[PDF] Top 20 Iterative Search for Weakly Supervised Semantic Parsing
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Iterative Search for Weakly Supervised Semantic Parsing
... open-domain semantic parsing tasks where it may not be pos- sible to arrive at a complete set of operators re- quired by the ...training semantic parsers with weak supervision requires not only ... See full document
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Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning
... object-based semantic segmentation while no attempts have been made to deal with the more difficult scene ...scene parsing but in- vestigating on parsing a scene image into a structured con- ... See full document
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Semantic Parsing with Semi Supervised Sequential Autoencoders
... cuses on defining the grammar of the logical forms (Zettlemoyer and Collins, 2005), other models learn purely from aligned pairs of text and logical form (Berant and Liang, 2014), or from more weakly su- pervised ... See full document
10
Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions
... CCG semantic parsing approach that learns a joint model of mean- ing and context for interpreting and executing natural language instructions, using various types of weak ... See full document
14
A Supervised Semantic Parsing with Lexicon Extension and Syntactic Constraint
... A main problem within the above semantic pars- ing is that it admits a large number of ungram- matical parses. This may result in the waste of time for searching the parse space. Our motiva- tion using the ... See full document
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Weakly Supervised Slot Tagging with Partially Labeled Sequences from Web Search Click Logs
... a weakly supervised framework that utilizes the information available in web click ...learn semantic tagging models from large-scale and naturally occurring user interaction data (Volkova et ... See full document
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Weakly supervised deep semantic segmentation using CNN and ELM with semantic candidate regions
... as supervised information and divides all pixels or superpixels in the image contained target label into positive samples and other negative samples without target ...between semantic labels and ...ing ... See full document
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Semantic Parsing with Dual Learning
... A semantic parser can be trained from labeled logical forms or weakly supervised samples (Krishnamurthy and Mitchell, 2012; Be- rant et ...a semantic parsing dataset starting from ... See full document
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Weakly Supervised Definition Extraction
... includes semantic informa- tion manually annotated such as definiendum or hy- pernym, we do not exploit any of it, which makes the seed-construction step highly flexible as it only requires the sentence ... See full document
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Corpus based Semantic Lexicon Induction with Web based Corroboration
... a weakly supervised corpus- based method for semantic lexicon induction with statistics obtained from the ...a semantic lexicon from a domain-specific ...the semantic category. For each ... See full document
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StructVAE: Tree structured Latent Variable Models for Semi supervised Semantic Parsing
... Semantic Parsing Most existing works allevi- ate issues of limited parallel data through weakly- supervised learning, using the denotations of MRs as indirect supervision (Reddy et ...of ... See full document
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Weakly Supervised Training of Semantic Parsers
... Our experiments use a subset of 77 relations 2 from Freebase 3 as the knowledge base and a corpus of web sentences. We constructed the sentence corpus by first sampling sentences from a web crawl and parsing them ... See full document
12
Evaluating Induced CCG Parsers on Grounded Semantic Parsing
... see a comparatively small gain in performance (43 vs 46). It is interesting that such weakly supervised models are able to achieve over 90% of the perfor- mance of a fully supervised parser. To ... See full document
6
Weakly Supervised Semantic Parsing with Abstract Examples
... Training semantic parsers from weak su- pervision (denotations) rather than strong supervision (programs) complicates train- ing in two ...large search space of potential programs needs to be explored at ... See full document
11
Weakly Supervised Neural Semantic Parsing with a Generative Ranker
... Weakly-supervised semantic parsers are trained on utterance-denotation pairs, treating logical forms as ...large search space and spuriousness of logical ...for weakly-supervised ... See full document
12
Weakly supervised evidence pinpointing and description
... strongly supervised method which describes the anatomy by local patches at each of the landmarks as well as the geometry of the landmark locations ...on weakly annotated ... See full document
13
How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing
... build semantic pars- ing datasets by generating canonical ut- terances using a grammar and having crowdworkers paraphrase them into natu- ral ...for semantic parsing ...a semantic ... See full document
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Weakly Supervised Approaches for Ontology Population
... to search ef- ficiently for syntactic structures and to calculate their ...to search for syntactic structures, not ...we search for more complex structures than a relation between two words: for ... See full document
8
Weakly supervised learning of allomorphy
... In the realm of natural language processing, mor- phological segmentation is a well-researched and established problem (Goldsmith (2001), Creutz and Lagus (2005), Poon et al. (2009), Dreyer and Eisner (2011), Ruokolainen ... See full document
11
Weakly-Supervised Hierarchical Text Classification
... Hierarchical text classification, which aims to classify text documents into a given hierarchy, is an important task in many real-world applications. Recently, deep neural models are gaining increasing popularity for ... See full document
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