4,502 research outputs found
Comparing Transformers and RNNs on predicting human sentence processing data
Recurrent neural networks (RNNs) have long been an architecture of interest
for computational models of human sentence processing. The more recently
introduced Transformer architecture has been shown to outperform recurrent
neural networks on many natural language processing tasks but little is known
about their ability to model human language processing. It has long been
thought that human sentence reading involves something akin to recurrence and
so RNNs may still have an advantage over the Transformer as a cognitive model.
In this paper we train both Transformer and RNN based language models and
compare their performance as a model of human sentence processing. We use the
trained language models to compute surprisal values for the stimuli used in
several reading experiments and use mixed linear modelling to measure how well
the surprisal explains measures of human reading effort. Our analysis shows
that the Transformers outperform the RNNs as cognitive models in explaining
self-paced reading times and N400 strength but not gaze durations from an
eye-tracking experiment
Asynchronous Changes in Vegetation, Runoff and Erosion in the Nile River Watershed during the Holocene
The termination of the African Humid Period in northeastern Africa during the early
Holocene was marked by the southward migration of the rain belt and the
disappearance of the Green Sahara. This interval of drastic environmental changes
was also marked by the initiation of food production by North African huntergatherer
populations and thus provides critical information on human-environment
relationships. However, existing records of regional climatic and environmental
changes exhibit large differences in timing and modes of the wet/dry transition at
the end of the African Humid Period. Here we present independent records of
changes in river runoff, vegetation and erosion in the Nile River watershed during
the Holocene obtained from a unique sedimentary sequence on the Nile River fan
using organic and inorganic proxy data. This high-resolution reconstruction allows
to examine the phase relationship between the changes of these three parameters
and provides a detailed picture of the environmental conditions during the
Paleolithic/Neolithic transition. The data show that river runoff decreased gradually
during the wet/arid transition at the end of the AHP whereas rapid shifts of
vegetation and erosion occurred earlier between 8.7 and ,6 ka BP. These
asynchronous changes are compared to other regional records and provide new
insights into the threshold responses of the environment to climatic changes. Our
record demonstrates that the degradation of the environment in northeastern Africa
was more abrupt and occurred earlier than previously thought and may have
accelerated the process of domestication in order to secure sustainable food
resources for the Neolithic African populations
Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge
Distributional semantic models capture word-level meaning that is useful in
many natural language processing tasks and have even been shown to capture
cognitive aspects of word meaning. The majority of these models are purely text
based, even though the human sensory experience is much richer. In this paper
we create visually grounded word embeddings by combining English text and
images and compare them to popular text-based methods, to see if visual
information allows our model to better capture cognitive aspects of word
meaning. Our analysis shows that visually grounded embedding similarities are
more predictive of the human reaction times in a large priming experiment than
the purely text-based embeddings. The visually grounded embeddings also
correlate well with human word similarity ratings. Importantly, in both
experiments we show that the grounded embeddings account for a unique portion
of explained variance, even when we include text-based embeddings trained on
huge corpora. This shows that visual grounding allows our model to capture
information that cannot be extracted using text as the only source of
information
Semantic sentence similarity: size does not always matter
This study addresses the question whether visually grounded speech
recognition (VGS) models learn to capture sentence semantics without access to
any prior linguistic knowledge. We produce synthetic and natural spoken
versions of a well known semantic textual similarity database and show that our
VGS model produces embeddings that correlate well with human semantic
similarity judgements. Our results show that a model trained on a small
image-caption database outperforms two models trained on much larger databases,
indicating that database size is not all that matters. We also investigate the
importance of having multiple captions per image and find that this is indeed
helpful even if the total number of images is lower, suggesting that
paraphrasing is a valuable learning signal. While the general trend in the
field is to create ever larger datasets to train models on, our findings
indicate other characteristics of the database can just as important important.Comment: This paper has been accepted at Interspeech 2021 where it will be
presented and appear in the conference proceedings in September 202
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The Learnability of the Wh-Island Constraint in Dutch by a Long Short-Term Memory Network
The current study investigates whether a Long Short-Term Memory (LSTM) network can learn the wh-island constraint in Dutch in a way comparable to human native speakers. After establishing with an acceptability judgement task that native speakers demonstrate a clear sensitivity to wh-island violations, the LSTM network was tested on the same sentences. Contrary to the results of the native speakers, the network was not able to recognize wh-islands and to block gap expectancies within them. This suggests that input and the networkâs inductive biases alone might not be enough to learn about syntactic island constraints, and that built-in language knowledge or abilities might be necessary
The missing-VP effect in readers of English as a second language
English sentences with double center-embedded clauses are read faster when they are made ungrammatical by removing one of the required verb phrases. This phenomenon is known as the missing-VP effect. German and Dutch speakers do not experience the missing-VP effect when reading their native language, but they do when reading English as a second language (L2). We investigate whether the missing-VP effect when reading L2 English occurs in native Dutch speakers because their knowledge of English is similar to that of native English speakers (the high exposure account), or because of the difficulty of L2 reading (the low proficiency account). In an eye-tracking study, we compare the size of the missing-VP effect between native Dutch and native English participants, and across native Dutch participants with varying L2 English proficiency and exposure. Results provide evidence for both accounts, suggesting that both native-like knowledge of English and L2 reading difficulty play a role
Nanostructure-modulated planar high spectral resolution spectro-polarimeter
We present a planar spectro-polarimeter based on Fabry-P{\'e}rot cavities
with embedded polarization-sensitive high-index nanostructures. A
m-thick spectro-polarimetric system for 3 spectral bands and 2 linear
polarization states is experimentally demonstrated. Furthermore, an optimal
design is theoretically proposed, estimating that a system with a bandwidth of
127~nm and a spectral resolution of 1~nm is able to reconstruct the first three
Stokes parameters \textcolor{black}{with a signal-to-noise ratio of -13.14~dB
with respect to the the shot noise limited SNR}. The pixelated
spectro-polarimetric system can be directly integrated on a sensor, thus
enabling applicability in a variety of miniaturized optical devices, including
but not limited to satellites for Earth observation
UvA-DARE (Digital Academic Repository) Generalization and Systematicity in Echo State Networks
Abstract Echo state networks (ESNs) are recurrent neural networks that can be trained efficiently because the weights of recurrent connections remain fixed at random values. Investigations of these networks' ability to generalize in sentence-processing tasks have resulted in mixed outcomes. Here, we argue that ESNs do generalize but that they are not systematic, which we define as the ability to generally outperform Markov models on test sentences that violate the training sentences' grammar. Moreover, we show that systematicity in ESNs can easily be obtained by switching from arbitrary to informative representations of words, suggesting that the information provided by such representations facilitates connectionist systematicity
The metabolic vascular syndrome - guide to an individualized treatment
In ancient Greek medicine the concept of a distinct syndrome (going together) was used to label 'a group of signs and symptoms' that occur together and 'characterize a particular abnormality and condition'. The (dys)metabolic syndrome is a common cluster of five pre-morbid metabolic-vascular risk factors or diseases associated with increased cardiovascular morbidity, fatty liver disease and risk of cancer. The risk for major complications such as cardiovascular diseases, NASH and some cancers develops along a continuum of risk factors into clinical diseases. Therefore we still include hyperglycemia, visceral obesity, dyslipidemia and hypertension as diagnostic traits in the definition according to the term 'deadly quartet'. From the beginning elevated blood pressure and hyperglycemia were core traits of the metabolic syndrome associated with endothelial dysfunction and increased risk of cardiovascular disease. Thus metabolic and vascular abnormalities are in extricable linked. Therefore it seems reasonable to extend the term to metabolic-vascular syndrome (MVS) to signal the clinical relevance and related risk of multimorbidity. This has important implications for integrated diagnostics and therapeutic approach. According to the definition of a syndrome the rapid global rise in the prevalence of all traits and comorbidities of the MVS is mainly caused by rapid changes in life-style and sociocultural transition resp. with over- and malnutrition, low physical activity and social stress as a common soil
Unconditional cash transfers for reducing poverty and vulnerabilities: effect on use of health services and health outcomes in low-and middle-income countries
Background Unconditional cash transfers (UCTs; provided without obligation) for reducing poverty and vulnerabilities (e.g. orphanhood, old age or HIV infection) are a type of social protection intervention that addresses a key social determinant of health (income) in lowâ and middleâincome countries (LMICs). The relative effectiveness of UCTs compared with conditional cash transfers (CCTs; provided so long as the recipient engages in prescribed behaviours such as using a health service or attending school) is unknown. Objectives To assess the effects of UCTs for improving health services use and health outcomes in vulnerable children and adults in LMICs. Secondary objectives are to assess the effects of UCTs on social determinants of health and healthcare expenditure and to compare to effects of UCTs versus CCTs. Search methods We searched 17 electronic academic databases, including the Cochrane Public Health Group Specialised Register, the Cochrane Database of Systematic Reviews (the Cochrane Library 2017, Issue 5), MEDLINE and Embase, in May 2017. We also searched six electronic grey literature databases and websites of key organisations, handsearched key journals and included records, and sought expert advice. Selection criteria We included both parallel group and clusterârandomised controlled trials (RCTs), quasiâRCTs, cohort and controlled beforeâandâafter (CBAs) studies, and interrupted time series studies of UCT interventions in children (0 to 17 years) and adults (18 years or older) in LMICs. Comparison groups received either no UCT or a smaller UCT. Our primary outcomes were any health services use or health outcome. Data collection and analysis Two reviewers independently screened potentially relevant records for inclusion criteria, extracted data and assessed the risk of bias. We tried to obtain missing data from study authors if feasible. For clusterâRCTs, we generally calculated risk ratios for dichotomous outcomes from crude frequency measures in approximately correct analyses. Metaâanalyses applied the inverse variance or MantelâHaenszel method with random effects. We assessed the quality of evidence using the GRADE approach. Main results We included 21 studies (16 clusterâRCTs, 4 CBAs and 1 cohort study) involving 1,092,877 participants (36,068 children and 1,056,809 adults) and 31,865 households in Africa, the Americas and SouthâEast Asia in our metaâanalyses and narrative synthesis. The 17 types of UCTs we identified, including one basic universal income intervention, were pilot or established government programmes or research experiments. The cash value was equivalent to 1.3% to 53.9% of the annualised gross domestic product per capita. All studies compared a UCT with no UCT, and three studies also compared a UCT with a CCT. Most studies carried an overall high risk of bias (i.e. often selection and/or performance bias). Most studies were funded by national governments and/or international organisations. Throughout the review, we use the words \u27probably\u27 to indicate moderateâquality evidence, \u27may/maybe\u27 for lowâquality evidence, and \u27uncertain\u27 for very lowâquality evidence. UCTs may not have impacted the likelihood of having used any health service in the previous 1 to 12 months, when participants were followed up between 12 and 24 months into the intervention (risk ratio (RR) 1.04, 95% confidence interval (CI) 1.00 to 1.09, P = 0.07, 5 clusterâRCTs, N = 4972, I² = 2%, lowâquality evidence). At one to two years, UCTs probably led to a clinically meaningful, very large reduction in the likelihood of having had any illness in the previous two weeks to three months (odds ratio (OR) 0.73, 95% CI 0.57 to 0.93, 5 clusterâRCTs, N = 8446, I² = 57%, moderateâquality evidence). Evidence from five clusterâRCTs on food security was too inconsistent to be combined in a metaâanalysis, but it suggested that at 13 to 24 months\u27 followâup, UCTs could increase the likelihood of having been food secure over the previous month (lowâquality evidence). UCTs may have increased participants\u27 level of dietary diversity over the previous week, when assessed with the Household Dietary Diversity Score and followed up 24 months into the intervention (mean difference (MD) 0.59 food categories, 95% CI 0.18 to 1.01, 4 clusterâRCTs, N = 9347, I² = 79%, lowâquality evidence). Despite several studies providing relevant evidence, the effects of UCTs on the likelihood of being moderately stunted and on the level of depression remain uncertain. No evidence was available on the effect of a UCT on the likelihood of having died. UCTs probably led to a clinically meaningful, moderate increase in the likelihood of currently attending school, when assessed at 12 to 24 months into the intervention (RR 1.06, 95% CI 1.03 to 1.09, 6 clusterâRCTs, N = 4800, I² = 0%, moderateâquality evidence). The evidence was uncertain for whether UCTs impacted livestock ownership, extreme poverty, participation in child labour, adult employment or parenting quality. Evidence from six clusterâRCTs on healthcare expenditure was too inconsistent to be combined in a metaâanalysis, but it suggested that UCTs may have increased the amount of money spent on health care at 7 to 24 months into the intervention (lowâquality evidence). The effects of UCTs on health equity (or unfair and remedial health inequalities) were very uncertain. We did not identify any harms from UCTs. Three clusterâRCTs compared UCTs versus CCTs with regard to the likelihood of having used any health services, the likelihood of having had any illness or the level of dietary diversity, but evidence was limited to one study per outcome and was very uncertain for all three. Authors\u27 conclusions This body of evidence suggests that unconditional cash transfers (UCTs) may not impact a summary measure of health service use in children and adults in LMICs. However, UCTs probably or may improve some health outcomes (i.e. the likelihood of having had any illness, the likelihood of having been food secure, and the level of dietary diversity), one social determinant of health (i.e. the likelihood of attending school), and healthcare expenditure. The evidence on the relative effectiveness of UCTs and CCTs remains very uncertain
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