245 research outputs found
BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting
The BLOOM model is a large publicly available multilingual language model, but its pretraining was limited to 46 languages. To extend the benefits of BLOOM to other languages without incurring prohibitively large costs, it is desirable to adapt BLOOM to new languages not seen during pretraining. In this work, we apply existing language adaptation strategies to BLOOM and benchmark its zero-shot prompting performance on eight new languages in a resource-constrained setting. We find language adaptation to be effective at improving zero-shot performance in new languages. Surprisingly, we find that adapter-based finetuning is more effective than continued pretraining for large models. In addition, we discover that prompting performance is not significantly affected by language specifics, such as the writing system. It is primarily determined by the size of the language adaptation data. We also add new languages to BLOOMZ, which is a multitask finetuned version of BLOOM capable of following task instructions zero-shot. We find including a new language in the multitask fine-tuning mixture to be the most effective method to teach BLOOMZ a new language. We conclude that with sufficient training data language adaptation can generalize well to diverse languages. Our code is available at https://github.com/bigscience-workshop/multilingual-modeling
Identification of soluble protein fragments by gene fragmentation and genetic selection
We describe a new method, which identifies protein fragments for soluble expression in Escherichia coli from a randomly fragmented gene library. Inhibition of E. coli dihydrofolate reductase (DHFR) by trimethoprim (TMP) prevents growth, but this can be relieved by murine DHFR (mDHFR). Bacterial strains expressing mDHFR fusions with the soluble proteins green fluroscent protein (GFP) or EphB2 (SAM domain) displayed markedly increased growth rates with TMP compared to strains expressing insoluble EphB2 (TK domain) or ketosteroid isomerase (KSI). Therefore, mDHFR is affected by the solubility of fusion partners and can act as a reporter of soluble protein expression. Random fragment libraries of the transcription factor Fli1 were generated by deoxyuridine incorporation and endonuclease V cleavage. The fragments were cloned upstream of mDHFR and TMP resistant clones expressing soluble protein were identified. These were found to cluster around the DNA binding ETS domain. A selected Fli1 fragment was expressed independently of mDHFR and was judged to be correctly folded by various biophysical methods including NMR. Soluble fragments of the cell-surface receptor Pecam1 were also identified. This genetic selection method was shown to generate expression clones useful for both structural studies and antibody generation and does not require a priori knowledge of domain architecture
Subnational climate entrepreneurship: innovative climate action in California and São Paulo
The distinct role of subnational governments such as states and provinces in addressing climate change has been increasingly acknowledged. But while most studies investigate the causes and consequences of particular governments’ actions and networking activities, this article argues that subnational governments can develop climate action as a collective entrepreneurial activity. Addressing many elements explored in this special issue, it focuses on the second question and identifies climate entrepreneurship in two subnational governments—the states of California (USA) and São Paulo (Brazil). Examining internal action, as well as interaction with local authorities, national governments and the international regime, entrepreneurial activities are identified in the invention, diffusion and evaluation of subnational climate policy in each case. The article draws from the recent scholarship on policy innovation, entrepreneurship and climate governance. It contributes to the literature by exploring entrepreneurial subnational government activity in addressing climate change and expanding the understanding of the effects of policy innovation at the subnational level
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders
Action Contro
The impact of Participatory Budgeting on health and wellbeing:A scoping review of evaluations
Background: Participatory budgeting (PB), citizens deliberating among themselves and with officials to decide how
to allocate funds for public goods, has been increasingly implemented across Europe and worldwide. While PB is
recommended as good practice by the World Bank and the United Nations, with potential to improve health and
wellbeing, it is unclear what evaluations have been conducted on the impact of PB on health and wellbeing.
Methods: For this scoping review, we searched 21 databases with no restrictions on publication date or language.
The search term ‘participatory budget’ was used as the relevant global label for the intervention of interest. Studies
were included if they reported original analysis of health, social, political, or economic and budgetary outcomes of
PB. We examined the study design, analysis, outcomes and location of included articles. Findings are reported
narratively.
Results: From 1458 identified references, 37 studies were included. The majority of evaluations (n = 24) were of PB
in South America, seven were in Europe. Most evaluations were case studies (n = 23) conducting ethnography and
surveys, focussing on political outcomes such as participation in PB or impacts on political activities. All of the
quantitative observational studies analysing population level data, except one in Russia, were conducted in South
America.
Conclusion: Despite increasing interest in PB, evaluations applying robust methods to analyse health and
wellbeing outcomes are scarce, particularly beyond Brazil. Therefore, implementation of PB schemes should be
accompanied by rigorous qualitative and quantitative evaluation to identify impacts and the processes by which
they are realised
He votes or she votes? Female and male discursive strategies in Twitter political hashtags
In this paper, we conduct a study about differences between female and
male discursive strategies when posting in the microblogging service
Twitter, with a particular focus on the hashtag designation process
during political debate. The fact that men and women use language in
distinct ways, reverberating practices linked to their expected roles in
the social groups, is a linguistic phenomenon known to happen in
several cultures and that can now be studied on the Web and on online
social networks in a large scale enabled by computing power. Here, for
instance, after analyzing tweets with political content posted during
Brazilian presidential campaign, we found out that male Twitter users,
when expressing their attitude toward a given candidate, are more prone
to use imperative verbal forms in hashtags, while female users tend to
employ declarative forms. This difference can be interpreted as a sign
of distinct approaches in relation to other network members: for
example, if political hashtags are seen as strategies of persuasion in
Twitter, imperative tags could be understood as more overt ways of
persuading and declarative tags as more indirect ones. Our findings help
to understand human gendered behavior in social networks and contribute
to research on the new fields of computer-enabled Internet linguistics
and social computing, besides being useful for several computational
tasks such as developing tag recommendation systems based on users'
collective preferences and tailoring targeted advertising strategies,
among others.FGW – Publications without University Leiden contrac
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