Assessment of Post-Project Paper 4

Dear NN,

We have finished assessing your post-project paper.

Your grade for this deliverable is: 5

I have attached a more detailed assessment below.

Your paper was evaluated using the grading criteria specified on the course website (link). It was first assessed by one of the teaching assistants, and then an AI assistant provided a separate evaluation. I reviewed both of these assessments, resolved any differences between them, and combined them into a final evaluation. In writing the latter, I also took into account your self-assessment.

Please do not hesitate to reach out if you have any questions.

Best, Marco

Clarity

Your report provides a clear and well-organized account of the project. The structure is easy to follow, and your explanation of key concepts (such as the role of BERT, the evaluation setup, and the mitigation strategies) is generally accessible to readers with a background in AI and ML. You do a good job explaining the experimental workflow, and technical terminology is introduced appropriately. One area where the report could be further improved is in helping readers develop an intuition for the bias evaluation metrics (WEAT and SEAT). While you include the mathematical formulas and implementation details, a clearer explanation of why these metrics are useful and what a bias score actually tells us about a model would make your description more accessible to readers who are less familiar with fairness evaluation in NLP.

Critical Reflection

You reflect thoughtfully and in detail on how the project deepened your understanding of course topics and helped you explore areas beyond what was covered in class. Your discussion of the challenges you faced, such as the practical limits of gender swapping and the instability of adversarial debiasing, shows a clear and honest engagement with the difficulties of real-world NLP research. These reflections are grounded in your experience and well supported by relevant literature. You also demonstrate a good understanding of where course content provided a solid foundation and where additional independent research was needed.

Articulation of Learning

You clearly articulate what you learned from the project and how that learning happened, drawing direct connections to your practical experiences and literature research. You highlight key insights, such as the complexity of applying mitigation strategies and the difference between theoretical approaches and real-world implementations. What stands out here is your discussion of future work, which indirectly points out how your experience with bias mitigation strategies could inform the work of other researchers. You are more modest in your self-assessment here than your writing warrants: your report shows that you are not just able to use research literature effectively, but also able to draw meaningful conclusions from your work that are relevant to the field.

Effort and Care

Your report is well written, polished, and professionally presented. The structure is clear, your language is precise, and your references are consistently formatted. Technical terms are used accurately and integrated seamlessly into your writing. The effort you invested in writing, revising, and grounding your discussion in the literature is clearly evident.

Overall Assessment

The overall assessment of the report is: Grade 5

You have written an excellent post-project paper. It demonstrates clarity, depth of reflection, and a strong ability to engage critically with both course content and research literature. You show not only what you learned but also why it matters, both for your development and for the field of NLP more broadly.