id stringlengths 4 8 | tokens listlengths 4 170 | labels listlengths 4 170 | template_name stringclasses 6
values | template stringclasses 6
values | rendered_input stringlengths 74 1.45k | rendered_output stringlengths 0 538 |
|---|---|---|---|---|---|---|
TR-13823 | [
"In",
"the",
"problem",
"of",
"allocating",
"multiple",
"people",
"(",
"either",
"full",
"-",
"time",
"or",
"in",
"smaller",
"time",
"fractions",
")",
"to",
"various",
"groups",
"is",
"called",
"the",
"Multiple",
"Team",
"Formation",
"Problem",
"(",
"MTFP",
... | [
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,
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(label... | 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 problem of allocating multiple people ( either full - time or in smaller time fractions ) to various groups is called the Multiple Team Forma... | Multiple Team Formation Problem |
TR-13824 | [
"We",
"also",
"train",
"a",
"support",
"vector",
"classifier",
"(",
"SVC",
")",
"with",
"an",
"RBF",
"kernel",
"and",
"we",
"implement",
"the",
"model",
"with",
"sklearn",
"."
] | [
4,
4,
4,
4,
0,
2,
2,
4,
1,
4,
4,
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(label... | 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 train a support vector classifier ( SVC ) with an RBF kernel and we implement the model with sklearn . | support vector classifier |
TR-13825 | [
"Averaging",
"the",
"APs",
"over",
"all",
"classes",
"gives",
"the",
"mean",
"average",
"precision",
"."
] | [
4,
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(label... | 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: Averaging the APs over all classes gives the mean average precision . | No expansions found |
TR-13826 | [
"In",
"the",
"following",
"we",
"consider",
"the",
"case",
"of",
"regular",
"-",
"ordered",
"equations",
"with",
"regular",
"constraints",
",",
"when",
"the",
"regular",
"constraints",
"are",
"regular",
"languages",
"that",
"are",
"all",
"accepted",
"by",
"non... | [
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,
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(label... | 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 we consider the case of regular - ordered equations with regular constraints , when the regular constraints are regular languages t... | nondeterministic finite automata |
TR-13827 | [
"It",
"is",
"straightforward",
"to",
"verify",
"that",
"when",
"and",
"are",
"QC",
"channels",
",",
"is",
"also",
"a",
"QC",
"channel",
"for",
"the",
"composite",
"system",
"."
] | [
4,
4,
4,
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(label... | 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 is straightforward to verify that when and are QC channels , is also a QC channel for the composite system . | No expansions found |
TR-13828 | [
"Given",
"the",
"uniform",
"distribution",
"of",
"direction",
"of",
"arrival",
"(",
"DOA",
")",
"measurement",
"errors",
",",
"the",
"authors",
"can",
"significantly",
"improved",
"the",
"bit",
"error",
"rate",
"(",
"BER",
")",
"performance",
"based",
"on",
... | [
4,
4,
4,
4,
4,
0,
2,
2,
4,
1,
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
] | 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(label... | 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: Given the uniform distribution of direction of arrival ( DOA ) measurement errors , the authors can significantly improved the bit error rate ( BER ... | direction of arrival, bit error rate |
TR-13829 | [
"The",
"first",
"of",
"the",
"four",
"layers",
"hosts",
"the",
"Intelligent",
"Element",
"(",
"IE",
")",
"named",
"Controller",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
0,
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(label... | 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 first of the four layers hosts the Intelligent Element ( IE ) named Controller . | Intelligent Element |
TR-13830 | [
"The",
"unlabeled",
"target",
"domain",
"as",
"well",
"as",
"the",
"labeled",
"source",
"domain",
"were",
"used",
"in",
"DAN",
"and",
"SSPP",
"-",
"DAN",
"for",
"unsupervised",
"DA",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
1,
3,
3,
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(label... | 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 unlabeled target domain as well as the labeled source domain were used in DAN and SSPP - DAN for unsupervised DA . | No expansions found |
TR-13831 | [
"Since",
"our",
"objective",
"is",
"to",
"produce",
"a",
"method",
"that",
"can",
"tackle",
"large",
"datasets",
"of",
"experiment",
"results",
",",
"we",
"also",
"propose",
"a",
"mathematical",
"programming",
"heuristic",
"based",
"on",
"Variable",
"Neighborhoo... | [
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,
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(label... | 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 our objective is to produce a method that can tackle large datasets of experiment results , we also propose a mathematical programming heurist... | Variable Neighborhood Descent |
TR-13832 | [
"We",
"used",
"the",
"same",
"hit",
"criterium",
"and",
"competition",
"performance",
"metric",
"(",
"CPM",
")",
"as",
"in",
"the",
"LUNA16",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
0,
2,
2,
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(label... | 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 used the same hit criterium and competition performance metric ( CPM ) as in the LUNA16 . | competition performance metric |
TR-13833 | [
"This",
"depends",
"on",
"many",
"factors",
"such",
"as",
"the",
"users",
"'",
"location",
",",
"number",
"of",
"the",
"users",
"to",
"be",
"served",
",",
"and",
"existence",
"of",
"the",
"TBSs",
"."
] | [
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
] | 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(label... | 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 depends on many factors such as the users ' location , number of the users to be served , and existence of the TBSs . | No expansions found |
TR-13834 | [
"ESA",
"’s",
"Sentinel-2",
"Global",
"Land",
"Cover",
"(",
"S2GLC",
")",
"project",
"selected",
"a",
"pixel",
"-",
"based",
",",
"supervised",
"approach",
"using",
"Random",
"Forests",
"“",
"based",
"on",
"classification",
"accuracy",
",",
"preservation",
"of"... | [
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,
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(label... | 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: ESA ’s Sentinel-2 Global Land Cover ( S2GLC ) project selected a pixel - based , supervised approach using Random Forests “ based on classification ... | Sentinel-2 Global Land Cover |
TR-13835 | [
"Simulations",
"show",
"that",
"the",
"PS",
"estimator",
"has",
"smaller",
"Root",
"Mean",
"Square",
"Error",
"(",
"RMSE",
")",
"compared",
"to",
"the",
"state",
"-",
"of",
"-",
"the",
"-",
"art",
"estimators",
"."
] | [
4,
4,
4,
4,
1,
4,
4,
4,
0,
2,
2,
2,
4,
1,
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(label... | 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: Simulations show that the PS estimator has smaller Root Mean Square Error ( RMSE ) compared to the state - of - the - art estimators . | Root Mean Square Error |
TR-13836 | [
"Effect",
"of",
"ROI",
"versus",
"virtual",
"camera",
",",
"the",
"number",
"of",
"multi",
"-",
"views",
"on",
"CNN",
"inference",
"time",
"for",
"16",
"objects",
",",
"and",
"orientation",
"score",
"(",
"OS",
")",
"when",
"used",
"for",
"training",
"and... | [
4,
4,
1,
4,
4,
4,
4,
4,
4,
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
] | 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(label... | 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: Effect of ROI versus virtual camera , the number of multi - views on CNN inference time for 16 objects , and orientation score ( OS ) when used for ... | orientation score |
TR-13837 | [
"RNNs",
"and",
"their",
"variations",
"such",
"as",
"Long",
"Short",
"-",
"term",
"Memory",
"(",
"LSTM",
")",
",",
"and",
"Gated",
"Recurrent",
"Units",
"(",
"GRU",
")",
"are",
"the",
"most",
"widely",
"used",
"recurrence",
"-",
"based",
"models",
"used"... | [
4,
4,
4,
4,
4,
4,
0,
2,
2,
2,
2,
4,
1,
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(label... | 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: RNNs and their variations such as Long Short - term Memory ( LSTM ) , and Gated Recurrent Units ( GRU ) are the most widely used recurrence - based ... | Long Short - term Memory, Gated Recurrent Units |
TR-13838 | [
"In",
"this",
"paper",
",",
"we",
"present",
"a",
"generative",
"adversarial",
"neural",
"network",
"(",
"GAN",
")",
"that",
"translates",
"multi",
"-",
"view",
"images",
"of",
"objects",
"with",
"specular",
"reflection",
"to",
"diffuse",
"ones",
"."
] | [
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,
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(label... | 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 a generative adversarial neural network ( GAN ) that translates multi - view images of objects with specular reflection t... | generative adversarial neural network |
TR-13839 | [
"Thus",
",",
"due",
"to",
"the",
"central",
"limit",
"theorem",
"(",
"CLT",
")",
"when",
",",
"implying",
"is",
"perfectly",
"accurate",
"."
] | [
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(label... | 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: Thus , due to the central limit theorem ( CLT ) when , implying is perfectly accurate . | central limit theorem |
TR-13840 | [
"To",
"provide",
"explanations",
"for",
"the",
"system",
"’s",
"predictions",
",",
"we",
"analyze",
"the",
"user",
"-",
"specific",
"data",
"along",
"with",
"the",
"20",
"chosen",
"movies",
"using",
"Local",
"Interpretable",
"Model",
"-",
"agnostic",
"Explanat... | [
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,
2,
2,
4,
1,
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(label... | 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 provide explanations for the system ’s predictions , we analyze the user - specific data along with the 20 chosen movies using Local Interpretabl... | Local Interpretable Model - agnostic Explanations |
TR-13841 | [
"The",
"scripts",
"provide",
"a",
"variety",
"of",
"metrics",
";",
"however",
",",
"in",
"accordance",
"with",
"the",
"shared",
"task",
",",
"we",
"report",
"Mean",
"Average",
"Precision",
"(",
"MAP",
")",
"(",
"the",
"official",
"metric",
"for",
"the",
... | [
4,
4,
4,
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,
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... | 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(label... | 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 scripts provide a variety of metrics ; however , in accordance with the shared task , we report Mean Average Precision ( MAP ) ( the official me... | Mean Average Precision, Mean Reciprocal Rank |
TR-13842 | [
"For",
"more",
"information",
"on",
"the",
"Coherent",
"Accelerator",
"Processor",
"Interface",
"on",
"Power8",
"+",
"Processor",
"chip",
"refer",
"to",
"the",
"CAPI",
"user",
"manual",
"CAPI",
"-",
"Manual",
"."
] | [
4,
4,
4,
4,
4,
0,
2,
2,
2,
4,
4,
4,
4,
4,
4,
4,
4,
1,
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(label... | 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 more information on the Coherent Accelerator Processor Interface on Power8 + Processor chip refer to the CAPI user manual CAPI - Manual . | Coherent Accelerator Processor Interface |
TR-13843 | [
"The",
"German",
"Traffic",
"Sign",
"Benchmark",
"Dataset",
"(",
"GTSBD",
")",
"is",
"one",
"of",
"the",
"first",
"datasets",
"that",
"was",
"created",
"to",
"evaluate",
"the",
"classification",
"branch",
"of",
"the",
"problem",
"."
] | [
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
] | 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(label... | 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 German Traffic Sign Benchmark Dataset ( GTSBD ) is one of the first datasets that was created to evaluate the classification branch of the probl... | German Traffic Sign Benchmark Dataset |
TR-13844 | [
"In",
"particular",
",",
"AI",
"(",
"such",
"as",
"machine",
"learning",
")",
"approaches",
"may",
"help",
"to",
"capture",
"the",
"abnormal",
"behaviours",
"in",
"blockchain",
"after",
"analyzing",
"the",
"blockchain",
"data",
",",
"detecting",
"and",
"identi... | [
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
] | 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(label... | 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 , AI ( such as machine learning ) approaches may help to capture the abnormal behaviours in blockchain after analyzing the blockchain ... | No expansions found |
TR-13845 | [
"In",
",",
"the",
"networks",
"are",
"trained",
"using",
"the",
"Contrastive",
"Divergence",
"(",
"CD",
")",
"algorithm",
",",
"which",
"demonstrated",
"the",
"ability",
"of",
"deep",
"networks",
"to",
"capture",
"the",
"distributions",
"over",
"the",
"feature... | [
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
] | 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(label... | 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 networks are trained using the Contrastive Divergence ( CD ) algorithm , which demonstrated the ability of deep networks to capture the dis... | Contrastive Divergence |
TR-13846 | [
"The",
"proposed",
"methodology",
"is",
"coined",
"as",
"Motionless",
"Analysis",
"of",
"Traffic",
"Using",
"Convolutional",
"Neural",
"Networks",
"on",
"SOPC",
":",
"MAT",
"-",
"CNN",
"-",
"SOPC",
"and",
"we",
"have",
"also",
"introduced",
"a",
"Quality",
"... | [
4,
4,
4,
4,
4,
4,
0,
2,
2,
2,
4,
0,
2,
2,
4,
1,
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,
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(label... | 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 proposed methodology is coined as Motionless Analysis of Traffic Using Convolutional Neural Networks on SOPC : MAT - CNN - SOPC and we have also... | Motionless Analysis of Traffic, Convolutional Neural Networks |
TR-13847 | [
"It",
"proposes",
"and",
"implements",
"a",
"generic",
"log",
"processing",
"library",
",",
"called",
"GLoP",
"(",
"GPU",
"Log",
"Processing",
")",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
0,
2,
2,
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(label... | 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 proposes and implements a generic log processing library , called GLoP ( GPU Log Processing ) . | GPU Log Processing |
TR-13848 | [
"CT",
"is",
"a",
"function",
"that",
"given",
"a",
"class",
"table",
"returns",
"the",
"immediate",
"subclass",
"relation",
"of",
"classes",
"in",
"."
] | [
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(label... | 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: CT is a function that given a class table returns the immediate subclass relation of classes in . | No expansions found |
TR-13849 | [
"The",
"proposed",
"framework",
"which",
"is",
"called",
"Collaborative",
"Vehicle",
"Health",
"Management",
"(",
"CVHM",
")",
"is",
"developed",
"to",
"automatically",
"optimize",
"the",
"DP",
"algorithms",
"on",
"a",
"host",
"vehicle",
",",
"using",
"the",
"... | [
4,
4,
4,
4,
4,
4,
0,
2,
2,
2,
4,
1,
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
] | 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(label... | 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 proposed framework which is called Collaborative Vehicle Health Management ( CVHM ) is developed to automatically optimize the DP algorithms on ... | Collaborative Vehicle Health Management |
TR-13850 | [
"Radio",
"frequency",
"(",
"RF",
")",
"EH",
",",
"which",
"is",
"also",
"known",
"as",
"wireless",
"energy",
"transfer",
",",
"has",
"been",
"introduced",
"as",
"an",
"effective",
"harvesting",
"technique",
"where",
"energy",
"is",
"collected",
"from",
"RF",... | [
0,
2,
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,
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(label... | 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: Radio frequency ( RF ) EH , which is also known as wireless energy transfer , has been introduced as an effective harvesting technique where energy ... | Radio frequency |
TR-13851 | [
"In",
"particular",
",",
"we",
"note",
"some",
"potential",
"differences",
"that",
"may",
"have",
"been",
"introduced",
"between",
"YLI",
"-",
"MED",
"and",
"the",
"Heterogenous",
"Audio",
"Visual",
"Internet",
"Collection",
"(",
"HAVIC",
")",
"(",
"HAVIC",
... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
1,
4,
4,
0,
2,
2,
2,
2,
4,
1,
4,
4,
1,
4,
4,
4,
1,
4,
1,
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
] | 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(label... | 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 , we note some potential differences that may have been introduced between YLI - MED and the Heterogenous Audio Visual Internet Collec... | Heterogenous Audio Visual Internet Collection |
TR-13852 | [
"For",
"an",
"experimental",
"comparison",
",",
"we",
"implemented",
"our",
"two",
"incremental",
"approaches",
"IA",
"and",
"IAW",
",",
"as",
"well",
"as",
"the",
"static",
"approximation",
"RK",
",",
"the",
"static",
"exact",
"BA",
",",
"the",
"dynamic",
... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
1,
4,
4,
4,
4,
4,
4,
4,
1,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
1,
4,
1,
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(label... | 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 an experimental comparison , we implemented our two incremental approaches IA and IAW , as well as the static approximation RK , the static exac... | No expansions found |
TR-13853 | [
"Truncated",
"Singular",
"Value",
"Decomposition",
"(",
"SVD",
")",
"is",
"a",
"dimensionality",
"reduction",
"technique",
"applied",
"to",
"the",
"bag",
"of",
"words",
"representation",
"."
] | [
4,
0,
2,
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(label... | 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: Truncated Singular Value Decomposition ( SVD ) is a dimensionality reduction technique applied to the bag of words representation . | Singular Value Decomposition |
TR-13854 | [
"Discrete",
"Fourier",
"transform",
"(",
"DFT",
")",
"which",
"maps",
"images",
"into",
"frequency",
"domain",
"is",
"a",
"good",
"tool",
"to",
"achieve",
"those",
"goals",
"."
] | [
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(label... | 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: Discrete Fourier transform ( DFT ) which maps images into frequency domain is a good tool to achieve those goals . | Discrete Fourier transform |
TR-13855 | [
"In",
"this",
"paper",
",",
"we",
"experiment",
"with",
"the",
"best",
"low",
"-",
"dimensional",
"embedding",
"technique",
"known",
"as",
"t",
"-",
"SNE",
"(",
"Student",
"-",
"t",
"distribution",
"-",
"Stochastic",
"Neighborhood",
"Embedding",
")",
"for",
... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
0,
2,
2,
2,
2,
2,
2,
2,
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(label... | 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 experiment with the best low - dimensional embedding technique known as t - SNE ( Student - t distribution - Stochastic Neighborh... | Student - t distribution - Stochastic Neighborhood Embedding |
TR-13856 | [
"Mimblewimble",
"is",
"an",
"optimization",
"to",
"CT",
"that",
"can",
"make",
"the",
"size",
"of",
"the",
"ledger",
"even",
"smaller",
",",
"by",
"aggregating",
"and",
"compressing",
"transactions",
"in",
"such",
"a",
"way",
"that",
"avoids",
"the",
"necess... | [
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
] | 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(label... | 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: Mimblewimble is an optimization to CT that can make the size of the ledger even smaller , by aggregating and compressing transactions in such a way ... | No expansions found |
TR-13857 | [
"Thanks",
"to",
"the",
"distributed",
"maximum",
"ratio",
"combining",
"(",
"MRC",
")",
"weighting",
"at",
"the",
"APs",
",",
"we",
"propose",
"that",
"only",
"the",
"quantized",
"version",
"of",
"the",
"weighted",
"signals",
"are",
"sent",
"back",
"to",
"... | [
4,
4,
4,
4,
0,
2,
2,
4,
1,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
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(label... | 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: Thanks to the distributed maximum ratio combining ( MRC ) weighting at the APs , we propose that only the quantized version of the weighted signals ... | maximum ratio combining |
TR-13858 | [
"In",
"addition",
",",
"proposed",
"protection",
"mechanisms",
"with",
"double",
"-",
"base",
"chains",
"method",
"against",
"SCA",
"attack",
"(",
"SPA",
"and",
"DPA",
")",
",",
"using",
"side",
"channel",
"atomicity",
"against",
"SPA",
"and",
"randomization",... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
4,
1,
4,
4,
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(label... | 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 , proposed protection mechanisms with double - base chains method against SCA attack ( SPA and DPA ) , using side channel atomicity agai... | No expansions found |
TR-13859 | [
"The",
"separable",
"mask",
"(",
"mask",
"2",
")",
"based",
"on",
"maximum",
"length",
"sequence",
"(",
"MLS",
")",
"have",
"much",
"stronger",
"frequency",
"response",
"along",
"the",
"horizontal",
"and",
"vertical",
"axes",
"."
] | [
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
] | 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(label... | 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 separable mask ( mask 2 ) based on maximum length sequence ( MLS ) have much stronger frequency response along the horizontal and vertical axes ... | maximum length sequence |
TR-13860 | [
"al",
"proposed",
"a",
"new",
"convolutional",
"neural",
"network",
"(",
"CNN",
")",
"architecture",
"called",
"SRNet",
"for",
"steganalysis",
"."
] | [
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(label... | 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: al proposed a new convolutional neural network ( CNN ) architecture called SRNet for steganalysis . | convolutional neural network |
TR-13861 | [
"As",
"the",
"goal",
"is",
"to",
"stay",
"below",
"a",
"target",
"reconfiguration",
"rate",
"while",
"minimizing",
"the",
"routing",
"cost",
",",
"we",
"compared",
"the",
"performance",
"of",
"our",
"policy",
"against",
"a",
"Periodic",
"Policy",
"(",
"PP",
... | [
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,
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(label... | 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 the goal is to stay below a target reconfiguration rate while minimizing the routing cost , we compared the performance of our policy against a P... | Periodic Policy |
TR-13862 | [
"We",
"successfully",
"implemented",
"conditioning",
"on",
"a",
"very",
"modern",
"GAN",
"architecture",
"(",
"and",
"will",
"continue",
"to",
"improve",
"our",
"model",
"and",
"update",
"the",
"website",
"linked",
"above",
")",
",",
"but",
"more",
"importantl... | [
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,
4,
4,
0,
2,
2,
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(label... | 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 successfully implemented conditioning on a very modern GAN architecture ( and will continue to improve our model and update the website linked ab... | Generative Adversarial Networks |
TR-13863 | [
"The",
"normalized",
"mean",
"square",
"error",
"(",
"MSE",
")",
"for",
"is",
"(",
"and",
"similarly",
"for",
")",
"."
] | [
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(label... | 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 normalized mean square error ( MSE ) for is ( and similarly for ) . | mean square error |
TR-13864 | [
"DELF",
"features",
"are",
"extracted",
"using",
"Multiplicative",
"Attention",
"(",
"MA",
")",
"and",
"Additive",
"Attention",
"(",
"AA",
")",
"."
] | [
1,
4,
4,
4,
4,
0,
2,
4,
1,
4,
4,
0,
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(label... | 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: DELF features are extracted using Multiplicative Attention ( MA ) and Additive Attention ( AA ) . | Multiplicative Attention, Additive Attention |
TR-13865 | [
"Having",
"a",
"honeypot",
"tool",
"targeted",
"to",
"UPnP",
"device",
"class",
"will",
"help",
"researchers",
"to",
"deploy",
"the",
"same",
"tool",
"for",
"a",
"large",
"variants",
"of",
"devices",
"and",
"vendors",
"to",
"fight",
"against",
"vulnerabilities... | [
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,
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(label... | 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: Having a honeypot tool targeted to UPnP device class will help researchers to deploy the same tool for a large variants of devices and vendors to fi... | No expansions found |
TR-13866 | [
"Under",
"the",
"output",
"-",
"friendly",
"coordinate",
"frame",
"the",
"solvability",
"of",
"disturbance",
"decoupling",
"problem",
"(",
"DDP",
")",
"was",
"converted",
"to",
"solving",
"a",
"set",
"of",
"algebraic",
"equations",
",",
"by",
"putting",
"the",... | [
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,
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(label... | 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: Under the output - friendly coordinate frame the solvability of disturbance decoupling problem ( DDP ) was converted to solving a set of algebraic e... | disturbance decoupling problem |
TR-13867 | [
"Secondly",
",",
"we",
"propose",
"Human",
"Pose",
"Models",
"(",
"HPM",
")",
"that",
"are",
"Convolutional",
"Neural",
"Networks",
"and",
"transfer",
"human",
"poses",
"to",
"a",
"shared",
"high",
"level",
"invariant",
"space",
"."
] | [
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
] | 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(label... | 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: Secondly , we propose Human Pose Models ( HPM ) that are Convolutional Neural Networks and transfer human poses to a shared high level invariant spa... | Human Pose Models |
TR-13868 | [
"Scenario",
"4",
":",
"No",
"Retirements",
"beyond",
"Forward",
"Capacity",
"Auctions",
"(",
"FCA",
")",
"10In",
"contrast",
"to",
"other",
"scenarios",
",",
"no",
"generation",
"units",
"are",
"retired",
"beyond",
"the",
"known",
"FCA",
"resources",
"."
] | [
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
] | 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(label... | 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: Scenario 4 : No Retirements beyond Forward Capacity Auctions ( FCA ) 10In contrast to other scenarios , no generation units are retired beyond the k... | Forward Capacity Auctions |
TR-13869 | [
"However",
",",
"it",
"is",
"desirable",
"to",
"circumvent",
"the",
"requirement",
"of",
"an",
"additional",
"CT",
"acquisition",
"not",
"just",
"to",
"reduce",
"the",
"exposed",
"radiation",
"dose",
"to",
"the",
"patient",
"but",
"also",
"to",
"avoid",
"the... | [
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,
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(label... | 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 , it is desirable to circumvent the requirement of an additional CT acquisition not just to reduce the exposed radiation dose to the patient... | No expansions found |
TR-13870 | [
"Existing",
"end",
"-",
"to",
"-",
"end",
"ML",
"frameworks",
"like",
"TFX",
",",
"KeystoneML",
",",
"or",
"Alpine",
"Meadow",
"are",
"built",
"on",
"top",
"of",
"ML",
"libraries",
",",
"which",
"allows",
"reusing",
"these",
"evolving",
"systems",
",",
"... | [
4,
4,
4,
4,
4,
4,
1,
4,
4,
1,
4,
1,
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
] | 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(label... | 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: Existing end - to - end ML frameworks like TFX , KeystoneML , or Alpine Meadow are built on top of ML libraries , which allows reusing these evolvin... | No expansions found |
TR-13871 | [
"DS",
"(",
"Direct",
"sharing",
")",
",",
"B64S",
"(",
"Base64",
"sharing",
")",
",",
"ES",
"(",
"Encrypted",
"sharing",
")",
",",
"PCS",
"(",
"ID",
"as",
"part",
"of",
"the",
"cookie",
")",
",",
"PPS",
"(",
"ID",
"sent",
"as",
"part",
"of",
"the... | [
1,
4,
0,
2,
4,
4,
1,
4,
0,
2,
4,
4,
1,
4,
0,
2,
4,
4,
1,
4,
0,
2,
2,
2,
2,
2,
4,
4,
1,
4,
0,
2,
2,
2,
2,
2,
2,
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(label... | 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: DS ( Direct sharing ) , B64S ( Base64 sharing ) , ES ( Encrypted sharing ) , PCS ( ID as part of the cookie ) , PPS ( ID sent as part of the paramet... | Direct sharing, Base64 sharing, Encrypted sharing, ID as part of the cookie, ID sent as part of the parameter |
TR-13872 | [
"For",
"example",
",",
"D13",
"-",
"1170",
"introduced",
"Recursive",
"Neural",
"Tensor",
"Network",
"(",
"RNTN",
")",
"over",
"parse",
"trees",
"to",
"compute",
"sentence",
"embedding",
"for",
"sentiment",
"analysis",
"."
] | [
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
] | 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(label... | 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 , D13 - 1170 introduced Recursive Neural Tensor Network ( RNTN ) over parse trees to compute sentence embedding for sentiment analysis . | Recursive Neural Tensor Network |
TR-13873 | [
"Among",
"the",
"conventional",
"supervised",
"approaches",
",",
"SVM",
"and",
"Naive",
"Bayes",
"(",
"NB",
")",
"achieved",
"better",
"performances",
"in",
"terms",
"of",
"F1-Score",
"across",
"all",
"three",
"hospitals",
"."
] | [
4,
4,
4,
4,
4,
4,
1,
4,
0,
2,
4,
1,
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(label... | 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: Among the conventional supervised approaches , SVM and Naive Bayes ( NB ) achieved better performances in terms of F1-Score across all three hospita... | Naive Bayes |
TR-13874 | [
"The",
"proposed",
"methodology",
"should",
"be",
"assessed",
"for",
"different",
"modalities",
",",
"e.g.",
"positron",
"emission",
"tomography",
"(",
"PET",
")",
"and",
"magnetic",
"resonance",
"imaging",
"(",
"MRI",
")",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
2,
4,
1,
4,
4,
0,
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(label... | 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 proposed methodology should be assessed for different modalities , e.g. positron emission tomography ( PET ) and magnetic resonance imaging ( MR... | positron emission tomography, magnetic resonance imaging |
TR-13875 | [
"We",
"use",
"Normalized",
"Mutual",
"Information",
"(",
"NMI",
")",
"as",
"a",
"similarity",
"value",
",",
"a",
"common",
"measure",
"for",
"comparing",
"partitions",
"of",
"graphs",
"."
] | [
4,
4,
0,
2,
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(label... | 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 Normalized Mutual Information ( NMI ) as a similarity value , a common measure for comparing partitions of graphs . | Normalized Mutual Information |
TR-13876 | [
"In",
"Proceedings",
"of",
"the",
"5th",
"IBM",
"Collaborative",
"Academia",
"Research",
"Exchange",
"Workshop",
",",
"I",
"-",
"CARE",
"'",
"13",
",",
"pages",
"13:1",
"-",
"13:4",
"."
] | [
4,
4,
4,
4,
4,
1,
0,
2,
2,
2,
4,
4,
4,
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(label... | 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 Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop , I - CARE ' 13 , pages 13:1 - 13:4 . | Collaborative Academia Research Exchange |
TR-13877 | [
"The",
"third",
"dataset",
"is",
"the",
"Dog",
"Breed",
"Identification",
"(",
"DBI",
")",
"playground",
"competition",
"from",
"Kaggle",
"."
] | [
4,
4,
4,
4,
4,
0,
2,
2,
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(label... | 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 third dataset is the Dog Breed Identification ( DBI ) playground competition from Kaggle . | Dog Breed Identification |
TR-13878 | [
"Bui",
"et",
"al",
"proposed",
"a",
"hybrid",
"feature",
"selection",
"for",
"land",
"pattern",
"classification",
",",
"using",
"Whale",
"Optimization",
"Algorithm",
"(",
"WOA",
")",
"and",
"adaptive",
"neuro",
"-",
"fuzzy",
"inference",
"concepts",
"."
] | [
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
] | 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(label... | 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: Bui et al proposed a hybrid feature selection for land pattern classification , using Whale Optimization Algorithm ( WOA ) and adaptive neuro - fuzz... | Whale Optimization Algorithm |
TR-13879 | [
"RA",
"will",
"stop",
"all",
"pending",
"pre",
"-",
"generation",
"jobs",
"with",
"the",
"previous",
"PCA",
"certificate",
"and",
"delete",
"all",
"pre",
"-",
"generated",
"certificates",
"as",
"soon",
"as",
"it",
"receives",
"the",
"updated",
"CRL",
"."
] | [
1,
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,
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(label... | 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: RA will stop all pending pre - generation jobs with the previous PCA certificate and delete all pre - generated certificates as soon as it receives ... | No expansions found |
TR-13880 | [
"The",
"proposed",
"method",
"differs",
"from",
"the",
"previous",
"studies",
"in",
"two",
"facets",
":",
"First",
",",
"utilizing",
"the",
"dependency",
"relationships",
"between",
"the",
"protein",
"names",
",",
"we",
"generate",
"the",
"Shortest",
"Dependency... | [
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,
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(label... | 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 proposed method differs from the previous studies in two facets : First , utilizing the dependency relationships between the protein names , we ... | Shortest Dependency Path |
TR-13881 | [
"On",
"the",
"other",
"hand",
",",
"Ensemble",
"Diffusion",
"(",
"ED",
")",
"requires",
"to",
"perform",
"a",
"similarity",
"diffusion",
"."
] | [
4,
4,
4,
4,
4,
0,
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(label... | 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 the other hand , Ensemble Diffusion ( ED ) requires to perform a similarity diffusion . | Ensemble Diffusion |
TR-13882 | [
"Incidentally",
",",
"these",
"typically",
"are",
"the",
"scenarios",
"where",
"TTS",
"systems",
"are",
"widely",
"deployed",
"as",
"speech",
"interfaces",
"and",
"therefore",
"these",
"systems",
"should",
"be",
"able",
"to",
"handle",
"such",
"input",
"."
] | [
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
] | 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(label... | 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: Incidentally , these typically are the scenarios where TTS systems are widely deployed as speech interfaces and therefore these systems should be ab... | No expansions found |
TR-13883 | [
"The",
"NN",
"and",
"NN",
"networks",
"are",
"trained",
"with",
"only",
"in",
"-",
"campaign",
"data",
"sets",
",",
"e.g.",
",",
"NN",
"with",
"the",
"data",
"sets",
"from",
"only",
"2018",
"campaign",
",",
"and",
"we",
"find",
"slightly",
"worse",
"re... | [
4,
1,
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,
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(label... | 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 NN and NN networks are trained with only in - campaign data sets , e.g. , NN with the data sets from only 2018 campaign , and we find slightly w... | No expansions found |
TR-13884 | [
"In",
"5",
"G",
"software",
"defined",
"vehicular",
"networks",
",",
"BSs",
"transmit",
"wireless",
"signals",
"by",
"traditional",
"long",
"term",
"evolution",
"(",
"LTE",
")",
"frequency",
"and",
"provide",
"a",
"large",
"coverage",
"for",
"vehicles",
"."
] | [
4,
4,
4,
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(label... | 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 5 G software defined vehicular networks , BSs transmit wireless signals by traditional long term evolution ( LTE ) frequency and provide a large ... | long term evolution |
TR-13885 | [
"We",
"have",
"then",
"presented",
"a",
"specific",
"spiking",
"neural",
"network",
"model",
",",
"the",
"Random",
"Neural",
"Network",
"(",
"RNN",
")",
"that",
"was",
"first",
"introduced",
"in",
"."
] | [
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(label... | 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 have then presented a specific spiking neural network model , the Random Neural Network ( RNN ) that was first introduced in . | Random Neural Network |
TR-13886 | [
"This",
"paper",
"carries",
"out",
"a",
"large",
"dimensional",
"analysis",
"of",
"a",
"variation",
"of",
"kernel",
"ridge",
"regression",
"that",
"we",
"call",
"centered",
"kernel",
"ridge",
"regression",
"(",
"CKRR",
")",
",",
"also",
"known",
"in",
"the",... | [
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,
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(label... | 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 paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call centered kernel ridge regression ( CKRR )... | centered kernel ridge regression |
TR-13887 | [
"The",
"problem",
"is",
"that",
"after",
"getting",
"the",
"result",
"as",
"a",
"MIDI",
"file",
",",
"the",
"user",
"still",
"has",
"to",
"put",
"it",
"into",
"a",
"digital",
"audio",
"workstation",
"(",
"DAW",
")",
"to",
"synthesize",
"the",
"audio",
... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
2,
4,
1,
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(label... | 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 problem is that after getting the result as a MIDI file , the user still has to put it into a digital audio workstation ( DAW ) to synthesize th... | digital audio workstation |
TR-13888 | [
"Specially",
"designed",
"sequential",
"convex",
"programming",
"(",
"SCP",
")",
"routines",
"exist",
"for",
"solving",
"optimization",
"problems",
"with",
"DC",
"structure",
"."
] | [
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(label... | 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: Specially designed sequential convex programming ( SCP ) routines exist for solving optimization problems with DC structure . | sequential convex programming |
TR-13889 | [
"We",
"can",
"contrast",
"these",
"students",
"with",
"the",
"students",
"that",
"are",
"highly",
"committed",
"to",
"the",
"CS",
"major",
"and",
"its",
"core",
"classes",
"starting",
"freshman",
"year",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
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(label... | 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 can contrast these students with the students that are highly committed to the CS major and its core classes starting freshman year . | No expansions found |
TR-13890 | [
"The",
"MTE",
"metrics",
"with",
"a",
"high",
"correlation",
"with",
"human",
"evaluation",
"enable",
"the",
"continuous",
"integration",
"and",
"deployment",
"of",
"a",
"machine",
"translation",
"(",
"MT",
")",
"system",
"."
] | [
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
] | 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(label... | 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 MTE metrics with a high correlation with human evaluation enable the continuous integration and deployment of a machine translation ( MT ) syste... | machine translation |
TR-13891 | [
"He",
"is",
"currently",
"an",
"Assistant",
"Professor",
"of",
"Computer",
"Science",
"in",
"the",
"San",
"Diego",
"State",
"University",
"(",
"SDSU",
")",
",",
"San",
"Diego",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
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(label... | 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: He is currently an Assistant Professor of Computer Science in the San Diego State University ( SDSU ) , San Diego . | San Diego State University |
TR-13892 | [
"Authors",
"in",
"proposed",
"a",
"new",
"interpretation",
"of",
"the",
"I",
"/",
"O",
"transitions",
",",
"based",
"on",
"which",
"a",
"controller",
"that",
"enforced",
"determinism",
"and",
"non",
"-",
"blockingness",
"of",
"the",
"closed",
"-",
"loop",
... | [
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(label... | 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: Authors in proposed a new interpretation of the I / O transitions , based on which a controller that enforced determinism and non - blockingness of ... | No expansions found |
TR-13893 | [
"For",
"instance",
",",
"consider",
"a",
"simple",
"but",
"pathological",
"case",
"of",
"the",
"SI",
"model",
"where",
"there",
"are",
"only",
"two",
"nodes",
"in",
"the",
"graph",
",",
"and",
",",
"with",
"an",
"edge",
"between",
"them",
"as",
"shown",
... | [
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(label... | 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 instance , consider a simple but pathological case of the SI model where there are only two nodes in the graph , and , with an edge between them... | No expansions found |
TR-13894 | [
"In",
"the",
"multi",
"-",
"user",
"scheme",
"proposed",
"in",
"jornet2012phlame",
",",
"referred",
"to",
"as",
"Rate",
"Division",
"Multiple",
"Access",
"(",
"RDMA",
")",
",",
"users",
"are",
"assigned",
"co",
"-",
"prime",
"transmission",
"rates",
"during"... | [
4,
4,
4,
4,
4,
4,
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,
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(label... | 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 multi - user scheme proposed in jornet2012phlame , referred to as Rate Division Multiple Access ( RDMA ) , users are assigned co - prime tran... | Rate Division Multiple Access |
TR-13895 | [
"We",
"propose",
"a",
"significance",
"-",
"aware",
"information",
"bottlenecked",
"adversarial",
"network",
"(",
"SIBAN",
")",
"for",
"feature",
"-",
"space",
"domain",
"adaptive",
"semantic",
"segmentation",
",",
"which",
"combines",
"the",
"advantages",
"from",... | [
4,
4,
4,
0,
2,
2,
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
] | 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(label... | 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 propose a significance - aware information bottlenecked adversarial network ( SIBAN ) for feature - space domain adaptive semantic segmentation ,... | significance - aware information bottlenecked adversarial network |
TR-13896 | [
"In",
"this",
"paper",
"we",
"propose",
"methods",
"to",
"enhance",
"the",
"robustness",
"of",
"MT",
"systems",
"by",
"emulating",
"naturally",
"occurring",
"noise",
"in",
"otherwise",
"clean",
"data",
"."
] | [
4,
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(label... | 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 propose methods to enhance the robustness of MT systems by emulating naturally occurring noise in otherwise clean data . | No expansions found |
TR-13897 | [
"In",
"ref",
",",
"for",
"each",
"mass",
",",
"eight",
"shape",
"parameters",
"and",
"ten",
"enhancement",
"texture",
"features",
"were",
"calculated",
"and",
"then",
"an",
"Artificial",
"Neural",
"Network",
"(",
"ANN",
")",
"was",
"used",
"to",
"build",
"... | [
4,
4,
4,
4,
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
] | 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(label... | 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 ref , for each mass , eight shape parameters and ten enhancement texture features were calculated and then an Artificial Neural Network ( ANN ) w... | Artificial Neural Network |
TR-13898 | [
"The",
"most",
"common",
"form",
"of",
"sleep",
"apnoea",
"Obstructive",
"Sleep",
"Apnoea",
"(",
"OSA",
")",
"is",
"caused",
"by",
"either",
"the",
"partial",
"or",
"complete",
"blockage",
"of",
"the",
"upper",
"airway",
"and",
"can",
"be",
"effectively",
... | [
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,
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(label... | 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 most common form of sleep apnoea Obstructive Sleep Apnoea ( OSA ) is caused by either the partial or complete blockage of the upper airway and c... | Obstructive Sleep Apnoea |
TR-13899 | [
"In",
"contrast",
",",
"Bayesian",
"approaches",
"such",
"as",
"Markov",
"Chain",
"Monte",
"Carlo",
"(",
"MCMC",
")",
"techniques",
"do",
"capture",
"uncertainty",
"estimates",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
0,
2,
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(label... | 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 contrast , Bayesian approaches such as Markov Chain Monte Carlo ( MCMC ) techniques do capture uncertainty estimates . | Markov Chain Monte Carlo |
TR-13900 | [
"Built",
"on",
"the",
"causal",
"relationships",
"of",
"raw",
"material",
"quality",
"attributes",
",",
"production",
"process",
",",
"and",
"bio",
"-",
"drug",
"properties",
"in",
"safety",
"and",
"efficacy",
",",
"we",
"develop",
"a",
"Bayesian",
"Network",
... | [
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,
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(label... | 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: Built on the causal relationships of raw material quality attributes , production process , and bio - drug properties in safety and efficacy , we de... | Bayesian Network |
TR-13901 | [
"Associated",
"with",
"each",
"sample",
"we",
"have",
"a",
"label",
",",
"which",
"could",
"be",
"either",
"normal",
",",
"Mild",
"Cognitive",
"Impairment",
"(",
"MCI",
")",
"or",
"demented",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
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(label... | 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: Associated with each sample we have a label , which could be either normal , Mild Cognitive Impairment ( MCI ) or demented . | Mild Cognitive Impairment |
TR-13902 | [
"In",
"this",
"paper",
",",
"two",
"novel",
"M2",
"M",
"relay",
"selection",
"algorithms",
"are",
"proposed",
",",
"named",
"as",
"Optimal",
"Relay",
"Selection",
"Algorithm",
"(",
"ORSA",
")",
"and",
"Matching",
"based",
"Relay",
"Selection",
"Algorithm",
"... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
2,
2,
4,
1,
4,
4,
0,
2,
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(label... | 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 , two novel M2 M relay selection algorithms are proposed , named as Optimal Relay Selection Algorithm ( ORSA ) and Matching based Rela... | Optimal Relay Selection Algorithm, Matching based Relay Selection Algorithm |
TR-13903 | [
"Conventional",
"time",
"-",
"domain",
"approaches",
"perform",
"coherent",
"detection",
"in",
"combination",
"with",
"digital",
"signal",
"processing",
"(",
"DSP",
")",
"to",
"cope",
"with",
"this",
"issue",
",",
"but",
"as",
"higher",
"order",
"modulation",
... | [
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,
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(label... | 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: Conventional time - domain approaches perform coherent detection in combination with digital signal processing ( DSP ) to cope with this issue , but... | digital signal processing |
TR-13904 | [
"In",
"Section",
",",
"the",
"utility",
"of",
"the",
"finite",
"block",
"length",
"achievability",
"bound",
"is",
"demonstrated",
"for",
"the",
"well",
"known",
"binary",
"symmetric",
"channel",
"(",
"BSC",
")",
"and",
"AWGN",
"channel",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
2,
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(label... | 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 Section , the utility of the finite block length achievability bound is demonstrated for the well known binary symmetric channel ( BSC ) and AWGN... | binary symmetric channel |
TR-13905 | [
"Fortunately",
",",
"many",
"reasonable",
"approximations",
"exist",
"for",
"general",
"graphs",
":",
"in",
"this",
"paper",
"we",
"employ",
"the",
"commonly",
"used",
"maximum",
"cardinality",
"search",
"(",
"MCS",
")",
"heuristic",
"introduced",
"by",
"Tarjan"... | [
4,
4,
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,
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(label... | 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: Fortunately , many reasonable approximations exist for general graphs : in this paper we employ the commonly used maximum cardinality search ( MCS )... | maximum cardinality search |
TR-13906 | [
"Next",
",",
"the",
"last",
"few",
"years",
"have",
"seen",
"the",
"development",
"of",
"more",
"comprehensive",
"models",
"of",
"gene",
"family",
"evolution",
",",
"accounting",
"for",
"example",
"for",
"genes",
"appearing",
"at",
"a",
"given",
"species",
"... | [
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,
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... | 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(label... | 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: Next , the last few years have seen the development of more comprehensive models of gene family evolution , accounting for example for genes appeari... | incomplete lineage sorting |
TR-13907 | [
"(",
"a",
")",
"NQG",
"+",
"NER",
":",
"NQG",
"with",
"the",
"coarse",
"-",
"grained",
"named",
"entity",
"recognition(We",
"use",
"the",
"Stanford",
"NER",
"to",
"tag",
"the",
"entity",
")",
"feature",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
0,
2,
2,
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(label... | 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 ) NQG + NER : NQG with the coarse - grained named entity recognition(We use the Stanford NER to tag the entity ) feature . | named entity recognition(We |
TR-13908 | [
"jangid2018handwritten",
"developed",
"a",
"deep",
"convolutional",
"neural",
"network",
"(",
"DCNN",
")",
"and",
"adaptive",
"gradient",
"methods",
"to",
"identify",
"handwritten",
"Devanagari",
"characters",
"."
] | [
4,
4,
4,
0,
2,
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(label... | 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: jangid2018handwritten developed a deep convolutional neural network ( DCNN ) and adaptive gradient methods to identify handwritten Devanagari charac... | deep convolutional neural network |
TR-13909 | [
"First",
"of",
"all",
",",
"we",
"train",
"a",
"convolutional",
"neural",
"network",
"(",
"CNN",
")",
"on",
"a",
"large",
"stereo",
"set",
",",
"and",
"compute",
"the",
"matching",
"confidence",
"of",
"each",
"pixel",
"by",
"using",
"the",
"trained",
"CN... | [
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,
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(label... | 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: First of all , we train a convolutional neural network ( CNN ) on a large stereo set , and compute the matching confidence of each pixel by using th... | convolutional neural network |
TR-13910 | [
"In",
"the",
"second",
"form",
",",
"it",
"is",
"most",
"probable",
"that",
"the",
"change",
"to",
"g-",
"in",
"MP",
"gul",
"was",
"triggered",
"by",
"the",
"following",
"*",
"-r-",
",",
"which",
"subsequently",
"underwent",
"lateralization",
"(",
"e.g.",
... | [
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,
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(label... | 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 second form , it is most probable that the change to g- in MP gul was triggered by the following * -r- , which subsequently underwent lateral... | No expansions found |
TR-13911 | [
"This",
"material",
"is",
"based",
"in",
"part",
"on",
"research",
"sponsored",
"by",
"the",
"NSF",
"under",
"grants",
"IIS-1822754",
"and",
"IIS-1755898",
",",
"DARPA",
"through",
"the",
"ARO",
"under",
"agreement",
"number",
"W911NF-17-C-0095",
",",
"through",... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
4,
1,
4,
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
] | 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(label... | 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 material is based in part on research sponsored by the NSF under grants IIS-1822754 and IIS-1755898 , DARPA through the ARO under agreement num... | No expansions found |
TR-13912 | [
"Before",
"we",
"perform",
"classification",
",",
"we",
"need",
"to",
"pass",
"through",
"two",
"preliminary",
"steps",
"namely",
",",
"Image",
"Preprocessing",
"(",
"IP",
")",
"and",
"Feature",
"Extraction",
"(",
"FE",
")",
"as",
"shown",
"in",
"Figure",
... | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
4,
1,
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(label... | 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: Before we perform classification , we need to pass through two preliminary steps namely , Image Preprocessing ( IP ) and Feature Extraction ( FE ) a... | Image Preprocessing, Feature Extraction |
TR-13913 | [
"Due",
"to",
"the",
"use",
"of",
"MIMO",
"array",
"and",
"random",
"frequency",
"selection",
"at",
"transmitter",
",",
"where",
"denotes",
"the",
"number",
"of",
"transmit",
"antennas",
"at",
"DM",
"transceiver",
",",
"the",
"desired",
"receiver",
"requires",
... | [
4,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
4,
4,
4,
4,
4,
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(label... | 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: Due to the use of MIMO array and random frequency selection at transmitter , where denotes the number of transmit antennas at DM transceiver , the d... | No expansions found |
TR-13914 | [
"The",
"Relative",
"Agreement",
"(",
"RA",
")",
"model",
"then",
"extends",
"the",
"Bounded",
"Confidence",
"model",
"to",
"allow",
"agents",
"to",
"assign",
"weights",
"to",
"the",
"beliefs",
"of",
"others",
"by",
"quantifying",
"the",
"extent",
"of",
"the"... | [
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,
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(label... | 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 Relative Agreement ( RA ) model then extends the Bounded Confidence model to allow agents to assign weights to the beliefs of others by quantify... | Relative Agreement |
TR-13915 | [
"For",
"the",
"sake",
"of",
"a",
"complete",
"comparison",
",",
"we",
"present",
"the",
"results",
"of",
"our",
"system",
"FTSum",
"together",
"with",
"the",
"the",
"attentional",
"s2s",
"model",
"s2s+att",
"."
] | [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
1,
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(label... | 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 the sake of a complete comparison , we present the results of our system FTSum together with the the attentional s2s model s2s+att . | No expansions found |
TR-13916 | [
"Belief",
"Propagation",
"(",
"BP",
")",
"is",
"a",
"widely",
"employed",
"approximate",
"inference",
"algorithms",
"for",
"PGMs",
"."
] | [
0,
2,
4,
1,
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(label... | 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: Belief Propagation ( BP ) is a widely employed approximate inference algorithms for PGMs . | Belief Propagation |
TR-13917 | [
"Recurrent",
"Neural",
"Network",
"(",
"RNN",
")",
"is",
"used",
"for",
"sequence",
"prediction",
"problem",
"like",
"named",
"entity",
"recognition",
"."
] | [
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(label... | 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: Recurrent Neural Network ( RNN ) is used for sequence prediction problem like named entity recognition . | Recurrent Neural Network |
TR-13918 | [
"Based",
"on",
"the",
"DeepLesion",
"dataset",
",",
"proposed",
"a",
"weakly",
"supervised",
"self",
"-",
"paced",
"segmentation",
"segmentation",
"(",
"WSSS",
")",
"method",
"that",
"utilized",
"tumor",
"'s",
"long-",
"and",
"short",
"-",
"axis",
"drawings",
... | [
4,
4,
4,
4,
4,
4,
4,
4,
0,
2,
2,
2,
2,
2,
2,
4,
1,
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
] | 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(label... | 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: Based on the DeepLesion dataset , proposed a weakly supervised self - paced segmentation segmentation ( WSSS ) method that utilized tumor 's long- a... | weakly supervised self - paced segmentation segmentation |
TR-13919 | [
"Supported",
"in",
"part",
"by",
"Office",
"of",
"Naval",
"Research",
"(",
"ONR",
")",
"grant",
"N00014",
"-",
"18",
"-",
"1",
"-",
"2562",
"."
] | [
4,
4,
4,
4,
0,
2,
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(label... | 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: Supported in part by Office of Naval Research ( ONR ) grant N00014 - 18 - 1 - 2562 . | Office of Naval Research |
TR-13920 | [
"The",
"products",
"included",
"in",
"this",
"shopping",
"pattern",
"are",
"especially",
"needed",
"for",
"the",
"IT",
"sector",
"."
] | [
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(label... | 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 products included in this shopping pattern are especially needed for the IT sector . | No expansions found |
TR-13921 | [
"Some",
"use",
"the",
"direction",
"of",
"arrival",
"(",
"DOA",
")",
"of",
"the",
"SOI",
"and",
"directly",
"calculate",
"the",
"weight",
"vector",
"by",
"sample",
"matrix",
"inversion",
"(",
"SMI",
")",
"."
] | [
4,
4,
4,
0,
2,
2,
4,
1,
4,
4,
4,
1,
4,
4,
4,
4,
4,
4,
4,
0,
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(label... | 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: Some use the direction of arrival ( DOA ) of the SOI and directly calculate the weight vector by sample matrix inversion ( SMI ) . | direction of arrival, sample matrix inversion |
TR-13922 | [
"The",
"Domain",
"Transfer",
"Network",
"(",
"DTN",
")",
"we",
"present",
"employs",
"a",
"compound",
"loss",
"function",
"that",
"includes",
"a",
"multiclass",
"GAN",
"loss",
",",
"an",
"-constancy",
"component",
",",
"and",
"a",
"regularizing",
"component",
... | [
4,
0,
2,
2,
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
] | 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(label... | 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 Domain Transfer Network ( DTN ) we present employs a compound loss function that includes a multiclass GAN loss , an -constancy component , and ... | Domain Transfer Network |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.