ML Conference Appendices Growing Too Long?
💡Debate on ML paper appendices reshaping conference standards—key for submitters.
⚡ 30-Second TL;DR
What Changed
Appendices in top ML conferences like ICML and NeurIPS are expanding significantly
Why It Matters
This trend may overburden reviewers and push comprehensive work to journals, altering ML publication norms.
What To Do Next
Comment on the r/MachineLearning thread to share your appendix experiences.
Key Points
- •Appendices in top ML conferences like ICML and NeurIPS are expanding significantly
- •Reviewers push for extensive experiments that don't fit main 8-10 page limits
- •Debate on whether appendices should remain non-essential supplementary material
🧠 Deep Insight
AI-generated analysis for this event — not the original article.
🔑 Enhanced Key Takeaways
- •The 'appendix bloat' phenomenon is exacerbated by the 'reproducibility crisis' in AI, where reviewers increasingly mandate comprehensive ablation studies and hyperparameter sensitivity analyses that were previously considered optional.
- •Major conferences like NeurIPS have experimented with 'unlimited' appendix policies to encourage transparency, but this has inadvertently incentivized authors to move core proofs and critical architecture details out of the main paper to bypass strict page limits.
- •The academic community is actively debating a shift toward 'living papers' or modular submission formats, where the main paper serves as a summary and the appendix acts as a version-controlled, searchable repository of technical artifacts.
🔮 Future ImplicationsAI analysis grounded in cited sources
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Original source: Reddit r/MachineLearning ↗
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