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27 Mar 2024: Wan Yin Lim PhD student   Current situation Member of Chinese Annual Conference (CAC), Methodist Church of Malaysia   Subject Peacebuilding in Malaysia: An Interdisciplinary Examination of Chinese Methodist Peace Theology and Peace Studies &#xa0

30 Nov 2023: LIONEL D. SMITH __________________________________________________________________. Faculty of Law, University of Cambridge 10 West Road, Cambridge UK CB3 9DZ. Fellow of Gonville and Caius College, Cambridge CB2 1TA Telephone: ( 44) 01223 330079. lionel.smith@law.cam.ac.uk. EMPLOYMENT. 2022 – 2017-2023 2000-2022 2013-2016. Downing Professor of the Laws of England Faculty of Law, University of Cambridge Fellow, Gonville and Caius College, Cambridge Director, Cambridge Private Law Centre Courses taught: Equity (undergraduate level); Restitution, Advanced Private Law, English, Comparative and Transnational Secured Transactions Law (postgraduate level). Visiting Professor, Faculty of Law, University of Oxford. Courses taught: Trusts, Land Law (undergraduate level); Advanced Property and Trusts, Restitution (postgraduate level). Professor, Faculty of Law, McGill University. Full Professor (2007-2022); Sir William C. Macdonald Professor of Law (2014-2022); James McGill Professor of Law (2004-2014); Associate Professor (2000-2007); William Dawson Scholar in Law (2003-2004). 2007-2014: Director, Paul-André Crépeau Centre for Private and Comparative Law (until 2012, the Quebec Research Centre of Private and Comparative Law). 2001-2004:

4 Dec 2023: A1-1 A1-2 A2-1 A2-2 B1 B2 C1 C2. 聞く. 身近な場面でよく使われ. る基本的な語句がわかる。. 限られた範囲であれば、自. 分の専門分野でよく使わ. れる語句がわかる。. 身近な場面でよく使われ. る簡単な表現がわかる。. 自分の専門分野で必要な. 基本的な語句や表現が. わかる。. 日常的な話題について短. くはっきり話されれば、. 大切なポイントを聞き取. ることができる。. 日常のコミュニケーショ. ンでよく使われる表現が. わかる。自分の専門分野. でよく使われる語句を. 含む簡単な指示や説明が. わかる。. よく知っている話題なら、メ. ディア（音声メディア・テレ. ビ・動画など）から、主な内容. やデータを推測しながら聞き. 取ることができる。自分の専. 門分野でよく耳にする指示や. 説明がだいたいわかる。. 自分の専門分野の話題につい. て、構成がまとまっていれば. 理解できる。特定のポイント. を聞き分け、示すことができ. る。メディア（動画・講義・ウ. ェビナーなど）から、主要な事.

21 Nov 2023: Multilingual Models in Neural MachineTranslation. Guangyu Yang. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Clare Hall August 2023. Dedicated to my loving parents. Declaration. I, Guangyu Yang of Clare Hall, being a candidate for the MPhil in Machine Learning andMachine Intelligence, hereby declare that this report and the work described in it are my ownwork, unaided except as may be specified below, and that the report does not contain materialthat has already been used to any substantial extent for a comparable purpose. All software used in this thesis was written in Python and PyTorch. The open-sourceHugging Face transformers library1 [47] was used for downloading pre-trained models andinference. The sacreBLEU library2 [26] was used to download datasets and evaluate theperformance of the models using the BLEU metric. The BLEURT library3 [34] was used toevaluate the performance of the models using the BLEURT metric. The OpenICL frameworkwas used to experiment with in-context learning. And the Direct Preference Optimizationcodebase4 [28] was used for unsupervised preference optimization with MBR. The

24 Nov 2023: Multilingual Models in Neural MachineTranslation. Guangyu Yang. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofMaster of Philosophy in Machine Learning and Machine Intelligence. Clare Hall August 2023. Dedicated to my loving parents. Declaration. I, Guangyu Yang of Clare Hall, being a candidate for the MPhil in Machine Learning andMachine Intelligence, hereby declare that this report and the work described in it are my ownwork, unaided except as may be specified below, and that the report does not contain materialthat has already been used to any substantial extent for a comparable purpose. All software used in this thesis was written in Python and PyTorch. The open-sourceHugging Face transformers library1 [47] was used for downloading pre-trained models andinference. The sacreBLEU library2 [26] was used to download datasets and evaluate theperformance of the models using the BLEU metric. The BLEURT library3 [34] was used toevaluate the performance of the models using the BLEURT metric. The OpenICL frameworkwas used to experiment with in-context learning. And the Direct Preference Optimizationcodebase4 [28] was used for unsupervised preference optimization with MBR. The