# HW7: Experiments ## Writing * Write the Experiments section in your team overleaf project. * Recommended length: 100 - 200 lines (including tables and figures). * Submit the PDF version of your current draft up to the Experiments section. ## Rubric * **Data Section** (1 point) * Are the sources and choices of the datasets clearly explained and justified? * Is the data preprocessing pipeline well-documented (if any)? * Are the dataset characteristics adequately described? * **Data Split** (1 point) * Is the division of data into training/development/evaluation sets clearly specified? * Are the statistics for each data split comprehensively reported? * If using cross-validation, is the procedure properly explained? * **Model Descriptions** (2 points) * Are the models described with sufficient references to the approach section? * Are the differences between methods clearly distinguished? * Is there a clear connection between model design choices and research objectives? * **Evaluation Metrics** (2 points) * Are all evaluation metrics clearly defined with proper mathematical notation? * Is the choice of each metric well-justified? * Are the limitations of the chosen metrics discussed (if any)? * **Experimental Settings** (1 point) * Are the hyperparameters and implementation details fully specified? * Is the hardware/software environment clearly described? * Are the experiments documented in a way that enables replication? * **Model Development** (1 point) * Is the model development process clearly documented? * Are the key decisions and modifications during development explained? * Are the challenges encountered and their solutions discussed? * **Result Tables** (2 points) * Are the experimental results presented in well-formatted, readable tables? * Are all tables properly labeled with units and descriptions? * Are baseline as well as existing state-of-the-art comparisons included and clearly marked? * **Result Interpretations** (2 points) * Are the key findings from the results clearly identified and explained? * Are the strengths and weaknesses of the results discussed? * Are the implications of the results connected to the research questions? --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://emory.gitbook.io/ai-research-practicum/assignments/hw7-experiments.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.