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Large language models, which are often trained for hundreds of thousands of compute days, have shown remarkable capabilities for zero- and few-shot learning. Given their computational cost, these models are difficult to replicate without significant capital. For the few that are available through APIs, no access is granted to the full model weights, making them difficult to study. We present Open Pre-trained Transformers (OPT), a suite of decoder-only pre-trained transformers ranging from...
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The design of an automatic solver for mathematical word problems (MWPs) dates back to the early 1960s and regained booming attention in recent years, owing to revolutionary advances in deep learning. Its objective is to parse the human-readable word problems into machine-understandable logical expressions. The problem is challenging due to the existence of a substantial semantic gap. To a certain extent, MWPs have been recognized as good test beds to evaluate the intelligence level of agents...
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This study provided a content analysis of studies aiming to disclose how artificial intelligence (AI) has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers (74 studies) and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions...
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We present LDA*, a system that has been deployed in one of the largest Internet companies to fulfil their requirements of "topic modeling as an internal service" ---relying on thousands of machines, engineers in different sectors submit their data, some are as large as 1.8TB, to LDA* and get results back in hours. LDA* is motivated by the observation that none of the existing topic modeling systems is robust enough ---Each of these...
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In recent years, led by the wave of artificial intelligence, “artificial intelligence + education” has become a very hot topic. More and more traditional educational institutions have begun to organize and layout the field of ARTIFICIAL intelligence education. Training artificial intelligence talents will become an important mission of education. Meanwhile, educational methods will change with the development of artificial intelligence, and the deep integration of artificial intelligence and...
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Emerging tools bring forth fresh approaches to work, and the field of natural science is no different. In natural science, traditional manual, serial, and labour-intensive work is being augmented by automated, parallel, and iterative processes driven by artificial intelligence-based experimental automation and more. To add new capabilities in natural science, enabling the acceleration and enrichment of automation of the discovery process, we present DARWIN, a series of tailored LLMs for...
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Literature reviews establish the foundation of academic inquires. However, in the planning field, we lack rigorous systematic reviews. In this article, through a systematic search on the methodology of literature review, we categorize a typology of literature reviews, discuss steps in conducting a systematic literature review, and provide suggestions on how to enhance rigor in literature reviews in planning education and research.
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Research Guides: AI-Based Literature Review Tools: Home
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The twenty-first century has brought with it a growing variety of authentic and engaging learning environments. While significant portions of human learning still take place in traditional classrooms, researchers and educators have innovated several learning experiences that are embodied, project-based, inquiry-driven, collaborative, and open-ended. Furthermore, there has been greater acknowledgement of the varying timescales and contexts where meaningful learning takes place, as well as...
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Artificial intelligence (AI) plays an increasingly prevalent role in the global education system. However, there is a lack of transparency about how AI technologies work alongside certain ethical guidelines. Achieving the global benefits of AI-driven learning and education requires international dialogue on the commonplaces of ethical considerations. This paper, taking China and Finland as two contextual cases, analyzes how AI-related policies at the national level have focused on...
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Background Automated approaches to improve the efficiency of systematic reviews are greatly needed. When testing any of these approaches, the criterion standard of comparison (gold standard) is usually human reviewers. Yet, human reviewers make errors in inclusion and exclusion of references. Objectives To determine citation false inclusion and false exclusion rates during abstract screening by pairs of independent reviewers. These rates can help in designing, testing and implementing...
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