Synthesis of reviewer comments (concise):
- Positive: novelty of model architecture and promising empirical gains on target tasks.
- Concerns: reproducibility due to proprietary dataset and missing hyperparameter details; need for clearer baseline selection and statistical significance; insufficient ablation studies isolating components; limited discussion of failure modes, compute cost, and ethical considerations.
- Requests: additional analyses (robustness, cross-domain eval), clearer methodology, and transparency about what can be shared.
Suggested public response structure:
- Opening gratitude and high-level summary of revisions.
- Brief synthesis of major issues raised.
- Point-by-point responses organized by theme:
- Reproducibility & data confidentiality (what is shared vs withheld)
- Hyperparameters & training protocol (non-sensitive summary and reproducible recipe)
- Baselines, metrics, and statistical significance
- Ablations and component analyses
- Robustness, compute cost, and ethical/failure-mode discussion
- Non-sensitive additional experiments planned or performed.
- How readers can reproduce core findings (code, synthetic data, model checkpoints if possible).
- Invitation for follow-up and contact for limited-access collaboration.
- Closing appreciation.
Three sample sentences for the public reply:
- Acknowledgement: "We thank the reviewers for highlighting the model's strengths and for constructive concerns regarding reproducibility, baseline comparisons, and deeper ablation—these points helped us prioritize additional analyses."
- Objective rebuttal summary: "To address reproducibility while preserving proprietary constraints, we provide an exhaustive, non-sensitive training recipe, open-source the model implementation and synthetic evaluation datasets, and report confidence intervals showing the improvements remain statistically significant across five seeds."
- Non-sensitive next steps/additional analyses: "As next steps we will add targeted robustness tests (domain-shift and noise perturbations), expanded ablation studies that isolate each architectural component, and a computational-cost appendix; we also welcome vetted collaborations to enable restricted access to the original dataset under agreed terms."
