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Final Exam

The Fall 2025 Final Exam serves as an assessment of the advanced generative architectures and language models presented in the second half of the semester. This exam is non-cumulative and will strictly cover material taught after the midterm exam.

Logistics

  • Date: Wednesday, ۸ بهمن ۱۴۰۴ (January 28, 2026)
  • Time: 09:00
  • Location: Department of Mathematical Sciences

Scope & Material

The exam covers Topic 9 through the end of the course. Please review the slides and notes for the following sections:

  1. Topic 9: Energy-Based Models
  2. Topic 10: Score-Based Models
  3. Topic 11: Flow Matching
  4. Topic 12: Diffusion Models
  5. Topic 13: Evaluation of Generative Models
  6. Topic 14: Parameter-Efficient Fine-Tuning (PEFT)
  7. Topic 15: Multi-Modal Models
  8. Large Language Models (LLMs) & Advanced Topics:
    • Large Language Models
    • Emergent Abilities & Reasoning
    • RLHF (Reinforcement Learning from Human Feedback) & RAG

Scope Note

Since this exam is not cumulative, we recommend focusing your study time entirely on the advanced architectures (e.g. Diffusion, Flow Matching) and the theoretical underpinnings of Large Language Models. While foundational knowledge from the first half of the course (e.g., probability, basic neural networks) is assumed, you will not be tested on specific pre-midterm architectures like VAEs, GANs, or Normalizing Flows.

Preparation Advice

The lecture slides cover the complete scope of the exam, including all necessary mathematical derivations. However, given the concise nature of the slides, we highly recommend consulting the Supplementary Material linked on the Course Material page. These resources provide the full context and narrative needed to gain a complete and deep understanding of the concepts presented in class.