# Reproduction Bundle

Paper: Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System

OpenReview: https://openreview.net/forum?id=LTHHiPNbrs  
arXiv: https://arxiv.org/abs/2406.04374  
HF Job smoke check: https://huggingface.co/jobs/Srishti280992/6a5d7cc4bee6ee1cf4ed1c32

## Contents

- `rcb/`: RCB implementation from the paper pseudocode.
- `scripts/`: theorem checks, mechanism checks, synthetic runs, warfarin runs, and figure generation.
- `data/`: IWPC/PharmGKB warfarin data used by the local pipeline.
- `outputs/`: JSON and logs from the reproduced runs.
- `figs/`: Plotly HTML figures and CSV backing data.
- `poster.html`, `poster_embed.html`, `poster_preview.png`, `GATE_REPORT.json`: Posterly poster and gate report.

## Rerun

```bash
pip install numpy pandas scikit-learn plotly xlrd

python scripts/theory_checks.py
python scripts/claim3_structure.py
python scripts/regret_rate_fit.py --seeds 5 --workers 10 --out outputs/claim1_rate.json
python scripts/run_synthetic.py --only s3 --out outputs/syn_s3.json
python scripts/run_synthetic.py --only feas --out outputs/feas.json
python scripts/run_warfarin.py --C_N 1.0 --N 5 --reward binary --EF theory --phi0 1.0 --perms 10 --out outputs/warfarin.json
python scripts/warfarin_ablation.py --perms 5 --out outputs/warfarin_ablation.json
python scripts/figures.py rate rate_Kd warfarin warfarin_ablation warfarin_N feasibility Neps tradeoff gain
```

The scripts `chdir` to the bundle root, so run them from this directory or from any parent path.