Paper Implementation

Input

Require arxiv link (not PDF). Fetch LaTeX: https://arxiv.org/e-print/XXXX.XXXXX (.tar.gz with .tex files)

Phases

1. Discovery

Parse LaTeX for: architecture, algorithms, hyperparameters, loss functions, datasets. Search existing GitHub implementations. Note ambiguities.

Gather: Scope (train/inference/finetune)? Scale (model size, compute)? Baseline codebase? Priority (accuracy/speed/memory)? Validation method?

2. Verification

If repo exists: audit against LaTeX source. Check architecture, hyperparameters, training procedure. Identify discrepancies.

3. Refinement

Present findings, ask questions, iterate until execution steps are perfectly clear.

4. Implementation

Build/modify code. Write correctness tests. Profile performance.

5. Optimization (optional)

Profile with nsight-systems/torch.profiler. Write custom CUDA/Triton kernels. Benchmark with measurements.

Compute Strategy

• Local 3090: quick tests, debugging, small validation
• VP H100s: training runs, large experiments (ask before provisioning)

On arxiv link

1. Parse LaTeX source
2. Search existing implementations
3. Present structured questions
4. Wait for answers, refine, then proceed autonomously