21 papers · ranked by Valyu relevance
Robert A.J. Borst, Rik Wehrens, Roland Bal
Background: The health policy and systems research literature increasingly observes that knowledge translation (KT) practices are difficult to sustain. An important issue is that it remains unclear what sustainability of KT practices means and how it can be improved. The aim of this study was thus to identify and…
John Damm Scheuer
This paper aims to show how organizational translation theories and models may supplement implementation science with a new process perspective on how knowledge objects such as Cochrane reviews, clinical guidelines and reference programs are implemented in practice in healthcare organizations. They build on Bruno…
Birthe Møgster, Lillian Bruland Selseng, Monika Alvestad Reime
This article aims to contribute to the research-practice gap in bereavement care by exploring Research Circles as a collaborative approach to implementation of research-based knowledge into bereavement care. Particularly the article discusses key dimensions for translating research concerning bereaved after…
John Ødemark
This commentary examines the claim made by Borst et al that knowledge translation (KT) should look to Science and Technology Studies (STS), the sociology of translation, and constructionist views on knowledge, and begin to think of the sustainability of a certain practice as construction work in continuous progress…
Abednego Musau, Lindsey Reynolds, Nabeel Petersen, Matthew Wilson + 2 more
More effective knowledge translation (KT) in the field of adolescent sexual and reproductive health (ASRH) could improve the speed at which effective health and behavioural interventions are delivered to young people, improving their overall health and well-being. Given the limited literature on KT for ASRH, this…
Guangsheng Ou, Mingwei Liu, Yuxuan Chen, Xueying Du + 4 more
'Zekai Zhang' 'Xin Peng' 'Zibin Zheng'] Large language models (LLMs) have behaved well in function-level code translation without repository-level context. However, the performance of LLMs in repository-level context code translation remains suboptimal due to complex dependencies and context, hindering their adoption…
Doreen Osmelak, Koel Dutta Chowdhury, Uliana Sentsova, Cristina España-Bonet + 1 more
Translators often enrich texts with background details that make implicit cultural meanings explicit for new audiences. This phenomenon, known as pragmatic explicitation, has been widely discussed in translation theory but rarely modeled computationally. We introduce PragExTra, the first multilingual corpus and…
Tam Trinh, Anh Dao, Hy Thi Hong Nhung, Truong Son Hy
Traditional Vietnamese Medicine (TVM) and Traditional Chinese Medicine (TCM) have shared significant similarities due to their geographical location, cultural exchanges, and hot and humid climatic conditions. However, unlike TCM, which has substantial works published to construct a knowledge graph, there is a notable…
Guangrong Qin, Kamileh Narsinh, Qi Wei, Jared C. Roach + 15 more
As large clinical and multiomics datasets and knowledge resources accumulate, they need to be transformed into computable and actionable information to support automated reasoning. These datasets range from laboratory experiment results to electronic health records (EHRs). Barriers to accessibility and sharing of such…
Jiahuan Li, Shanbo Cheng, Shujian Huang, Jiajun Chen
Language Models for Machine Translation Authors: ['Jiahuan Li' 'Shanbo Cheng' 'Shujian Huang' 'Jiajun Chen'] Large Language Models (LLM) have demonstrated their strong ability in the field of machine translation (MT), yet they suffer from high computational cost and latency. Therefore, transferring translation…
Eojin Kang, Juae Kim
Multilingual large language models (LLMs) open up new possibilities for leveraging information across languages, but their factual knowledge recall remains inconsistent depending on the input language. While previous studies have attempted to address this issue through English-based prompting and evaluation, we explore…
E. C. Wood, Amy K. Glen, Lindsey G. Kvarfordt, Finn Womack + 13 more
Biomedical translational science is increasingly using computational reasoning on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome, DrugBank, and SMPDB in order to facilitate discovery of new therapeutic targets and modalities. The NCATS Biomedical Data Translator project is working to…
Swarnavo Sarkar, Jayan Rammohan
Living cells process information about their environment through the central dogma processes of transcription and translation, which drive the cellular response to stimuli. Here, we study the transfer of information from environmental input to the transcript and protein expression levels. Evaluation of both…
Michaël Carl
Horizontal (automatic) and vertical (control) processes have been observed and reported for a long time in translation production. Schaeffer and Carl's Monitor Model integrates these two processes into one framework, assuming that priming mechanisms underlie horizontal/automatic processes, while vertical/monitoring…
Emma Tysinger, Brajesh Rai, Anton Sinitskiy
Meaningful exploration of the chemical space of druglike molecules in drug design is a highly challenging task due to a combinatorial explosion of possible modifications of molecules. In this work, we address this problem with transformer models, a type of machine learning (ML) model, with recent demonstrated success…
Michaël Carl
Over the past four decades, efforts have been made to develop and evaluate models for Empirical Translation Process Research (TPR), yet a comprehensive framework remains elusive. This article traces the evolution of empirical TPR within the CRITT TPR-DB tradition and proposes the Free Energy Principle (FEP) and Active…
Dimitris Gkoumas, Maria Liakata
The intersection of chemistry and Artificial Intelligence (AI) is an active area of research focused on accelerating scientific discovery. While using large language models (LLMs) with scientific modalities has shown potential, there are significant challenges to address, such as improving training efficiency and…
Zhonggang Sang
Translation is both an interpretive use of language and problem-solving activity. In his work, Ernst-August Gutt adopts a Relevance-Theoretic approach to unveil the inferential nature of translation as interpretive language use. He holds that in translating a translator aims to seek the interpretive resemblance between…
Wenyu Zhang, Mason Guy, Jerrica Yang, Lucy Hao + 5 more
Large Language Models (LLMs) have revolutionized numerous industries as well as accelerated scientific research. However, their application in planning and conducting experimental science, has been limited. In this study, we introduce an adaptable prompt-set with GPT-4, converting literature experimental procedures…
Mohammad Ibrahim Qani
translating words which do not have equivalent in target language is not easy and finding proper equivalent of those words are very important to render correctly and understandably, the article defines some thoughts and ideas of scientists on the common problems of non-equivalent words from English to Russian language…
S. S. Ho, R. E. Mills
The inundating rate of scientific publishing means every researcher will miss new discoveries from overwhelming saturation. To address this limitation, we employ natural language processing to overcome human limitations in reading, curation, and knowledge synthesis, with domain-specific applications to genetics and…