Rename simulation scripts to descriptive names
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@@ -227,14 +227,14 @@ evaluation uses 150-200 Monte Carlo batches of 64 per point.
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`simulation/semantic_correlation_sim.py` with the trained decoder-only
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overlay from `simulation/maml_semantic.py --decoder_only`; threshold
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sweep tau in [0.30,0.50] and the mean-cosine comparison in
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`simulation/revision_experiments.py`.
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- **beta sweep** (monotone gain law): `simulation/revision_betasweep.py`
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`simulation/threshold_phase_study.py`.
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- **beta sweep** (monotone gain law): `simulation/betasweep.py`
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(figure `fig/fig4_beta_sweep.pdf`).
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- **Attention heatmaps**: `simulation/plot_figures.py`
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(figure `fig/fig6_hlm.pdf`).
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- **Hyperparameter studies** (S, lambda, d, H, K):
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`simulation/revision_ablation.py`, `simulation/revision_dsweep.py`,
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`simulation/revision_e2e.py`.
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`simulation/ablation_hks.py`, `simulation/dsweep.py`,
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`simulation/e2e_check.py`.
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- **Real-data study** (manuscript Fig. 5): UCI optical-recognition digits
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(8x8=64 dimensions), `simulation/revision_realdata_train.py` +
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`simulation/revision_realdata_plot.py`.
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(8x8=64 dimensions), `simulation/realdata_train.py` +
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`simulation/realdata_plot.py`.
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