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src/
models/
dpa_model.py # DPA architecture (GLA + softmax router)
baselines.py # Transformer, pure linear, uniform hybrid baselines
router.py # Decision point router (learned binary classifier)
data/
agent_trajectory.py # Synthetic agent trajectory generator
decision_points.py # Decision point labeling & analysis
datasets.py # HotpotQA, GSM8K, ToolBench loaders
eval/
benchmark.py # Unified evaluation pipeline
metrics.py # Accuracy, FLOPs, latency, KV cache metrics
visualize.py # Publication figures
configs/
dpa_7b.yaml # 7B model config
dpa_72b.yaml # 72B model config (Merlin 8xH100)
scripts/
run_baseline.sh # Run all baselines
run_dpa.sh # Run DPA experiments
run_ablation.sh # Ablation studies
paper/
main.tex # NeurIPS 2026 LaTeX
results/ # Experiment outputs
figures/ # Generated plots1# 1. Install deps
2pip install -r requirements.txt
3
4# 2. Run trajectory analysis (no GPU needed)
5python src/data/decision_points.py
6
7# 3. Run attention simulation (CPU/MPS OK)
8python src/eval/benchmark.py --mode simulate
9
10# 4. Run full training (8xH100 on Merlin)
11bash scripts/run_dpa.sh