Ying-Jia Lin

Academic Paper Writing in Artificial Intelligence (2026 Fall)

· Ying-Jia Lin

Welcome to the course page of Academic Paper Writing in Artificial Intelligence 🎓
This is a graduate course offered by the Graduate Institute of Artificial Intelligence, Chang Gung University. The course is taught in English.

Course Information

  • Instructor: Ying-Jia Lin, Assistant Professor (Department of Artificial Intelligence, Chang Gung University)
  • Department: Graduate Institute of Artificial Intelligence
  • Level: Graduate
  • Language: English
  • Course Code: AID008
  • Serial No.: A3469
  • Credits: 3
  • Class Schedule: Thursday 09:10–12:00 (every week)
  • Classroom: C0104R
  • Website: CGU E-Learning system
  • Before Enrolling: Please get your advisor’s approval and upload it to E-Learning by Sep. 17th.

Course Description

This course adopts a dual approach combining reverse-order writing instruction with hands-on, section-by-section practice. Rather than following the conventional reading order of a paper, the course progresses from concrete to abstract sections based on their ease of entry into the writing process. Students will begin with the Experimental Setup and then complete the Main Results, Ablation Studies, Discussion, Method, Related Work, Introduction, and Abstract. By drafting one section each week, students will gradually develop a complete research paper by the end of the semester.

The course also covers practical skills specific to AI research writing, including model architecture diagrams, experimental result visualization, LaTeX and BibTeX, peer review, rebuttal writing, and the ethical use of LLM-assisted writing tools. Each class will typically include a 30–60-minute lecture introducing key concepts and examples, followed by 50–75 minutes of hands-on practice. Students are therefore encouraged to bring materials from their own research, such as data, figures, and experimental results, to class.

Course Objectives

By the end of this course, students will be able to:

  1. Write a complete English AI research paper suitable for top-tier conferences or journals.
  2. Apply appropriate structure, logic, and academic language to each paper section.
  3. Create effective figures, tables, and captions using LaTeX and BibTeX.
  4. Use LLM tools responsibly while maintaining academic integrity and authorial agency.

Teaching Methods

  1. Instructor-led instruction and demonstrations: The instructor will explain key principles and strategies for writing AI research papers using published examples.
  2. Guided in-class writing practice: Students will apply the concepts through paper analysis, revision exercises, and section drafting.
  3. Individualized feedback: Students will complete writing assignments and receive individualized feedback to progressively develop a complete research paper.

Course mode. Each week:

  1. Short lecture
  2. In-class writing: this week’s new section, and revise last week’s draft according to the teacher’s feedback (submit in class or by 23:59 on the same day)
  3. Individual guidance
  4. Feedback from the instructor after class

No homework: all the writing happens in class. If you cannot finish in class, submit by 23:59 on the same day (no more delay) and you still get the full score. There are no quizzes or exams in this course.

Syllabus

Week Date Topic LaTeX Note
1 9/10 Course Introduction, How to write your paper title? LaTeX environment (env)
2 9/17 Datasets BibTeX, table env
3 9/24 Evaluation Metrics, Baselines \citet & \citep
4 10/1 Paper Figures: Method Overview (including captions) figure env & caption Diagramming
5 10/8 Method Section (I): Problem Formulation and Model Architecture Math symbols
6 10/15 Method Section (II): Algorithms, Loss Functions, and Training Details Equations
7 10/22 How to Write Related Work (Literature Review) BibTeX (clean)
8 10/29 Results Section (I): Tables (including captions) table env, \ref
9 11/5 Results Section (II): Figures (including captions) figure/subfigure env, \ref
10 11/12 How to Write Discussion
11 11/19 Abstract and Title (more formal than the first week)
12 11/26 Introduction (I): Motivation and Problem Statement
13 12/3 Introduction (II): Contributions and Paper Organization \begin{enumerate}, \ref
14 12/10 Paper Optimization
15 12/17 Academic Writing with AI
16 12/24 Final Paper Presentation and Discussions Presentation

W1–W14: we do not use AI. Once we know how to write, we can steer AI to help us write.

Grading

  • In-class writing activities and participation: 15% (1% for each week)
    • You can get the scores if you come and write.
  • Weekly section drafts and revisions: 60% (4% for each week)
    • This week’s draft is evaluated by the teacher based on its quality (3% / 2% / 1%). Correctly revising it next week earns 1% more. Not received: 0%.
  • Final Paper Presentation and Discussions (W16): 25%
    • Oral presentation (60 min, 15%): present the biggest changes in your paper writing during this semester.
    • Peer review (50 min, 10%): read your classmates’ papers in class and check whether the paper contains the essential elements you learned in this course.

Textbook and References