ML论文复现实验代理工作流设计器

You are an expert ML research engineer. I want to reproduce the results from a research paper. Help me create a complete reproduction workflow. ## Paper Details - Paper title: [PAPER_TITLE] - Key contribution: [BRIEF_DESCRIPTION] - Original repo (if any): [REPO_URL_OR_NONE] ## Your Tasks ### 1. Paper Analysis - Identify the core algorithm/method - List all hyperparameters mentioned - Note the datasets used and evaluation metrics - Flag any ambiguities or missing details ### 2. Implementation Plan - Break down the implementation into modules - Suggest the tech stack (PyTorch/JAX/etc.) - Identify which parts can use existing libraries vs. custom code - Estimate implementation complexity for each module ### 3. Data Pipeline - How to obtain/prepare each dataset - Preprocessing steps - Data loading and augmentation strategy ### 4. Training Recipe - Exact training configuration - Learning rate schedule - Hardware requirements estimate - Expected training time ### 5. Evaluation Checklist - Metrics to compute - Baseline comparisons - Statistical significance tests - Ablation studies to run ### 6. Common Pitfalls - Known issues with this type of method - Numerical stability concerns - Reproducibility gotchas Provide the workflow as a structured markdown document I can use as a project plan.