[PDF] Top 20 Towards Zero shot Language Modeling
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Towards Zero shot Language Modeling
... - SHOT learning setting, with the uninformed prior (N INF ) and the universal prior (U NIV ): see §2 for the descriptions of the ...each language (rows) has been held ... See full document
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Hubness and Pollution: Delving into Cross Space Mapping for Zero Shot Learning
... for zero-shot learning, in order to achieve a better understanding of its shortcom- ings, and improve its quality by devising meth- ods to overcome ...reporting zero-shot performances in both ... See full document
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Reconstructing Capsule Networks for Zero shot Intent Classification
... Capsule Networks. Capsule Networks (Sabour et al., 2017) were first proposed to address the shortcomings of convolutional neural networks (CNN) in the domain of computer vision. It al- lows the networks to learn ... See full document
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Zero Shot Relation Extraction via Reading Comprehension
... key modeling challenge is that most ex- isting reading-comprehension problem formula- tions assume the answer to the question is always present in the given ...This modeling approach is another advantage of ... See full document
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Semantic embeddings of generic objects for zero-shot learning
... Sentence embeddings—universal sentence embedding models learn continuous distributed representations of sentences. Different embedding models differ in their architecture and the objective function they use for training. ... See full document
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Zero shot Reading Comprehension by Cross lingual Transfer Learning with Multi lingual Language Representation Model
... same language as testing data, using the untranslated data still yield better ...same language, the English training data is always better than the Chinese data (En-XX ...same language or ... See full document
8
Gaussian Visual Linguistic Embedding for Zero Shot Recognition
... than language-only models ...outperform language only models in various lexical tasks (Bruni et ...of zero-shot learning (ZSL). Zero-shot recognition aims to recognise visual ... See full document
7
Survey and Analysis on Language Translator using Neural Machine Translation
... that language pair. We show that the quality of zero shot language pairs can easily be improved with little additional data of the language pair in question,” the paper ... See full document
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A neural interlingua for multilingual machine translation
... English language model is stronger in the multilingual case, since the English decoder sees more English ...3.4 Zero-shot Multilingual Classification We constructed a multilingual Yelp review dataset ... See full document
9
Zero Shot Transfer Learning for Event Extraction
... Most previous event extraction methods have been based on supervised learning, using either sym- bolic features (Ji and Grishman, 2008; Miwa et al., 2009; Liao and Grishman, 2010; Liu et al., 2010; Hong et al., 2011; ... See full document
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Zero Shot Activity Recognition with Verb Attribute Induction
... large-scale zero-shot activity recognition by modeling the visual and linguistic attributes of ac- tion ...for zero-shot classes and focuses primarily on object attributes, our model ... See full document
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Consistency by Agreement in Zero Shot Neural Machine Translation
... reported zero-resource results on a subset of these directions and our ap- proach outperforms the former but not the latter on these ...each language pair and the approach of Chen et ... See full document
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A Deep Relevance Model for Zero Shot Document Filtering
... In the era of big data, focused analysis for diverse topics with a short response time becomes an urgent demand. As a funda- mental task, information filtering therefore becomes a critical necessity. In this pa- per, we ... See full document
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Dual-View Ranking with Hardness Assessment for Zero-Shot Learning
... for zero- shot learning simultaneously ranking labels for an image by point-to-point metric and ranking images for a label by point- to-set metric, which is capable of better modeling the rela- ... See full document
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Zero-Shot Neural Transfer for Cross-Lingual Entity Linking
... In most cases, the M ANUAL HRL is also the best perform- ing in B EST -53. However, we see that the Dravidian Tel- ugu (te) seems to obtain higher accuracy with Indo-Aryan HRLs – Punjabi (pa) or Hindi (hi). This could be ... See full document
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Integrating Semantic Knowledge to Tackle Zero shot Text Classification
... In the face of insufficient data, data augmentation has been widely used to improve generalisation of deep neural networks especially in computer vi- sion (Krizhevsky et al., 2012) and multimodality (Dong et al., 2017b), ... See full document
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Description Based Zero shot Fine Grained Entity Typing
... Entity Typing assigns a semantic type (e.g., per- son, location, organization) to an entity mention in text based on the local context. It is useful for enhancing a variety of Natural Language Process- ing(NLP) ... See full document
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Evaluating the Supervised and Zero shot Performance of Multi lingual Translation Models
... low-resource language pairs, and because of the potential efficiency gains enabled by translation models which share param- eters across many languages (Dong et ...perform zero-shot translation, ... See full document
9
Zero shot Entity Extraction from Web Pages
... In order to extract entities of a fine-grained category from semi-structured data in web pages, existing information extraction sys- tems rely on seed examples or redundancy across multiple web pages. In this paper, we ... See full document
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Zero Shot Entity Linking by Reading Entity Descriptions
... the zero-shot entity linking task, where mentions must be linked to unseen en- tities without in-domain labeled ...on language under- standing to resolve the new ... See full document
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