "(", "MTL", ")", "fire", "selectively", "to", "images", "of", "faces", ",", "animals", ",", "and", "other", "objects", "or", "scenes", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: A series of experiments demonstrated that neurons in the human medial temporal lobe ( MTL ) fire selectively to images of faces , animals , and other objects or scenes .
medial temporal lobe
TR-13924
[ "We", "process", "simulated", "raw", "images", "using", "a", "configurable", ",", "industry", "-", "grade", ",", "high", "dynamic", "range", "(", "HDR", ")", "ISP", "to", "generate", "RGB", "images", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 1, 4, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We process simulated raw images using a configurable , industry - grade , high dynamic range ( HDR ) ISP to generate RGB images .
high dynamic range
TR-13925
[ "We", "begin", "by", "introducing", "another", "important", "concept", "in", "the", "RIP", "framework", "-", "restricted", "orthogonal", "constants", "(", "ROC", ")", "proposed", "in", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We begin by introducing another important concept in the RIP framework - restricted orthogonal constants ( ROC ) proposed in .
restricted orthogonal constants
TR-13926
[ "We", "report", "average", "precision", "(", "AP", ")", "with", "IoU", "(", "Intersection", "over", "Union", ")", "thresholds", "at", "0.5", "and", "0.7", "." ]
[ 4, 4, 0, 2, 4, 1, 4, 4, 1, 4, 0, 2, 2, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We report average precision ( AP ) with IoU ( Intersection over Union ) thresholds at 0.5 and 0.7 .
average precision, Intersection over Union
TR-13927
[ "Considering", "the", "computational", "requirements", ",", "several", "muti", "-", "view", "methods", "using", "the", "augmented", "state", "technique", "for", "navigation", "aiding", "have", "been", "already", "proposed", ",", "which", "is", "an", "approach", "commonly", "referred", "to", "as", "simultaneous", "localization", "and", "mapping", "(", "SLAM", ")", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Considering the computational requirements , several muti - view methods using the augmented state technique for navigation aiding have been already proposed , which is an approach commonly referred to as simultaneous localization and mapping ( SLAM ) .
simultaneous localization and mapping
TR-13928
[ "Traditionally", ",", "crop", "statistics", "data", "are", "produced", "by", "national", "statistical", "offices", "(", "NSO", ")", "using", "adequate", "sampling", "strategies", "and", "statistical", "inference", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Traditionally , crop statistics data are produced by national statistical offices ( NSO ) using adequate sampling strategies and statistical inference .
national statistical offices
TR-13929
[ "We", "define", "the", "Coupling", "Between", "Microservice", "(", "CBM", ")", "extending", "the", "well", "-", "known", "Coupling", "Between", "Object", "(", "CBO", ")", "metric", "proposed", "by", "Chidamber", "and", "Kemerer", "Chidamber1994", "." ]
[ 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We define the Coupling Between Microservice ( CBM ) extending the well - known Coupling Between Object ( CBO ) metric proposed by Chidamber and Kemerer Chidamber1994 .
Coupling Between Microservice, Coupling Between Object
TR-13930
[ "We", "employ", "catSeq", "model", "for", "the", "generation", "process", ",", "which", "uses", "an", "encoder", "-", "decoder", "framework", ":", "the", "encoder", "being", "a", "bidirectional", "Gated", "Recurrent", "Unit", "(", "bi", "-", "GRU", ")", "and", "the", "decoder", "a", "forward", "GRU", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 4, 1, 3, 3, 4, 4, 4, 4, 4, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We employ catSeq model for the generation process , which uses an encoder - decoder framework : the encoder being a bidirectional Gated Recurrent Unit ( bi - GRU ) and the decoder a forward GRU .
bidirectional Gated Recurrent Unit
TR-13931
[ "In", "the", "following", "sections", ",", "we", "introduce", "an", "artifact", "disentanglement", "network", "(", "ADN", ")", "that", "learns", "these", "encodings", "and", "decodings", "without", "paired", "data", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In the following sections , we introduce an artifact disentanglement network ( ADN ) that learns these encodings and decodings without paired data .
artifact disentanglement network
TR-13932
[ "-", "From", "a", "practical", "perspective", ",", "it", "is", "desirable", "to", "have", "consistent", "embeddings", "for", "the", "same", "input", "graph", "irrespective", "of", "the", "order", "in", "which", "the", "nodes", "are", "processed", "or", "whether", "their", "IDs", "are", "modified", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: - From a practical perspective , it is desirable to have consistent embeddings for the same input graph irrespective of the order in which the nodes are processed or whether their IDs are modified .
No expansions found
TR-13933
[ "The", "research", "leading", "to", "these", "results", "has", "received", "funding", "from", "the", "European", "Research", "Council", "under", "the", "European", "Union", "'s", "Seventh", "Framework", "Programme", "(", "FP7/2007", "-", "2013", ")", "ERC", "grant", "agreement", "no", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The research leading to these results has received funding from the European Research Council under the European Union 's Seventh Framework Programme ( FP7/2007 - 2013 ) ERC grant agreement no .
European Research Council
TR-13934
[ "For", "two", "subqueries", "and", ",", "where", ",", "may", "be", "related", "to", "in", "one", "of", "the", "following", "relationship", "types", "OO", ",", "PP", ",", "SS", ",", "OP", ",", "OS", ",", "PS", ",", "PO", ",", "SP", ",", "SO", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 1, 4, 1, 4, 1, 4, 1, 4, 1, 4, 1, 4, 1, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: For two subqueries and , where , may be related to in one of the following relationship types OO , PP , SS , OP , OS , PS , PO , SP , SO .
No expansions found
TR-13935
[ "We", "divide", "the", "DP", "generation", "task", "into", "two", "phases", ":", "DP", "detection", "(", "from", "which", "position", "a", "pronoun", "is", "dropped", ")", ",", "and", "DP", "prediction", "(", "which", "pronoun", "is", "dropped", ")", "." ]
[ 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We divide the DP generation task into two phases : DP detection ( from which position a pronoun is dropped ) , and DP prediction ( which pronoun is dropped ) .
No expansions found
TR-13936
[ "For", "denoising", "with", "deep", "learning", ",", "often", "a", "Mean", "Square", "Error", "(", "MSE", ")", "is", "used", "as", "a", "loss", "function", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: For denoising with deep learning , often a Mean Square Error ( MSE ) is used as a loss function .
Mean Square Error
TR-13937
[ "One", "of", "the", "main", "reasons", "for", "creating", "Aadhaar", "as", "a", "huge", "Social", "Identification", "System", "(", "SIS", ")", "had", "been", "to", "prevent", "massive", "leakages", "and", "large", "scale", "fraudulent", "transactions", "in", "implementation", "of", "targeted", "delivery", "of", "subsidies", "for", "the", "poor", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: One of the main reasons for creating Aadhaar as a huge Social Identification System ( SIS ) had been to prevent massive leakages and large scale fraudulent transactions in implementation of targeted delivery of subsidies for the poor .
Social Identification System
TR-13938
[ "Third", ",", "Simple", "Neural", "AttentIve", "Learner", "(", "SNAIL", ")", "extends", "the", "idea", "behind", "Learning", "to", "reinforcement", "learn", "and", "RL", "by", "using", "a", "more", "powerful", "temporal", "-", "focused", "model", "than", "the", "simple", "RNN", "." ]
[ 4, 4, 0, 2, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Third , Simple Neural AttentIve Learner ( SNAIL ) extends the idea behind Learning to reinforcement learn and RL by using a more powerful temporal - focused model than the simple RNN .
Simple Neural AttentIve Learner, reinforcement learn
TR-13939
[ "Hidden", "Markov", "Models", "on", "Dynamic", "Features", "The", "method", "denoted", "as", "is", "a", "direct", "application", "of", "HMM", "to", "sequential", "data", "." ]
[ 0, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Hidden Markov Models on Dynamic Features The method denoted as is a direct application of HMM to sequential data .
Hidden Markov Models
TR-13940
[ "Sidestream", "Dark", "Field", "(", "SDF", ")", "imaging", ":", "a", "novel", "stroboscopic", "LED", "ring", "-", "based", "imaging", "modality", "for", "clinical", "assessment", "of", "the", "microcirculation", "." ]
[ 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Sidestream Dark Field ( SDF ) imaging : a novel stroboscopic LED ring - based imaging modality for clinical assessment of the microcirculation .
Sidestream Dark Field
TR-13941
[ "Performance", "is", "evaluated", "using", "the", "eer", "and", "the", "minimum", "Decision", "Cost", "Function", "(", "DCF", ")", "calculated", "using", ",", ",", "and", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Performance is evaluated using the eer and the minimum Decision Cost Function ( DCF ) calculated using , , and .
Decision Cost Function
TR-13942
[ "We", "plot", "the", "median", "recovery", "error", "(", "MRE", ")", "for", "100", "iterations", "." ]
[ 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We plot the median recovery error ( MRE ) for 100 iterations .
median recovery error
TR-13943
[ "When", "computing", "the", "Point", "Cloud", "(", "PC", ")", "from", "the", "images", "of", "the", "colour", "cameras", ",", "we", "have", "been", "obtaining", "reconstructions", "of", "the", "intersections", "displaced", "from", "the", "correct", "positions", "." ]
[ 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: When computing the Point Cloud ( PC ) from the images of the colour cameras , we have been obtaining reconstructions of the intersections displaced from the correct positions .
Point Cloud
TR-13944
[ "We", "introduce", "surrogate", "probability", "action", "and", "develop", "the", "probability", "surrogate", "action", "deterministic", "policy", "gradient", "(", "PSADPG", ")", "algorithm", "based", "on", "SAEI", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 4, 1, 4, 4, 4, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We introduce surrogate probability action and develop the probability surrogate action deterministic policy gradient ( PSADPG ) algorithm based on SAEI .
probability surrogate action deterministic policy gradient
TR-13945
[ "We", "thus", "evaluate", "weighted", "coverage", "(", "Cov", ")", ",", "average", "precision", "(", "AP", ")", "as", "well", "as", "instance", "level", "precision", "and", "recall", "at", "." ]
[ 4, 4, 4, 4, 0, 4, 1, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We thus evaluate weighted coverage ( Cov ) , average precision ( AP ) as well as instance level precision and recall at .
coverage, average precision
TR-13946
[ "In", "addition", ",", "the", "adaptive", "adversarial", "loss", "is", "designed", "to", "force", "the", "refiner", "to", "pay", "more", "attention", "to", "the", "prediction", "of", "the", "myelin", "content", "in", "MS", "lesions", "and", "normal", "appearing", "white", "matter", "(", "NAWM", ")", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In addition , the adaptive adversarial loss is designed to force the refiner to pay more attention to the prediction of the myelin content in MS lesions and normal appearing white matter ( NAWM ) .
normal appearing white matter
TR-13947
[ "Similarly", ",", "a", "stringset", "is", "Piecewise", "-Testable", "(", "PT", ")", "iff", "for", "all", ",", "it", "is", "the", "case", "that", "if", "then", "either", "or", "." ]
[ 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Similarly , a stringset is Piecewise -Testable ( PT ) iff for all , it is the case that if then either or .
Piecewise -Testable
TR-13948
[ "In", ",", "an", "FD", "device", "-", "to", "-", "device", "aided", "cooperative", "NOMA", "scheme", "was", "proposed", "where", "the", "near", "user", "is", "FD", "capable", "and", "assist", "the", "base", "station", "(", "BS", ")", "transmissions", "to", "the", "far", "user", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In , an FD device - to - device aided cooperative NOMA scheme was proposed where the near user is FD capable and assist the base station ( BS ) transmissions to the far user .
base station
TR-13949
[ "On", "similar", "lines", ",", "a", "phase", "response", "curve", "(", "PRC", ")", "based", "technique", "effectively", "helps", "to", "manoeuvre", "an", "ensemble", "of", "TCLs", "by", "using", "a", "control", "input", "to", "modulate", "duty", "cycles", "as", "well", "as", "induce", "delay", "/", "advance", "and", "thereby", "changing", "the", "set", "point", "temperature", "." ]
[ 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: On similar lines , a phase response curve ( PRC ) based technique effectively helps to manoeuvre an ensemble of TCLs by using a control input to modulate duty cycles as well as induce delay / advance and thereby changing the set point temperature .
phase response curve
TR-13950
[ "shows", "the", "correctness", "of", "the", "DS", "labels", "on", "the", "dev", "set", "." ]
[ 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: shows the correctness of the DS labels on the dev set .
No expansions found
TR-13951
[ "The", "curves", "of", "CO2", "density", "and", "passenger", "flow", "for", "a", "station", "in", "Aug.", "30", "(", "a", "working", "day", ")", "and", "Aug.31", "(", "a", "weekend", ")", "are", "plotted", "in", "Fig", "..", "The", "curves", "of", "the", "CO2", "variations", "and", "the", "passenger", "flows", "show", "similar", "trends", "at", "corresponding", "time", "." ]
[ 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The curves of CO2 density and passenger flow for a station in Aug. 30 ( a working day ) and Aug.31 ( a weekend ) are plotted in Fig .. The curves of the CO2 variations and the passenger flows show similar trends at corresponding time .
No expansions found
TR-13952
[ "Illustrating", "this", "last", "point", ",", "IN4", "says", ",", "\"", "I", "asked", "my", "friends", "...", "I", "came", "across", "2", "or", "3", "friends", ",", "they", "told", "me", "that", "their", "...", "accounts", "had", "been", "hacked", "...", "So", ",", "I", "thought", ",", "ok", "it", "'s", "not", "just", "me", ".", "\"" ]
[ 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Illustrating this last point , IN4 says , " I asked my friends ... I came across 2 or 3 friends , they told me that their ... accounts had been hacked ... So , I thought , ok it 's not just me . "
No expansions found
TR-13953
[ "Such", "a", "trend", "towards", "decentralization", "reduces", "the", "amount", "of", "data", "that", "is", "transferred", "to", "the", "cloud", "for", "processing", "and", "analysis", ",", "and", "can", "also", "be", "instrumental", "to", "improve", "security", "and", "privacy", "of", "the", "managed", "data", ",", "a", "major", "concern", "in", "the", "IoT", "scenario", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Such a trend towards decentralization reduces the amount of data that is transferred to the cloud for processing and analysis , and can also be instrumental to improve security and privacy of the managed data , a major concern in the IoT scenario .
No expansions found
TR-13954
[ "Although", "a", "CI", "user", "can", "understand", "a", "good", "percentage", "of", "speech", "(", "around", "30", ")", "by", "the", "movement", "of", "the", "lips", ",", "this", "study", "is", "interested", "to", "analyze", "how", "well", "a", "CI", "-", "user", "can", "identify", "a", "distant", "speaker", "which", "include", "voice", "from", "a", "radio", "or", "someone", "over", "the", "phone", "." ]
[ 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Although a CI user can understand a good percentage of speech ( around 30 ) by the movement of the lips , this study is interested to analyze how well a CI - user can identify a distant speaker which include voice from a radio or someone over the phone .
No expansions found
TR-13955
[ "To", "address", "this", "problem", "of", "information", "efficiency", ",", "ensembles", "of", "conformal", "predictors", "were", "introduced", "such", "as", "Cross", "Conformal", "Prediction", "(", "CCP", ")", "vovk2015cross", ",", "papadopoulos2015cross", ",", "Aggregated", "Conformal", "Prediction", "(", "ACP", ")", "carlsson2014aggregated", ",", "Combination", "of", "inductive", "mondrian", "conformal", "predictors", "toccaceli2018combination", "etc", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: To address this problem of information efficiency , ensembles of conformal predictors were introduced such as Cross Conformal Prediction ( CCP ) vovk2015cross , papadopoulos2015cross , Aggregated Conformal Prediction ( ACP ) carlsson2014aggregated , Combination of inductive mondrian conformal predictors toccaceli2018combination etc .
Cross Conformal Prediction, Aggregated Conformal Prediction
TR-13956
[ "As", "an", "alternative", "to", "DeGroot", "'s", "model", ",", "the", "Bounded", "Confidence", "(", "BC", ")", "model", "introduced", "in", "provides", "agents", "with", "a", "confidence", "measure", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: As an alternative to DeGroot 's model , the Bounded Confidence ( BC ) model introduced in provides agents with a confidence measure .
Bounded Confidence
TR-13957
[ "Furthermore", ",", "the", "sparse", "Bayesian", "learning", "algorithms", "using", "automatic", "relevance", "determination", "(", "ARD", ")", "also", "have", "been", "applied", "for", "different", "applications", ",", "e.g.", "regression", "and", "classification", "DBLP", ":", "journals", "/", "corr", "/", "abs-1301", "-", "3838", ",", "tipping2001sparse", ",", "signal", "denoising", "Zhang2008SignalDA", ",", "neural", "architecture", "search", "zhou2019bayesnas", "and", "pattern", "recognition", "BayesRecognition", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Furthermore , the sparse Bayesian learning algorithms using automatic relevance determination ( ARD ) also have been applied for different applications , e.g. regression and classification DBLP : journals / corr / abs-1301 - 3838 , tipping2001sparse , signal denoising Zhang2008SignalDA , neural architecture search zhou2019bayesnas and pattern recognition BayesRecognition .
automatic relevance determination
TR-13958
[ "In", "the", "unpopulated", "airspace", ",", "the", "flight", "phase", "is", "en", "-", "route", ",", "but", "the", "data", "links", "are", "restricted", "to", "LOS", "A2A", "and", "A2S", "propagation", ",", "owing", "to", "the", "absence", "of", "ground", "stations", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In the unpopulated airspace , the flight phase is en - route , but the data links are restricted to LOS A2A and A2S propagation , owing to the absence of ground stations .
No expansions found
TR-13959
[ "of", "IEEE", "High", "Assurance", "Systems", "Engineering", "Symposium", "(", "HASE", ")", "." ]
[ 4, 1, 0, 2, 2, 2, 4, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: of IEEE High Assurance Systems Engineering Symposium ( HASE ) .
High Assurance Systems Engineering
TR-13960
[ "This", "strategy", "allows", "one", "to", "define", "dynamic", "versions", "of", "various", "indices", ",", "like", "the", "NMI", "and", "the", "VI", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: This strategy allows one to define dynamic versions of various indices , like the NMI and the VI .
No expansions found
TR-13961
[ "For", "example", ",", "replacing", "GI", "with", "FI", ",", "the", "Boolean", "formula", "isomorphism", "problem", ",", "and", "an", "-complete", "property", "on", "GI", "with", "a", "-complete", "property", "on", "FI", "yields", "a", "-complete", "equivalence", "relation", "." ]
[ 4, 4, 4, 4, 1, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: For example , replacing GI with FI , the Boolean formula isomorphism problem , and an -complete property on GI with a -complete property on FI yields a -complete equivalence relation .
No expansions found
TR-13962
[ "This", "combination", "of", "TF", "and", "IDF", "is", "well", "known", "as", "Term", "Frequency", "-", "Inverse", "document", "frequency", "(", "TF", "-", "IDF", ")", "." ]
[ 4, 4, 4, 1, 4, 1, 4, 4, 4, 4, 0, 2, 4, 0, 2, 2, 4, 1, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: This combination of TF and IDF is well known as Term Frequency - Inverse document frequency ( TF - IDF ) .
Term Frequency, Inverse document frequency
TR-13963
[ "In", ",", "the", "question", "is", "encoded", "by", "Gated", "Recurrent", "Unit", "(", "GRU", ")", "similar", "to", "LSTM", "and", "the", "authors", "also", "introduce", "a", "dynamic", "parameter", "layer", "in", "CNN", "whose", "weights", "are", "adaptively", "predicted", "by", "the", "encoded", "question", "feature", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In , the question is encoded by Gated Recurrent Unit ( GRU ) similar to LSTM and the authors also introduce a dynamic parameter layer in CNN whose weights are adaptively predicted by the encoded question feature .
Gated Recurrent Unit
TR-13964
[ "The", "LM", "-", "LSTM", "-", "CRF", "which", "contains", "character", "level", "language", "model", "is", "even", "worse", "(", "shown", "as", "w/", "LM", "in", "table", ",", "with", "different", "character", "level", "hidden", "size", ")", "." ]
[ 4, 1, 4, 1, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The LM - LSTM - CRF which contains character level language model is even worse ( shown as w/ LM in table , with different character level hidden size ) .
No expansions found
TR-13965
[ "After", "iterative", "back", "translation", "(", "BT", ")", "and", "knowledge", "distillation", "(", "KD", ")", ",", "as", "well", "as", "re", "-", "ranking", ",", "our", "system", "achieves", "30.8", "and", "30.9", "BLEU", "points", "on", "newstest2017", "and", "newstest2018", "respectively", "." ]
[ 4, 4, 0, 2, 4, 1, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: After iterative back translation ( BT ) and knowledge distillation ( KD ) , as well as re - ranking , our system achieves 30.8 and 30.9 BLEU points on newstest2017 and newstest2018 respectively .
back translation, knowledge distillation
TR-13966
[ "Besides", ",", "we", "used", "the", "QGroundControl", "ground", "station", ",", "which", "is", "an", "open", "source", "ground", "control", "station", "(", "GCS", ")", "software", "application", "developed", "by", "Lorenz", "Meier", "and", "written", "in", "C++", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Besides , we used the QGroundControl ground station , which is an open source ground control station ( GCS ) software application developed by Lorenz Meier and written in C++ .
ground control station
TR-13967
[ "It", "has", "two", "modes", "of", "communication", ",", "direct", "remote", "memory", "access", "(", "DRMA", ")", "and", "bulk", "synchronous", "message", "passing", "(", "BSMP", ")", "approach", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: It has two modes of communication , direct remote memory access ( DRMA ) and bulk synchronous message passing ( BSMP ) approach .
direct remote memory access, bulk synchronous message passing
TR-13968
[ "Classification", "accuracy", "(", "CA", ")", "was", "used", "as", "the", "performance", "metric", "for", "the", "fire", "identification", "case", ",", "while", "Mean", "Square", "Error", "(", "MSE", ")", "for", "the", "counting", "houses", "scenario", "." ]
[ 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Classification accuracy ( CA ) was used as the performance metric for the fire identification case , while Mean Square Error ( MSE ) for the counting houses scenario .
Classification accuracy, Mean Square Error
TR-13969
[ "Therefore", ",", "after", "the", "collision", "time", ",", "the", "receiving", "STAs", "will", "wait", "for", "an", "Extended", "Inter", "Frame", "Space", "(", "EIFS", ",", "as", "shown", "in", "Equation", "(", ")", ")", "interval", "to", "compete", "for", "the", "channel", "access", "together", "with", "those", "RTS", "-", "sending", "STAs", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Therefore , after the collision time , the receiving STAs will wait for an Extended Inter Frame Space ( EIFS , as shown in Equation ( ) ) interval to compete for the channel access together with those RTS - sending STAs .
Extended Inter Frame Space
TR-13970
[ "One", "of", "them", "is", "proposed", "in", "for", "Subtractive", "Pixel", "Adjacency", "Matrix", "(", "SPAM", ")", "feature", "extraction", "from", "spatial", "domain", "of", "the", "digital", "images", "and", "for", "extracting", "Cartesian", "Calibrated", "features", "extracted", "by", "PEVny", "(", "CC", "-", "PEV", ")", "features", "from", "transforming", "domain", "of", "the", "digital", "images", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 2, 4, 1, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: One of them is proposed in for Subtractive Pixel Adjacency Matrix ( SPAM ) feature extraction from spatial domain of the digital images and for extracting Cartesian Calibrated features extracted by PEVny ( CC - PEV ) features from transforming domain of the digital images .
Subtractive Pixel Adjacency Matrix, Cartesian Calibrated features extracted by PEVny
TR-13971
[ "To", "test", "the", "ability", "of", "generating", "knowledge", "-", "grounded", "responses", ",", "the", "seventh", "Dialog", "System", "Technology", "Challenge", "(", "DSTC7", ")", "proposed", "a", "benchmark", "Reddit", "dataset", ",", "in", "which", "the", "conversations", "are", "accompanied", "with", "a", "link", "to", "an", "external", "webpage", "that", "may", "contain", "related", "facts", "and", "knowledge", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: To test the ability of generating knowledge - grounded responses , the seventh Dialog System Technology Challenge ( DSTC7 ) proposed a benchmark Reddit dataset , in which the conversations are accompanied with a link to an external webpage that may contain related facts and knowledge .
seventh Dialog System Technology Challenge
TR-13972
[ "In", "order", "to", "isolate", "our", "proposed", "scheme", "from", "the", "specific", "implementation", "of", "a", "SI", "mitigation", "technique", ",", "since", "the", "SI", "can", "not", "be", "cancelled", "perfectly", "in", "FD", "systems", "due", "to", "limited", "dynamic", "range", "at", "the", "receiver", "even", "if", "the", "SI", "channel", "is", "known", "perfectly", ",", "we", "model", "the", "residual", "SI", "after", "cancellation", "as", "as", "in", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In order to isolate our proposed scheme from the specific implementation of a SI mitigation technique , since the SI can not be cancelled perfectly in FD systems due to limited dynamic range at the receiver even if the SI channel is known perfectly , we model the residual SI after cancellation as as in .
No expansions found
TR-13973
[ "ACM", "Press", ",", "New", "York", ",", "NY", ",", "USA", "." ]
[ 1, 4, 4, 0, 2, 4, 1, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: ACM Press , New York , NY , USA .
New York
TR-13974
[ "The", "results", "of", "the", "top", "systems", "in", "the", "2017", "ADI", "Shared", "Task", "indicate", "that", "the", "audio", "features", "produce", "a", "much", "better", "performance", ",", "probably", "because", "there", "are", "many", "ASR", "errors", "(", "perhaps", "more", "in", "the", "dialectal", "speech", "segments", ")", "that", "make", "Arabic", "dialect", "identification", "from", "ASR", "transcripts", "much", "more", "difficult", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The results of the top systems in the 2017 ADI Shared Task indicate that the audio features produce a much better performance , probably because there are many ASR errors ( perhaps more in the dialectal speech segments ) that make Arabic dialect identification from ASR transcripts much more difficult .
Arabic dialect identification
TR-13975
[ "The", "system", "calculates", "a", "prediction", "error", "PE", "by", "comparing", "the", "image", "predicted", "by", "the", "forward", "model", "and", "the", "sensory", "observation", "captured", "from", "the", "visual", "input", "after", "the", "execution", "of", "the", "movement", "." ]
[ 4, 4, 4, 4, 0, 2, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The system calculates a prediction error PE by comparing the image predicted by the forward model and the sensory observation captured from the visual input after the execution of the movement .
prediction error
TR-13976
[ "In", "particular", ",", "our", "class", "of", "CSPs", "properly", "contains", "the", "class", "of", "constraint", "satisfaction", "problems", "over", "finite", "domains", "." ]
[ 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 0, 2, 2, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In particular , our class of CSPs properly contains the class of constraint satisfaction problems over finite domains .
constraint satisfaction problems
TR-13977
[ "Since", "in", "CSMA", "/", "ECA", ",", "the", "current", "CW", "is", "derived", "from", "both", "backoff", "stage", "and", ",", "other", "stations", "can", "compute", "the", "future", "transmissions", "of", "the", "transmitting", "station", "(", "in", "terms", "of", "time", "slots", ")", "to", "avoid", "future", "'", "predicted", "'", "collisions", "with", "their", "own", "transmissions", "." ]
[ 4, 4, 1, 4, 1, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Since in CSMA / ECA , the current CW is derived from both backoff stage and , other stations can compute the future transmissions of the transmitting station ( in terms of time slots ) to avoid future ' predicted ' collisions with their own transmissions .
No expansions found
TR-13978
[ "The", "author", "used", "the", "following", "features", ":", "average", "packets", "per", "flow", ",", "average", "bytes", "per", "flow", ",", "number", "of", "flows", "per", "second", ",", "average", "duration", "per", "flow", ",", "entropy", "of", "destination", "IP", "addresses", "per", "second", ",", "entropy", "of", "source", "IP", "address", "per", "second", "and", "entropy", "of", "IP", "protocol", "per", "second", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The author used the following features : average packets per flow , average bytes per flow , number of flows per second , average duration per flow , entropy of destination IP addresses per second , entropy of source IP address per second and entropy of IP protocol per second .
No expansions found
TR-13979
[ "demonstrated", "a", "technique", "for", "allocating", "Virtual", "Machine", "(", "VM", ")", "resources", "based", "on", "CPU", "and", "memory", ",", "albeit", "limited", "." ]
[ 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: demonstrated a technique for allocating Virtual Machine ( VM ) resources based on CPU and memory , albeit limited .
Virtual Machine
TR-13980
[ "(", "last", "column", ")", "illustrates", "the", "nearest", "neighbor", "(", "NN", ")", "test", ",", "where", "is", "the", "training", "dataset", "NN", "of", "a", "few", "images", "." ]
[ 4, 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: ( last column ) illustrates the nearest neighbor ( NN ) test , where is the training dataset NN of a few images .
nearest neighbor
TR-13981
[ "Note", "that", "there", "are", "other", "variants", "of", "gated", "recurrent", "neural", "networks", ",", "such", "as", "Gated", "Recurrent", "Unit", "(", "GRU", ")", "chung2015gated", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Note that there are other variants of gated recurrent neural networks , such as Gated Recurrent Unit ( GRU ) chung2015gated .
Gated Recurrent Unit
TR-13982
[ "For", "signals", "that", "follow", "a", "single", "Gaussian", "model", ",", "with", "Gaussian", "or", "Bernoulli", "sensing", "matrices", "of", "measurements", ",", "considerably", "smaller", "than", "the", "required", "by", "conventional", "CS", "based", "on", "sparse", "models", ",", "where", "is", "the", "signal", "dimension", ",", "and", "with", "an", "optimal", "decoder", "implemented", "via", "linear", "filtering", ",", "significantly", "faster", "than", "the", "pursuit", "decoders", "applied", "in", "conventional", "CS", ",", "the", "error", "of", "SCS", "is", "shown", "tightly", "upper", "bounded", "by", "a", "constant", "times", "the", "best", "-term", "approximation", "error", ",", "with", "overwhelming", "probability", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: For signals that follow a single Gaussian model , with Gaussian or Bernoulli sensing matrices of measurements , considerably smaller than the required by conventional CS based on sparse models , where is the signal dimension , and with an optimal decoder implemented via linear filtering , significantly faster than the pursuit decoders applied in conventional CS , the error of SCS is shown tightly upper bounded by a constant times the best -term approximation error , with overwhelming probability .
No expansions found
TR-13983
[ "Table", "consists", "of", "the", "root", "mean", "squared", "(", "RMS", ")", "statistics", "of", "the", "attitude", "errors", "in", "Euler", "angles", "." ]
[ 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Table consists of the root mean squared ( RMS ) statistics of the attitude errors in Euler angles .
root mean squared
TR-13984
[ "author", "propose", "Universal", "Language", "Model", "Fine", "-", "Tuning", "for", "Text", "Classification", "(", "ULMFiT", ")", "which", "is", "bi", "-", "LSTM", "model", "that", "is", "trained", "on", "a", "general", "language", "modeling", "(", "LM", ")", "task", "and", "then", "fine", "tuned", "on", "text", "classification", "." ]
[ 4, 4, 0, 2, 2, 2, 2, 2, 2, 2, 4, 4, 1, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: author propose Universal Language Model Fine - Tuning for Text Classification ( ULMFiT ) which is bi - LSTM model that is trained on a general language modeling ( LM ) task and then fine tuned on text classification .
Universal Language Model Fine - Tuning for Text, language modeling
TR-13985
[ "Each", "report", "consists", "of", "the", "following", "sections", ":", "impression", ",", "findings", ",", "tags(There", "are", "two", "types", "of", "tags", ":", "manually", "generated", "(", "MeSH", ")", "and", "Medical", "Text", "Indexer", "(", "MTI", ")", "generated", ".", ")", "," ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Each report consists of the following sections : impression , findings , tags(There are two types of tags : manually generated ( MeSH ) and Medical Text Indexer ( MTI ) generated . ) ,
Medical Text Indexer
TR-13986
[ "Motion", "History", "Images", "(", "MHI", ")", "from", "videos", "accumulate", "foreground", "regions", "of", "a", "person", "and", "accounts", "for", "its", "shape", "and", "stance", "." ]
[ 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Motion History Images ( MHI ) from videos accumulate foreground regions of a person and accounts for its shape and stance .
Motion History Images
TR-13987
[ "Specifically", ",", "in", "Fog", "-", "RAN", ",", "each", "radio", "access", "unit", "(", "RAU", ")", "hosts", "storage", "and", "computation", "entities", ",", "thereby", "pushing", "data", "and", "its", "processing", "closer", "to", "end", "users", "." ]
[ 4, 4, 4, 1, 3, 3, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Specifically , in Fog - RAN , each radio access unit ( RAU ) hosts storage and computation entities , thereby pushing data and its processing closer to end users .
radio access unit
TR-13988
[ "Second", ",", "Specify", "VM", "Parameters", "as", "image", "size", ",", "VM", "memory", "(", "MB", ")", ",", "number", "of", "CPUs", "and", "VMM", "name", "." ]
[ 4, 4, 4, 1, 4, 4, 4, 4, 4, 1, 4, 4, 1, 4, 4, 4, 4, 1, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Second , Specify VM Parameters as image size , VM memory ( MB ) , number of CPUs and VMM name .
No expansions found
TR-13989
[ "If", "SR", "adaptation", "is", "enabled", ",", "the", "spatial", "resolution", "of", "the", "decoded", "video", "frames", "is", "firstly", "up", "-", "sampled", "by", "2", "using", "a", "nearest", "neighbour", "filter", "before", "CNN", "reconstruction(It", "is", "noted", "that", ",", "in", "our", "previous", "work", ",", "pre", "-", "CNN", "up", "-", "sampling", "was", "conducted", "using", "a", "Lanczos3", "filter", "." ]
[ 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: If SR adaptation is enabled , the spatial resolution of the decoded video frames is firstly up - sampled by 2 using a nearest neighbour filter before CNN reconstruction(It is noted that , in our previous work , pre - CNN up - sampling was conducted using a Lanczos3 filter .
No expansions found
TR-13990
[ "High", "Resolution", "Dataset", ":", "We", "construct", "the", "HR", "dataset", "by", "combining", "the", "training", "images", "from", "AFLW", "and", "the", "entire", "300W", "dataset", "." ]
[ 0, 2, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: High Resolution Dataset : We construct the HR dataset by combining the training images from AFLW and the entire 300W dataset .
High Resolution
TR-13991
[ "However", ",", "recurrent", "neural", "network", "language", "model", "(", "RNNLM", ")", "suffers", "from", "two", "major", "drawbacks", "when", "used", "to", "generate", "text", "." ]
[ 4, 4, 0, 2, 2, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: However , recurrent neural network language model ( RNNLM ) suffers from two major drawbacks when used to generate text .
recurrent neural network language model
TR-13992
[ "The", "spectral", "library", "is", "constructed", "using", "K", "-", "means", "method", "to", "cluster", "the", "endmembers", "extracted", "by", "vertex", "component", "analysis", "(", "VCA", ")", "from", "a", "collection", "of", "HSIs", "into", "a", "set", "of", "clusters", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: The spectral library is constructed using K - means method to cluster the endmembers extracted by vertex component analysis ( VCA ) from a collection of HSIs into a set of clusters .
vertex component analysis
TR-13993
[ "Three", "-", "dimensional", "within", "-", "IRT", "factorization", "vs", "linear", "factorization", "of", "Right", "Wing", "Authoritarianism", "(", "RWA", ")", "scale", "test", "items", ",", "colored", "by", "discrimination", "weights", "." ]
[ 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Three - dimensional within - IRT factorization vs linear factorization of Right Wing Authoritarianism ( RWA ) scale test items , colored by discrimination weights .
Right Wing Authoritarianism
TR-13994
[ "Recent", "studies", "also", "demonstrated", "the", "chest", "radiography", "'s", "application", "on", "detection", "and", "evaluation", "of", "coronary", "artery", "diseases", ",", "which", "are", "usually", "evaluated", "using", "Computed", "Tomography", "(", "CT", ")", "with", "expensive", "cost", "and", "high", "radiation", "dose", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Recent studies also demonstrated the chest radiography 's application on detection and evaluation of coronary artery diseases , which are usually evaluated using Computed Tomography ( CT ) with expensive cost and high radiation dose .
Computed Tomography
TR-13995
[ "Shared", "dynamic", "link", "libraries", "(", "DLL", ")", "do", "allow", "code", "sharing", "among", "multiple", "applications", "." ]
[ 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Shared dynamic link libraries ( DLL ) do allow code sharing among multiple applications .
dynamic link libraries
TR-13996
[ "For", "example", ",", "what", "does", "the", "Body", "Mass", "Index", "(", "BMI", ")", "look", "like", "for", "people", "with", "a", "height", "of", "?" ]
[ 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: For example , what does the Body Mass Index ( BMI ) look like for people with a height of ?
Body Mass Index
TR-13997
[ "In", "this", "paper", "we", "present", "the", "Hierarchical", "Document", "Topic", "Model", "(", "HDTM", ")", ",", "which", "uses", "a", "distributed", "vertex", "-", "programming", "process", "to", "calculate", "a", "nonparametric", "Bayesian", "generative", "model", "." ]
[ 4, 4, 4, 4, 4, 4, 0, 2, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: In this paper we present the Hierarchical Document Topic Model ( HDTM ) , which uses a distributed vertex - programming process to calculate a nonparametric Bayesian generative model .
Hierarchical Document Topic Model
TR-13998
[ "To", "do", "so", "we", "need", "the", "maximum", "a", "posteriori", "(", "MAP", ")", "estimate", "(", "equal", "to", "the", "mode", "of", "the", "posterior", "distribution", ")", "and", "a", "second", "order", "Taylor", "expansion", "around", "this", "mode", "." ]
[ 4, 4, 4, 4, 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: To do so we need the maximum a posteriori ( MAP ) estimate ( equal to the mode of the posterior distribution ) and a second order Taylor expansion around this mode .
maximum a posteriori
TR-13999
[ "We", "use", "Noise", "Contrastive", "Estimation", "(", "NCE", ")", ",", "which", "allows", "us", "to", "learn", "a", "model", "that", "provably", "converges", "to", "its", "objective", "(", "see", ",", "Theorem", "2", ")", "." ]
[ 4, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We use Noise Contrastive Estimation ( NCE ) , which allows us to learn a model that provably converges to its objective ( see , Theorem 2 ) .
Noise Contrastive Estimation
TR-14000
[ "Typical", "state", "-", "of", "-", "the", "-", "art", "IR", "approaches", "integrate", "a", "speech", "recognition", "(", "SR", ")", "unit", "directly", "with", "the", "QA", "system", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 1, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Typical state - of - the - art IR approaches integrate a speech recognition ( SR ) unit directly with the QA system .
speech recognition
TR-14001
[ "Electronic", "Medical", "Records", "(", "EMR", ")", "are", "used", "in", "medical", "sector", "in", "various", "ways", "which", "includes", "easy", "access", "to", "medical", "record", ",", "reduction", "of", "potential", "medical", "error", ",", "appointments", "and", "billing", "management", "However", ",", "there", "are", "obstacles", "to", "a", "successful", "adoption", "of", "electronic", "records", "and", "to", "the", "transition", "from", "a", "paper", "-", "based", "paradigm", "." ]
[ 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Electronic Medical Records ( EMR ) are used in medical sector in various ways which includes easy access to medical record , reduction of potential medical error , appointments and billing management However , there are obstacles to a successful adoption of electronic records and to the transition from a paper - based paradigm .
Electronic Medical Records
TR-14002
[ "taken", "into", "account", "both", "sparsity", "and", "locality", ",", "and", "upgraded", "the", "robustness", "of", "BB8", "(", "8", "corners", "of", "the", "bounding", "box", ")", "by", "predicting", "projection", "heatmaps", "from", "random", "local", "patches", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 0, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: taken into account both sparsity and locality , and upgraded the robustness of BB8 ( 8 corners of the bounding box ) by predicting projection heatmaps from random local patches .
8 corners of the bounding box
TR-14003
[ "Model", "-", "based", ",", "Reflex", "Agent", "model", "(", "MRA", "model", ")", ":", "A", "world", "model", "is", "introduced", "to", "maintain", "some", "kind", "of", "structure", ",", "which", "describes", "the", "part", "of", "the", "world", "which", "can", "not", "be", "observed", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Model - based , Reflex Agent model ( MRA model ) : A world model is introduced to maintain some kind of structure , which describes the part of the world which can not be observed .
No expansions found
TR-14004
[ "Classification", "performance", "of", "the", "spectral", "detector", "and", "three", "deep", "learning", "(", "DL", ")", "models", "evaluated", "on", "the", "reference", "data", "set", "containing", "200", "quiet", "brakings", ",", "200", "squeals", ",", "50", "wirebrush", "sounds", ",", "25", "click", "sounds", "and", "15", "broad", "-", "banded", "artefacts", "." ]
[ 4, 4, 4, 4, 4, 4, 4, 4, 0, 2, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: Classification performance of the spectral detector and three deep learning ( DL ) models evaluated on the reference data set containing 200 quiet brakings , 200 squeals , 50 wirebrush sounds , 25 click sounds and 15 broad - banded artefacts .
deep learning
TR-14005
[ "We", "also", "compare", "the", "performance", "of", "MRC", "cooperative", "NOMA", "with", "MRC", "cooperative", "orthogonal", "multiple", "access", "(", "OMA", ")", ",", "and", "we", "show", "that", "NOMA", "has", "a", "better", "performance", "than", "OMA", "." ]
[ 4, 4, 4, 4, 4, 4, 1, 4, 1, 4, 1, 4, 0, 2, 2, 4, 1, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 4, 1, 4 ]
list_expansions
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return {{"\"No expansions found\""}} if the expansions can't be found. Tokens: {{tokens|join(' ')}} ||| {% set abbr_string=namespace(value='') %} {% set answer_list=namespace(value=[]) %} {% for label_idx in range(labels|length) %} {% if labels[label_idx] == 0 %} {% set abbr_string.value = tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]==2%} {% set abbr_string.value = abbr_string.value+' '+tokens[label_idx] %} {% elif abbr_string.value!='' and labels[label_idx]!=2%} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% set abbr_string.value = '' %} {% endif %} {% if loop.last and abbr_string.value!='' %} {% set answer_list.value = answer_list.value +[abbr_string.value] %} {% endif %} {% endfor %} {% if answer_list.value|length!=0 %} {{ answer_list.value|join(', ') }} {% else %} No expansions found {% endif %}
List all the expansions (meanings) of the acronyms present in the following space-separated tokens. Return "No expansions found" if the expansions can't be found. Tokens: We also compare the performance of MRC cooperative NOMA with MRC cooperative orthogonal multiple access ( OMA ) , and we show that NOMA has a better performance than OMA .
orthogonal multiple access