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sida
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ica-lens-paper

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ArXiv:
Tags:
mechanistic-interpretability
interpretability
ica
independent-component-analysis
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
layer: string
activation_manifest: string
activation_shape: list<item: int64>
  child 0, item: int64
artifact_format: string
method: string
algorithm: string
preprocess: string
rows: int64
hidden_size: int64
n_components: int64
iterations: int64
converged: bool
lim_history: list<item: double>
  child 0, item: double
lim_stats_history: list<item: struct<iteration: int64, elapsed_seconds: double, max: double, p99: double, p95: double,  (... 56 chars omitted)
  child 0, item: struct<iteration: int64, elapsed_seconds: double, max: double, p99: double, p95: double, p05: double (... 44 chars omitted)
      child 0, iteration: int64
      child 1, elapsed_seconds: double
      child 2, max: double
      child 3, p99: double
      child 4, p95: double
      child 5, p05: double
      child 6, median: double
      child 7, mean: double
      child 8, std: double
final_lim: double
max_iter: int64
tol: double
fun: string
seed: int64
norm_eps: double
elapsed_seconds: double
repo_id: string
schema_version: int64
repo_type: string
contents: struct<models: struct<path: string, description: string>, databases: struct<path: string, files: str (... 109 chars omitted)
  child 0, models: struct<path: string, description: string>
      child 0, path: string
      child 1, description: string
  child 1, databases: struct<path: string, files: struct<ica_probe_mini.sqlite: struct<description: string>, ica_probe_ful (... 39 chars omitted)
      child 0, path: string
      child 1, files: struct<ica_probe_mini.sqlite: struct<description: string>, ica_probe_full.sqlite: struct<description (... 10 chars omitted)
          child 0, ica_probe_mini.sqlite: struct<description: string>
              child 0, description: string
          child 1, ica_probe_full.sqlite: struct<description: string>
              child 0, description: string
to
{'schema_version': Value('int64'), 'repo_id': Value('string'), 'repo_type': Value('string'), 'contents': {'models': {'path': Value('string'), 'description': Value('string')}, 'databases': {'path': Value('string'), 'files': {'ica_probe_mini.sqlite': {'description': Value('string')}, 'ica_probe_full.sqlite': {'description': Value('string')}}}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              layer: string
              activation_manifest: string
              activation_shape: list<item: int64>
                child 0, item: int64
              artifact_format: string
              method: string
              algorithm: string
              preprocess: string
              rows: int64
              hidden_size: int64
              n_components: int64
              iterations: int64
              converged: bool
              lim_history: list<item: double>
                child 0, item: double
              lim_stats_history: list<item: struct<iteration: int64, elapsed_seconds: double, max: double, p99: double, p95: double,  (... 56 chars omitted)
                child 0, item: struct<iteration: int64, elapsed_seconds: double, max: double, p99: double, p95: double, p05: double (... 44 chars omitted)
                    child 0, iteration: int64
                    child 1, elapsed_seconds: double
                    child 2, max: double
                    child 3, p99: double
                    child 4, p95: double
                    child 5, p05: double
                    child 6, median: double
                    child 7, mean: double
                    child 8, std: double
              final_lim: double
              max_iter: int64
              tol: double
              fun: string
              seed: int64
              norm_eps: double
              elapsed_seconds: double
              repo_id: string
              schema_version: int64
              repo_type: string
              contents: struct<models: struct<path: string, description: string>, databases: struct<path: string, files: str (... 109 chars omitted)
                child 0, models: struct<path: string, description: string>
                    child 0, path: string
                    child 1, description: string
                child 1, databases: struct<path: string, files: struct<ica_probe_mini.sqlite: struct<description: string>, ica_probe_ful (... 39 chars omitted)
                    child 0, path: string
                    child 1, files: struct<ica_probe_mini.sqlite: struct<description: string>, ica_probe_full.sqlite: struct<description (... 10 chars omitted)
                        child 0, ica_probe_mini.sqlite: struct<description: string>
                            child 0, description: string
                        child 1, ica_probe_full.sqlite: struct<description: string>
                            child 0, description: string
              to
              {'schema_version': Value('int64'), 'repo_id': Value('string'), 'repo_type': Value('string'), 'contents': {'models': {'path': Value('string'), 'description': Value('string')}, 'databases': {'path': Value('string'), 'files': {'ica_probe_mini.sqlite': {'description': Value('string')}, 'ica_probe_full.sqlite': {'description': Value('string')}}}}}
              because column names don't match

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ICA Lens Paper Artifacts

This dataset stores public artifacts for the paper ICA Lens: Interpreting Language Models Without Training Another Dictionary.

Introduction

ICA Lens is a practical workflow for stable, efficient, and auditable Independent Component Analysis (ICA) of language model representations. It recovers compact, human-interpretable directions without the need for training sparse autoencoders (SAEs). This repository contains the fitted FastICA artifacts and explorer databases for GPT-2 Small, Gemma 2 2B, and Qwen 3.5 2B Base.

Contents 

models/
  gpt2/
  gemma2_2b/
  qwen3_5_2b_base/

databases/
  ica_probe_mini.sqlite
  ica_probe_full.sqlite

manifest.json
checksums.sha256
  • models/: Contains fitted FastICA artifacts and JSON metadata for the supported models.
  • databases/: Contains SQLite databases for the ICA Lens explorer. The mini database maintains core browsing functionality, while the full database preserves richer context-token data.

Sample Usage

To use these artifacts with the official ICA Lens explorer, clone the source code and run the following:

uv sync
uv run python scripts/fetch_artifacts.py --models --databases
uv run python -m server.app --port 8001

Once the server is running, the explorer will be accessible at http://127.0.0.1:8001.

Citation 

@article{liu2026icalens,
  title={ICA Lens: Interpreting Language Models Without Training Another Dictionary},
  author={Liu, Sida and Han, Feijiang},
  journal={arXiv preprint arXiv:2606.11722},
  year={2026}
}
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