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The WaCky wide web: a collection of very large linguistically processed web-crawled corpora
This article introduces ukWaC, deWaC and itWaC, three very large corpora of English, German, and Italian built by web crawling, and describes the methodology and tools used in their construction. TheExpand
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Multimodal Distributional Semantics
Distributional semantic models derive computational representations of word meaning from the patterns of co-occurrence of words in text. Such models have been a success story of computationalExpand
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Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors
Context-predicting models (more commonly known as embeddings or neural language models) are the new kids on the distributional semantics block. Despite the buzz surrounding these models, theExpand
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A SICK cure for the evaluation of compositional distributional semantic models
Shared and internationally recognized benchmarks are fundamental for the development of any computational system. We aim to help the research community working on compositional distributionalExpand
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What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Although much effort has recently been devoted to training high-quality sentence embeddings, we still have a poor understanding of what they are capturing. "Downstream" tasks, often based on sentenceExpand
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Nouns are Vectors, Adjectives are Matrices: Representing Adjective-Noun Constructions in Semantic Space
We propose an approach to adjective-noun composition (AN) for corpus-based distributional semantics that, building on insights from theoretical linguistics, represents nouns as vectors and adjectivesExpand
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Improving zero-shot learning by mitigating the hubness problem
The zero-shot paradigm exploits vector-based word representations extracted from text corpora with unsupervised methods to learn general mapping functions from other feature spaces onto word space,Expand
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Distributional Memory: A General Framework for Corpus-Based Semantics
Research into corpus-based semantics has focused on the development of ad hoc models that treat single tasks, or sets of closely related tasks, as unrelated challenges to be tackled by extractingExpand
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Distributional Semantics in Technicolor
Our research aims at building computational models of word meaning that are perceptually grounded. Using computer vision techniques, we build visual and multimodal distributional models and compareExpand
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How we BLESSed distributional semantic evaluation
We introduce BLESS, a data set specifically designed for the evaluation of distributional semantic models. BLESS contains a set of tuples instantiating different, explicitly typed semantic relations,Expand
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