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Second-order contexts from lexical substitutes for few-shot learning of word representations
2019
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*
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In this paper, we focus on few-shot learning of emerging concepts that fully exploits only a few available contexts. ...
Previous context-based approaches to modelling unseen words only consider bag-of-word firstorder contexts, whereas our method aggregates contexts as second-order substitutes that are produced by a sequence-aware ...
Acknowledgments We acknowledge Peterhouse College at University of Cambridge for funding Qianchu Liu's PhD research. ...
doi:10.18653/v1/s19-1007
dblp:conf/starsem/LiuMK19
fatcat:3sdyzbzzgff3fgujoh7la2tg44
Few-shot Text Classification with Distributional Signatures
[article]
2020
arXiv
pre-print
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In this paper, we explore meta-learning for few-shot text classification. ...
Our model is trained within a meta-learning framework to map these signatures into attention scores, which are then used to weight the lexical representations of words. ...
used to weight the lexical representations of words. ...
arXiv:1908.06039v3
fatcat:bbddbkpop5gynaloacfxnuib3q
English Out-of-Vocabulary Lexical Evaluation Task
[article]
2019
arXiv
pre-print
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The OOV words are words that only appear in test samples. The goal of tasks is to provide solutions for OOV lexical classification and prediction. ...
The tasks require annotators to conclude the attributes of the OOV words based on their related contexts. ...
Second, most of the test words and the candidates in lexical substitution tasks such as [12] are daily words. ...
arXiv:1804.04242v3
fatcat:2h35jy5im5htbeqz76ejwu2qve
Siamese recurrent networks learn first-order logic reasoning and exhibit zero-shot compositional generalization
[article]
2019
arXiv
pre-print
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Can neural nets learn logic? ...
We approach this classic question with current methods, and demonstrate that recurrent neural networks can learn to recognize first order logical entailment relations between expressions. ...
In the last zero-shot learning experiment, we replace sets of nouns instead of single words, in order to assess the flexibility of the relational semantics that our networks have learned. ...
arXiv:1906.00180v1
fatcat:tf4i45rvprfmpm3mzljoyqccwa
Word Frequency Does Not Predict Grammatical Knowledge in Language Models
[article]
2020
arXiv
pre-print
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Finally, we find that a novel noun's grammatical properties can be few-shot learned from various types of training data. ...
Neural language models learn, to varying degrees of accuracy, the grammatical properties of natural languages. ...
Acknowledgements We thank the Google Cloud Platform research program for support. The Titan V used for this research was donated by the NVIDIA Corporation. ...
arXiv:2010.13870v1
fatcat:sj5ubiiqorevtoxpxaylrfzhpm
ON KNOWING A WORD
1999
Annual Review of Psychology
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A person who knows a word knows much more than its meaning and pronunciation. The contexts in which a word can be used to express a particular meaning are a critical component of word knowledge. ...
are able to identify the intended meanings of common polysemous words. ...
Unfortunately, learning words from context is a slow process. Many contexts of use must be encountered before a new word is mastered, so extensive reading is required for a large vocabulary. ...
doi:10.1146/annurev.psych.50.1.1
pmid:15012457
fatcat:dawazqvddvgivbufyinujuomau
Which Statistics Reflect Semantics? Rethinking Synonymy and Word Similarity
[chapter]
2005
Studies in Generative Grammar
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Overview A great deal of work has been done of late on the statistical modeling of word similarity relations (cf. ...
Acknowledgements I would like to thank the conference organizers for providing an open forum for discussion, and my ETS colleagues for their helpful comments on an earlier draft of this paper. ...
Any opinions expressed here are those of the author, and not necessarily of Educational Testing Service. ...
doi:10.1515/9783110197549.265
fatcat:plxpqfcdbjf6xijkw7kng7s4fu
On syllable structure and phonological variation: The case of i-epenthesis by Brazilian Portuguese learners of English
2017
Ilha do Desterro
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representations for single lexical items. ...
dual underlying representations which compete for selection at the moment of speaking. ...
First and foremost, we would like to thank our Brazilian collaborator, Léa Cardoso, for opening the doors of her school and for her active involvement in many aspects of this research, including her assistance ...
doi:10.5007/2175-8026.2017v70n3p169
fatcat:3pb5fenatvgprc4pm7ymyx6dui
Unsupervised Distillation of Syntactic Information from Contextualized Word Representations
[article]
2021
arXiv
pre-print
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Finally, we demonstrate the utility of our distilled representations by showing that they outperform the original contextualized representations in a few-shot parsing setting. ...
In this work, we tackle the task of unsupervised disentanglement between semantics and structure in neural language representations: we aim to learn a transformation of the contextualized vectors, that ...
Acknowledgments We would like to thank Gal Chechik for providing valuable feedback on early version of this work. ...
arXiv:2010.05265v2
fatcat:ejfjlke7czeuphg73lx4vjiasa
Analyzing machine-learned representations: A natural language case study
[article]
2019
arXiv
pre-print
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We find that these systems can learn abstract rules and generalize them to new contexts under certain circumstances -- similar to human zero-shot reasoning. ...
In this work, we study representations of sentences in one such artificial system for natural language processing. ...
Acknowledgements We are grateful to Anatole Gershman, Tim O'Donnell, Joshua Greene and Fiery Cushman for helpful discussions. ID is supported by Microsoft Research. ...
arXiv:1909.05885v1
fatcat:wo7z5woybfdvhe732gmc452soy
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
[article]
2016
arXiv
pre-print
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Our results show that DCC has distinct advantages over existing image and video captioning approaches for generating descriptions of new objects in context. ...
objects in context. ...
Marcus Rohrbach was supported by a fellowship within the FITweltweit-Program of the German Aca- ...
arXiv:1511.05284v2
fatcat:kjvewbdvybdhjbgo4jf27w7ote
A Survey On Neural Word Embeddings
[article]
2021
arXiv
pre-print
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The revolutionary idea of distributed representation for a concept is close to the working of a human mind in that the meaning of a word is spread across several neurons, and a loss of activation will ...
The study of meaning in natural language processing (NLP) relies on the distributional hypothesis where language elements get meaning from the words that co-occur within contexts. ...
[136] propose a neural representation learning model for predicting different types of lexical relations, e.g., hypernymy, synonymy, meronymy, etc. ...
arXiv:2110.01804v1
fatcat:rfxwasxwivdvzn6iukbpvvmnai
Effect of lexical cues on the production of active and passive sentences in Broca's and Wernicke's aphasia
2003
Brain and Language
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However when auxiliary and past tense morphemes were provided along with the verb stem, production of passive sentences improved drastically for both groups. ...
The ability to produce active and passive reversible and non-reversible sentences was examined when varying amounts of lexical information was provided. ...
Support for this notion comes from Bates et al. (1988) , who found the most frequent canonical word order is often preserved in aphasia in several languages. ...
doi:10.1016/s0093-934x(02)00586-2
pmid:12744953
pmcid:PMC3034248
fatcat:53cvgushmbdwhl4czmo6xp72ki
Virtual Augmentation Supported Contrastive Learning of Sentence Representations
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2110.08552v1 fatcat:vt5o47u36zgbfn3g3ghlveobju
We access the performance of VaSCL on a wide range of downstream tasks, and set a new state-of-the-art for unsupervised sentence representation learning. ...
We tackle this challenge by presenting a Virtual augmentation Supported Contrastive Learning of sentence representations (VaSCL). ...
±0.89 62.12±7.09
76.60±0.35 81.40±0.60 77.66±0.64
Table 3 : 3 Few-shot learning evaluation of Intent Classification. ...
arXiv:2110.08552v2
fatcat:t374n34vsjhh5fqim6q6xodq2e
Working Memory and Reading Skill Re-examined
[chapter]
2016
Attention and Performance XII
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British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-138-19163-1 (Set) ISBN: 978-1-315-54401-4 (Set) (ebk) ISBN: 978-1-138- ...
any information storage or retrieval system, without permission in writing from the publishers. ...
Office of Naval Research (O.N.R. Contract Num ber N0001486G0067 to S. Kornblum ) and by a grant from the Economic and Social Research Council of G reat Britain to M. Coltheart. ...
doi:10.4324/9781315630427-36
fatcat:hmaltn6wtng4nnkbn3izodfuki
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