CSE5023: Recent Advances in Deep Learning
Assignment 1: Survey Paper on Foundation Models
1 Objective
The primary objective of this assignment is to delve into the realm of foundation models, specifically focusing on a direction that is intricately related to your own research. This task aims to foster a deeper understanding of the subject matter, encourage critical thinking, and stimulate original research ideas.
2 Requirements
2.1 Topic Selection
Choose a specific direction within the broader scope of foundation models that aligns closely with your research interests. This could be in the domain of AI for X, where X represents your particular research focus.
2.2 Content Structure
• Abstract: Provide a concise summary of the survey paper, outlining the main themes, findings, and contri- butions.
• Introduction: Introduce the topic, its relevance to your research, and the significance of foundation models in the chosen domain.
• Literature Review/Methods: Present a comprehensive review of existing literature related to the selected topic. Discuss various methods, techniques, and models that have been employed in previous studies.
• Discussion: Analyze the strengths and weaknesses of the current state-of-the-art, identify gaps in the research and discuss potential areas for improvement.
• Possible Further Directions: Propose novel research directions that could advance the field. These should be informed by your analysis and aligned with your research interests.
• Preliminary Experiments (Optional): If applicable, include results from any preliminary experiments or simulations that support your research directions.
2.3 Length and Formatting
• The survey paper must be a minimum of six pages long, excluding the references.
• Follow a standard academic formatting style, including proper citations and references.
2.4 Originality and Plagiarism Policy
• The survey must be entirely your own work. Direct copying from any source, including ChatGPT or its variants, is strictly prohibited.
• While you may use ChatGPT as a tool for refining language, the final content must be original and reflect your own research thoughts.
• Any instance of direct copying from ChatGPT or other sources will be treated as plagiarism.
• The consequences of plagiarism will be determined according to the rules and regulations of the department and the university.
3 Evaluation Criteria
The assignment will be marked out of 80 marks, with the following breakdown:
• Relevance to your research direction: 10 marks.
• Depth of literature review and understanding of methods: 15 marks.
• Quality of discussion and analysis: 15 marks.
• Originality of proposed further directions: 15 marks.
• Clarity of writing and presentation: 25 marks.
Additionally, the report will be evaluated for originality, contributing to a separate score of 20 marks.
4 Submission instructions
To ensure a smooth and organized submission process for Assignment 1, please adhere to the following detailed instructions.
4.1 Preparing Your Submission
• Compilation of Files:
• Gather all the necessary files related to Assignment 1, which should include both the LaTeX source files (zipped) and the compiled PDF document.
• Ensure that your LaTeX source files are well-organized and compiled without errors.
• Creation of ZIP Archive:
• Once you have all the files ready, create a ZIP archive to bundle them together.
• This can typically be done by right-clicking on the folder containing your files and selecting the “Com- press” or “Send to ZIP” option, depending on your operating system.
4.2 Naming the ZIP Archive
• Format:
• It is crucial to name the ZIP file in a specific format to facilitate easy identification.
• The file name should be structured as follows: studentnumber assignment1.zip.
• For instance, if your student number is 123456, the file name should be 123456 assignment1.zip.
• Any deviation from the specified format may result in delays or issues with the processing of your submission.
4.3 Submission Platform
Please submit the archive that includes all your files through Blackboard.
The deadline for assignment 1 (all parts and all tasks) is 25 May 2025 at 23:55 (Beijing Time).