2,747 research outputs found

    Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers

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    Multilingual Large Language Models are capable of using powerful Large Language Models to handle and respond to queries in multiple languages, which achieves remarkable success in multilingual natural language processing tasks. Despite these breakthroughs, there still remains a lack of a comprehensive survey to summarize existing approaches and recent developments in this field. To this end, in this paper, we present a thorough review and provide a unified perspective to summarize the recent progress as well as emerging trends in multilingual large language models (MLLMs) literature. The contributions of this paper can be summarized: (1) First survey: to our knowledge, we take the first step and present a thorough review in MLLMs research field according to multi-lingual alignment; (2) New taxonomy: we offer a new and unified perspective to summarize the current progress of MLLMs; (3) New frontiers: we highlight several emerging frontiers and discuss the corresponding challenges; (4) Abundant resources: we collect abundant open-source resources, including relevant papers, data corpora, and leaderboards. We hope our work can provide the community with quick access and spur breakthrough research in MLLMs

    Chapter 6: Culture and Ethics

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    The OTiS (Online Teaching in Scotland) programme, run by the now defunct Scotcit programme, ran an International e-Workshop on Developing Online Tutoring Skills which was held between 8–12 May 2000. It was organised by Heriot–Watt University, Edinburgh and The Robert Gordon University, Aberdeen, UK. Out of this workshop came the seminal Online Tutoring E-Book, a generic primer on e-learning pedagogy and methodology, full of practical implementation guidelines. Although the Scotcit programme ended some years ago, the E-Book has been copied to the SONET site as a series of PDF files, which are now available via the ALT Open Access Repository. The editor, Carol Higgison, is currently working in e-learning at the University of Bradford (see her staff profile) and is the Chair of the Association for Learning Technology (ALT)

    Decoding the Diversity: A Review of the Indic AI Research Landscape

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    This review paper provides a comprehensive overview of large language model (LLM) research directions within Indic languages. Indic languages are those spoken in the Indian subcontinent, including India, Pakistan, Bangladesh, Sri Lanka, Nepal, and Bhutan, among others. These languages have a rich cultural and linguistic heritage and are spoken by over 1.5 billion people worldwide. With the tremendous market potential and growing demand for natural language processing (NLP) based applications in diverse languages, generative applications for Indic languages pose unique challenges and opportunities for research. Our paper deep dives into the recent advancements in Indic generative modeling, contributing with a taxonomy of research directions, tabulating 84 recent publications. Research directions surveyed in this paper include LLM development, fine-tuning existing LLMs, development of corpora, benchmarking and evaluation, as well as publications around specific techniques, tools, and applications. We found that researchers across the publications emphasize the challenges associated with limited data availability, lack of standardization, and the peculiar linguistic complexities of Indic languages. This work aims to serve as a valuable resource for researchers and practitioners working in the field of NLP, particularly those focused on Indic languages, and contributes to the development of more accurate and efficient LLM applications for these languages.Comment: 27 pages, 1 figur

    A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4

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    Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit special abilities which allow them to achieve remarkable performances without any task-specific training in many of the natural language processing tasks. The era of LLMs started with OpenAI GPT-3 model, and the popularity of LLMs is increasing exponentially after the introduction of models like ChatGPT and GPT4. We refer to GPT-3 and its successor OpenAI models, including ChatGPT and GPT4, as GPT-3 family large language models (GLLMs). With the ever-rising popularity of GLLMs, especially in the research community, there is a strong need for a comprehensive survey which summarizes the recent research progress in multiple dimensions and can guide the research community with insightful future research directions. We start the survey paper with foundation concepts like transformers, transfer learning, self-supervised learning, pretrained language models and large language models. We then present a brief overview of GLLMs and discuss the performances of GLLMs in various downstream tasks, specific domains and multiple languages. We also discuss the data labelling and data augmentation abilities of GLLMs, the robustness of GLLMs, the effectiveness of GLLMs as evaluators, and finally, conclude with multiple insightful future research directions. To summarize, this comprehensive survey paper will serve as a good resource for both academic and industry people to stay updated with the latest research related to GPT-3 family large language models.Comment: Preprint under review, 58 page

    Frameworks for the management of cross-cultural communication and business performance in the globalizing economy: a professional service TNC case study in Indonesia

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    Globalization increases the integration and interdependence of international, national and local business and stakeholder communities across economic, political and cultural spheres. Communication technology and the international role for English suggest the integrating global communication reality is simplifying. Experience indicates integration produces complex heterogeneous dialogue and asymmetrical relationships with no shared interpretative systems. The global/national/local nexus presents management with universal and particular paradoxes mediated through diverse contextual micro communication practices and behaviours. This thesis derives from a professional service (environmental engineering) TNC request for help to address the business communication and performance concerns implicated in the production of professional bi-lingual English and Indonesian reports for clients. At the heart of this corporate concern lie the multicultural nature of interactions between the individuals, organizations and wider stakeholders involved in the Jakarta, Indonesian branch office operations. A developing nation adds further complexity. This thesis contends that these micro organizational concerns link to critical macro economic, political, and cultural societal concerns for the development of more responsive ethical and sustainable management and governance. This thesis argues for an elevated notion of the role of communication management to enable business to pursue more sustainable goals, improve business performance, and address the issue of risk. The thesis reviews multidisciplinary literature to develop a multifaceted theoretical framework that links macro management issues to this micro contextual concern.This framework guides a qualitative research strategy to apply an ethnographic-oriented case study-based methodology to map the diverse worldviews of a sample of the Indonesian professional staff, their local senior expatriate management, and Headquarters. The case study assesses the impact of diverse worldviews on the interactions, relationships and performances involved in a specific project involving the international investment sector, a national proponent developer, the national regulatory agency, local and indigenous stakeholder communities and the consulting TNC. The findings have implications for the management of international business, the higher education sector and civil society organizations

    Tackling Hate Speech in Low-resource Languages with Context Experts

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    Given Myanmars historical and socio-political context, hate speech spread on social media has escalated into offline unrest and violence. This paper presents findings from our remote study on the automatic detection of hate speech online in Myanmar. We argue that effectively addressing this problem will require community-based approaches that combine the knowledge of context experts with machine learning tools that can analyze the vast amount of data produced. To this end, we develop a systematic process to facilitate this collaboration covering key aspects of data collection, annotation, and model validation strategies. We highlight challenges in this area stemming from small and imbalanced datasets, the need to balance non-glamorous data work and stakeholder priorities, and closed data-sharing practices. Stemming from these findings, we discuss avenues for further work in developing and deploying hate speech detection systems for low-resource languages.Comment: ICTD 2022 Conference pape

    Chapter 5 The future of inclusive innovation

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    "Innovation offers potential: to cure diseases, to better connect people, and to make the way we live and work more efficient and enjoyable. At the same time, innovation can fuel inequality, decimate livelihoods, and harm mental health. This book contends that inclusive innovation – innovation motivated by environmental and social aims – is able to uplift the benefits of innovation while reducing its harms. The book provides accessible engagement with inclusive innovation happening at the grassroots level through to policy arenas, with a focus on the South-East Asian region. Focusing on fundamental questions underpinning innovation, in terms of how, what and where, it argues that inclusive innovation has social processes and low-tech solutions as essential means of driving innovation, and that environmental concerns must be considered alongside societal aims. The book's understanding of inclusive innovation posits that marginalized or underrepresented innovators are empowered to include themselves by solving a problem that they are experiencing. The first in-depth exploration of efforts underway to assuage inequality from policy, private sector, and grassroots perspectives, this book will interest researchers in the areas of innovation studies, political economy, and development studies.

    Interrogating the Liberal Peace in East Timor

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    Peace operations from the 1990s have increasingly been driven by the assumption that conflict and social unrest can be ‘solved’ through the establishment and support of liberal structures. Known academically as liberal peace, this approach advocates the liberalisation of politics and economics, and the establishment of rule of law and international human rights norms, claiming such liberal structures offer the necessary foundation to lasting peace. This claim has become unquestioned logic for many of the international bodies and individual actors that participate in the peace industry and has led to a standardised approach to post-conflict situations. However, is this “peacebuilding consensus” justified? Does liberal peace foster sustainable peace? This thesis interrogates the concept and application of liberal peace to assess the extent to which liberal peacebuilding delivers on its claims and provides the foundations of sustainable peace. Due to the enormous size of such a project and the limitations of this thesis, I focus on one case study in my analysis of the liberal peace approach – East Timor. Relying on a single example of peacebuilding allows for a more in depth discussion of efforts, however, it is insufficient to draw broader conclusions about liberal peace. This body of research, therefore, is intended to contribute to existing academic work that evaluates liberal peace. Where this thesis deviates from existing research, however, is in the application of an immanent critique to assess liberal peacebuilding in East Timor..
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