artifact_id stringlengths 9 55 | category stringclasses 2
values | format stringclasses 3
values | path stringlengths 9 52 | sanitized bool 1
class | sha256 stringlengths 64 64 | size_bytes int64 425 384k |
|---|---|---|---|---|---|---|
CITATION_bib | metadata | bib | CITATION.bib | true | 4c3c90e3a7732e2d662952081b29a55affc17da70e3e3039b7c182a1ac4c1e7f | 425 |
README_md | metadata | md | README.md | true | 43bd8db223ad69e0bae67ee356d5010d89a468162d33765ff1084213e79e08ed | 3,184 |
results__activation_analysis_json | result_artifact | json | results/activation_analysis.json | true | d9b7e962cf7f075119968651e0a856ca73b7228a1a283f8b68d7d4fda3cdd232 | 1,618 |
results__alpha_sweep_json | result_artifact | json | results/alpha_sweep.json | true | 038699ec0852c48221aa62796c998c38928bddba245fe12386799634425bbf0e | 1,014 |
results__convergence_10k_json | result_artifact | json | results/convergence_10k.json | true | 9d721c4ff939d5955e5b886235c4fd1841b3c3e6bf61b40440a5a6d7474f6942 | 1,740 |
results__full__activation_rank_v1__aggregate_json | result_artifact | json | results/full/activation_rank_v1/aggregate.json | true | 9d92395f143c52de2e2fa40e593f0972fd75e044148ea822e062902f1d538531 | 69,999 |
results__full__all_results_json | result_artifact | json | results/full/all_results.json | true | 7797a498acfb8f2803bdc2d062e9550f4347d33b298864c59a6f08176b31a88e | 116,748 |
results__full__crossover_predictor_json | result_artifact | json | results/full/crossover_predictor.json | true | 4ac44ce544860ab9eb771c2defc97917064311985ed71e204751a62a285550a4 | 6,370 |
results__full__downstream_v5__aggregate_json | result_artifact | json | results/full/downstream_v5/aggregate.json | true | 974f3620ec33957cdc6afc8ebd0146b62e8874dc41136bf5b9b6c3bdd7d30ff6 | 4,897 |
results__full__fast_extract_json | result_artifact | json | results/full/fast_extract.json | true | 5881efea1ede8f29296fb7a2108f64e5a8de0f548c5c784056bff1fb46a65e93 | 15,815 |
results__full__hessian_pyhessian_v4__aggregate_json | result_artifact | json | results/full/hessian_pyhessian_v4/aggregate.json | true | 3b887dccad0b445a0bf74ff84ddc42dcac1417a19f6a117994449fd0de48f60e | 22,913 |
results__full__lambada_eval__aggregate_json | result_artifact | json | results/full/lambada_eval/aggregate.json | true | ce37d10cf3456d3fda311ddc97ff32f377b5272f81d9ec80e5bd6dfed37d8b61 | 27,980 |
results__full__manifests__alpha_sweep_118m_summary_json | result_artifact | json | results/full/manifests/alpha_sweep_118m_summary.json | true | ecd533b8152d2b6e348b4f94ff487fad561cb2a552d25a5ac557223832a52689 | 2,281 |
results__full__manifests__predictor_validation_json | result_artifact | json | results/full/manifests/predictor_validation.json | true | 14302e82266cfe5b39cfd6c0ea755a57da256a0c41f51f027f6a6183e753ab51 | 16,400 |
results__full__manifests__sig_tests_json | result_artifact | json | results/full/manifests/sig_tests.json | true | 9d10175c33f9c316f97f4039cb4c9bb524459e922c017ba28c1e23ffce8990f5 | 11,895 |
results__full__noise_stability_s3__aggregate_json | result_artifact | json | results/full/noise_stability_s3/aggregate.json | true | f5d601c707aa63e4c234ba59abc14e46baa4d4998475eb245ecfbd12e495aba7 | 3,127 |
results__full__noise_stability_uniform__aggregate_json | result_artifact | json | results/full/noise_stability_uniform/aggregate.json | true | 3ac8a1f87929bfea98e19cbf7ba8be4c4fca769321ae4f7024faa7a68be6cf7f | 15,271 |
results__full__saturation_results_json | result_artifact | json | results/full/saturation_results.json | true | bb871cb3e3c7cb95e8b334d042fb9cbfb5d3b0ed4bf45c6e3501cb3ef255c55a | 384,041 |
results__full__scale5_metadata_check_json | result_artifact | json | results/full/scale5_metadata_check.json | true | 0127598467a2bb63261d2587144c2101bd58ac12330c2cff0fa3416f379d6c53 | 13,138 |
results__phase_diagram_json | result_artifact | json | results/phase_diagram.json | true | ac6ee3bde5369f02c23961aa2b27e3572700526c3a5e06ba96ce55b779dfba68 | 2,130 |
results__rmsnorm_results_json | result_artifact | json | results/rmsnorm_results.json | true | fec2c4f67bef0c77485cea5c42258952c056ba252b89b9957c49867126e48aee | 1,242 |
results__scaling_json | result_artifact | json | results/scaling.json | true | f900f06124ba36f95b3c801db285c6e7e4c8331322687067ace79b50d5437c05 | 3,247 |
results__train_val_gap_json | result_artifact | json | results/train_val_gap.json | true | c46d32f450711887a3dfca4f13ab468c4e4a3d0f88b4198c608365d09cf10e4d | 2,026 |
results__vit_results_json | result_artifact | json | results/vit_results.json | true | af2028744c89e4af0c40b4df861cc6ebe923f2193693c15de1181fdd5f14acc4 | 1,975 |
DyT Composition Study Artifacts
This dataset contains sanitized result manifests and analysis outputs for When Does Removing LayerNorm Help? Activation Bounding as a Regime-Dependent Implicit Regularizer.
DOI: https://doi.org/10.48550/arXiv.2604.23434
Contents
The artifacts include aggregate training metrics, saturation measurements, statistical-test summaries, predictor-validation outputs, table-source manifests, and selected aggregate analysis files used by the public code repository.
The Dataset Viewer table is an index of the artifact files. The machine-readable result artifacts are stored under results/.
This is not a natural-language training dataset. It does not redistribute WikiText, OpenWebText, LAMBADA, BLIMP, model checkpoints, or raw training logs.
Intended Use
Use this artifact bundle to:
- inspect the machine-readable results behind the paper;
- reproduce paper tables and consistency checks;
- compare DyT, LayerNorm, RMSNorm, HardTanh, DiffAttn, and related controls at the reported scales;
- audit provenance for reported quantitative claims.
Limitations
- The experiments are compute-limited and below Chinchilla-optimal training.
- The included files are result artifacts, not full raw training traces or checkpoints.
- The saturation diagnostic should be treated as a per-deployment calibration cue, not a universal rule.
- Raw public datasets retain their original licenses and are not mirrored here.
Public Metadata
PROVENANCE.json: source repository, paper identifiers, cleanup policy, and file-level hashes.SHA256SUMS.txt: checksums for payload files and the provenance manifest.metadata/validation_report.md: JSON parse, naming, forbidden-file, and leak-scan summary.data/artifact_index.jsonl: machine-readable index of the artifact files.
Licensing
The result artifacts in this dataset are released under CC BY 4.0.
The associated GitHub code is released under the MIT License.
Citation
@misc{verma2026dytcomposition,
title = {When Does Removing LayerNorm Help? Activation Bounding as a Regime-Dependent Implicit Regularizer},
author = {Verma, Lucky},
year = {2026},
publisher = {arXiv},
doi = {10.48550/arXiv.2604.23434},
url = {https://arxiv.org/abs/2604.23434},
eprint = {2604.23434},
archivePrefix = {arXiv},
primaryClass = {cs.LG}
}
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