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, decision-making processes, and even democratic institutions. Large language models (LLMs) have shown tremendous potential in natural language understanding and generation. This research aims to harness
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation models, such as ChatGPT and GPT4, incorporating the cutting-edge techniques in the other areas,...
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Ryvka and Mordechai Lewin Yiddish Language Travel Grant This grant is awarded to the highest achieving student enrolled in an approved Yiddish intensive language course at an overseas institution
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language models (LLMs) to address these challenges by developing a comprehensive framework that seamlessly integrates LLM capabilities for generating accurate and optimised code, constructing complex SQL
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an honours degree in Japanese studies or Asian studies in the School of Languages, Cultures and Linguistics in the Faculty of Arts at a Monash campus in Australia. Conducting research in Japan as part of
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. This is a challenging problem as it spans a wide range of topic and contextual domains. Moreover, such language processing must deal with slang, foreign words and passages, localised dialects, unpredictably
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'. Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities
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at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders
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to address the Key Selection Criteria. Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them