# Paper Submission Checklist

Based on NeurIPS/ICML/ACL reproducibility requirements.

## 📄 Paper Content

### Abstract & Introduction
- [ ] Clear problem statement
- [ ] Concrete contributions (numbered list)
- [ ] Scope and limitations stated upfront

### Related Work
- [ ] RAG systems comparison (LlamaIndex, LangChain, etc.)
- [ ] Context management literature
- [ ] Enterprise AI deployment challenges
- [ ] Temporal/decay-based retrieval

### Method
- [ ] Architecture diagram
- [ ] Algorithm pseudocode for key components
- [ ] Complexity analysis
- [ ] Design decisions justified

### Experiments
- [ ] Datasets described (ours + public)
- [ ] Baselines clearly defined
- [ ] Metrics explained
- [ ] Statistical significance tests
- [ ] Ablation studies for each component

### Results
- [ ] Tables with confidence intervals
- [ ] Qualitative examples
- [ ] Failure case analysis
- [ ] Computational cost comparison

## 🔬 Reproducibility

### Code
- [x] Code publicly available (GitHub)
- [x] MIT License
- [x] Installation instructions (pip install)
- [x] Docker support
- [ ] Exact dependency versions pinned
- [ ] Random seeds documented

### Data
- [x] Dataset publicly available (Hugging Face)
- [x] Dataset card with documentation
- [ ] Data preprocessing scripts
- [ ] Train/test splits specified

### Experiments
- [ ] Hyperparameters documented
- [ ] Hardware requirements specified
- [ ] Runtime estimates provided
- [ ] Scripts to reproduce all tables/figures

## 📊 Figures & Tables

### Required Figures
- [ ] Fig 1: System architecture overview
- [ ] Fig 2: Context Triad visualization
- [ ] Fig 3: Structure-aware indexing example
- [ ] Fig 4: Benchmark results comparison

### Required Tables
- [ ] Table 1: Comparison with baselines
- [ ] Table 2: Ablation study results
- [ ] Table 3: Computational efficiency
- [ ] Table 4: Dataset statistics

## 📝 Writing Quality

- [ ] Proofread for grammar/typos
- [ ] Consistent terminology throughout
- [ ] All acronyms defined on first use
- [ ] References properly formatted
- [ ] Page limit respected
- [ ] Anonymous for review (if required)

## 🤖 AI Disclosure

- [x] LLM_DISCLOSURE.md prepared
- [ ] Disclosure statement in paper (if required by venue)
- [ ] AI-assisted sections documented

## 📦 Supplementary Materials

- [ ] Extended proofs (if any)
- [ ] Additional experiments
- [ ] Full hyperparameter tables
- [ ] More qualitative examples
- [ ] Video demo (optional)

## 🚀 Final Submission

- [ ] PDF compiles without errors
- [ ] All figures render correctly
- [ ] Supplementary ZIP prepared
- [ ] Code repository cleaned
- [ ] Dataset finalized
- [ ] Co-author approvals obtained
