4,560 research outputs found
Limitations of Cross-Lingual Learning from Image Search
Cross-lingual representation learning is an important step in making NLP
scale to all the world's languages. Recent work on bilingual lexicon induction
suggests that it is possible to learn cross-lingual representations of words
based on similarities between images associated with these words. However, that
work focused on the translation of selected nouns only. In our work, we
investigate whether the meaning of other parts-of-speech, in particular
adjectives and verbs, can be learned in the same way. We also experiment with
combining the representations learned from visual data with embeddings learned
from textual data. Our experiments across five language pairs indicate that
previous work does not scale to the problem of learning cross-lingual
representations beyond simple nouns
Why is unsupervised alignment of English embeddings from different algorithms so hard?
This paper presents a challenge to the community: Generative adversarial
networks (GANs) can perfectly align independent English word embeddings induced
using the same algorithm, based on distributional information alone; but fails
to do so, for two different embeddings algorithms. Why is that? We believe
understanding why, is key to understand both modern word embedding algorithms
and the limitations and instability dynamics of GANs. This paper shows that (a)
in all these cases, where alignment fails, there exists a linear transform
between the two embeddings (so algorithm biases do not lead to non-linear
differences), and (b) similar effects can not easily be obtained by varying
hyper-parameters. One plausible suggestion based on our initial experiments is
that the differences in the inductive biases of the embedding algorithms lead
to an optimization landscape that is riddled with local optima, leading to a
very small basin of convergence, but we present this more as a challenge paper
than a technical contribution.Comment: Accepted at EMNLP 201
Issue Framing in Online Discussion Fora
In online discussion fora, speakers often make arguments for or against
something, say birth control, by highlighting certain aspects of the topic. In
social science, this is referred to as issue framing. In this paper, we
introduce a new issue frame annotated corpus of online discussions. We explore
to what extent models trained to detect issue frames in newswire and social
media can be transferred to the domain of discussion fora, using a combination
of multi-task and adversarial training, assuming only unlabeled training data
in the target domain.Comment: To appear in NAACL-HLT 201
Novel decay dynamics revealed for virus-mediated drug activation in cytomegalovirus infection
Human cytomegalovirus (CMV) infection is a substantial cause of morbidity and mortality in immunocompromised hosts and globally is one of the most important congenital infections. The nucleoside analogue ganciclovir (GCV), which requires initial phosphorylation by the viral UL97 kinase, is the mainstay for treatment. To date, CMV decay kinetics during GCV therapy have not been extensively investigated and its clinical implications not fully appreciated. We measured CMV DNA levels in the blood of 92 solid organ transplant recipients with CMV disease over the initial 21 days of ganciclovir therapy and identified four distinct decay patterns, including a new pattern exhibiting a transient viral rebound (Hump) following initial decline. Since current viral dynamics models were unable to account for this Hump profile, we developed a novel multi-level model, which includes the intracellular role of UL97 in the continued activation of ganciclovir, that successfully described all the decline patterns observed. Fitting the data allowed us to estimate ganciclovir effectiveness in vivo (mean 92%), infected cell half-life (mean 0.7 days), and other viral dynamics parameters that determine which of the four kinetic patterns will ensue. An important clinical implication of our results is that the virological efficacy of GCV operates over a broad dose range. The model also raises the possibility that GCV can drive replication to a new lower steady state but ultimately cannot fully eradicate it. This model is likely to be generalizable to other anti-CMV nucleoside analogs that require activation by viral enzymes such as UL97 or its homologues
Influence of pH and media composition on suspension stability of silver, zinc oxide, and titanium dioxide nanoparticles and immobilization of Daphnia magna under guideline testing conditions
A taste of plastic - quantifying micro- and nanoplastic ingestion and interactions with feeding in daphnia magna (E)
The influence of pH and media composition on suspension stability of Ag, ZnO, and TiO2 nanoparticles and immobilization of Daphnia magna under guideline testing conditions
Transformation and distribution processes governing the fate and behaviour of nanomaterials in the environment: an overview
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