Complete a focused experimental project on a generative AI system, worth 40% of the course grade. Aim for about 20 hours of work, including experiments and writing.
Use an existing model, library, or small simulator. Established methods are welcome; model training is optional. Your contribution should be a clear question, a meaningful implementation or modification, and evidence that answers the question.
| Topic | Example question |
|---|---|
| LLM question answering | Does retrieval improve answer accuracy? How does the amount of retrieved context affect the result? |
| Agent reliability | Does a verification or retry step improve task success, and at what cost in tool/model calls? |
| Multimodal generation | Does checking and revising a prompt improve object counts or spatial relations in generated images? |
Other course-related topics, including generative modeling and small world-model experiments, are welcome in the proposal.
The baseline, modified method, and ablation are enough. Well-supported negative results receive full credit.
You may build on a homework, but add a new question or substantive method change and fresh evaluation cases. Identify what is reused.
The report should cover the question, method, experiments, results, and limitations. Cite reused code/data and disclose AI assistance.
Problem and experimental design 20%; implementation 30%; evaluation and analysis 30%; report and reproducibility 20%.