Dataset card

README.md

@@ -1,3 +1,50 @@
 ---
-license: mit
+license: cc-by-4.0
+pretty_name: What Arranges Features in Activation Space? (checkpoints and analysis)
+tags:
+  - interpretability
+  - computational-mechanics
+  - belief-states
 ---
+
+# What Arranges Features in Activation Space? Checkpoints and analysis outputs
+
+Trained checkpoints and pre-computed analysis outputs for the NeurIPS 2026 paper
+"What Arranges Features in Activation Space? Non-Classical Predictive Geometry in Next-Token
+Predictors" (arXiv:2507.07432). Code: https://github.com/adamimos/what-arranges-features.
+
+The original single-seed (seed 42) models used for the geometry panels of Fig. 2, Fig. 3 and
+the RSA figure are in a separate dataset,
+[`SimplexAI/quantum-representations`](https://huggingface.co/datasets/SimplexAI/quantum-representations).
+
+> **Upload in progress (November 2026).** The files listed below are being uploaded; until then only this card is present.
+
+## Layout
+
+Download into the root of the code repository (see its README); paths match what the scripts
+expect.
+
+| Path | Contents |
+|---|---|
+| `results/multiseed_{bloch,mess3,moon,frdn}_transformer/` | 5 seeds (0, 1, 2, 3, 42) x transformer |
+| `results/multiseed_{bloch,stage2,frdn}_rnn/` | 5 seeds x LSTM / GRU / vanilla RNN (`stage2` = Mess3 and Moon) |
+| `results/qrrxor_robust_{transformer,lstm,gru,rnn}/` | qRRXOR, 5 report seeds (42, 123, 456, 789, 1000) |
+| `results/20260424220339/`, `results/20260504050111_lstm_b64_full/` | qRRXOR transformer and LSTM shown in Fig. 4 |
+| `results/20260503215800_lstm_default_cpu/` | qRRXOR LSTM at lr 1e-4 / batch 16 (comparison runs) |
+| `results/paper_metrics/` | Fig. 2 and appendix bar metrics, order-k loss, PCA views |
+| `results/*.csv`, `results/causal_transplant/`, `results/heldout_suffix/` | scores behind the paper's numbers, including the scores (not the checkpoints) of the qRRXOR hyperparameter screen (dev seeds 7, 11, 13) |
+| `shuffle_results_quantum_rrxor_hero_3seed/`, `figures/beyond_ntp/` | cached curves read by the Fig. 4 script |
+
+Each run directory `run_<i>_.../` holds a checkpoint every 100 epochs, named by tokens seen
+(`0.pt` is the untrained network), plus `loss.csv`, `log.csv`, `log.json`, and the run config
+(`run_config.yaml`, and `hooked_model_config.json` or `model_config.json`). Each sweep
+directory has the `sweep_config.yaml` it was launched from.
+
+## Notes
+
+- A run counts as converged when the last `val_loss_mean` in `loss.csv` (normalized by the
+  optimal loss) is below 1.005. All runs in the core dataset converge except some seeds of
+  `20260503215800_lstm_default_cpu`, which are included for that comparison.
+- The shuffle columns of `qrrxor_robust_scores.csv` and `qrrxor_robust_grurnn_scores*.csv`
+  come from a single no-PCA shuffle and are not the paper's numbers; the paper's shuffle
+  results are in `qrrxor_shuffle_null_analysis.csv`.