Results 11 to 20 of about 5,623,819 (318)
Are NLP Models really able to Solve Simple Math Word Problems? [PDF]
North American Chapter of the Association for Computational Linguistics, 2021 The problem of designing NLP solvers for math word problems (MWP) has seen sustained research activity and steady gains in the test accuracy. Since existing solvers achieve high performance on the benchmark datasets for elementary level MWPs containing ...
Arkil Patel +2 more
semanticscholar +1 more source
Deep Contextualized Word Representations [PDF]
North American Chapter of the Association for Computational Linguistics, 2018 We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i.e., to model polysemy).
Matthew E. Peters +6 more
semanticscholar +1 more source
Enriching Word Vectors with Subword Information [PDF]
Transactions of the Association for Computational Linguistics, 2016 Continuous word representations, trained on large unlabeled corpora are useful for many natural language processing tasks. Popular models that learn such representations ignore the morphology of words, by assigning a distinct vector to each word. This is
Piotr Bojanowski +3 more
semanticscholar +1 more source
Unified Named Entity Recognition as Word-Word Relation Classification [PDF]
AAAI Conference on Artificial Intelligence, 2021 So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied individually.
Jingye Li +7 more
semanticscholar +1 more source
WARP: Word-level Adversarial ReProgramming [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Transfer learning from pretrained language models recently became the dominant approach for solving many NLP tasks. A common approach to transfer learning for multiple tasks that maximize parameter sharing trains one or more task-specific layers on top ...
Karen Hambardzumyan +2 more
semanticscholar +1 more source
Word Alignment by Fine-tuning Embeddings on Parallel Corpora [PDF]
Conference of the European Chapter of the Association for Computational Linguistics, 2021 Word alignment over parallel corpora has a wide variety of applications, including learning translation lexicons, cross-lingual transfer of language processing tools, and automatic evaluation or analysis of translation outputs. The great majority of past
Zi-Yi Dou, Graham Neubig
semanticscholar +1 more source
Vision, 2021 The primary goal of this study was to investigate the effects of sex, oral contraceptive (OC) use, and menstrual cycle phase on common ocular parameters assessed during ophthalmic evaluations, namely intraocular pressure (IOP), central corneal thickness (
Lourdes Fortepiani +2 more
doaj +1 more source
Fourier transforming a trapped Bose-Einstein condensate by waiting a quarter of the trap period: simulation and applications [PDF]
, 2006 We investigate the property of isotropic harmonic traps to Fourier transform a weakly interacting Bose–Einstein condensate (BEC) every quarter of a trap period.
Caradoc-Davies B M +10 more
core +1 more source
GloVe: Global Vectors for Word Representation
Conference on Empirical Methods in Natural Language Processing, 2014 Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the origin of these regularities has remained opaque. We analyze and make explicit
Jeffrey Pennington +2 more
semanticscholar +1 more source
Drowning is fast, silent, and preventable: a Texas example of research in action
Injury Epidemiology, 2023 Drowning is a major public health issue internationally. In August 2022, a report was released by members of the Central Texas Drowning Prevention Action Team that provided data on drowning fatalities in Texas between 2006 and 2020 and offered ...
Stewart R. Williams +2 more
doaj +1 more source