Datasets:

nur-dev
/

multilingual-robot-grounding-causal-audit

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
wrong_goal_prevented_5of5: struct<k: int64, n: int64, cp95: list<item: double>>
  child 0, k: int64
  child 1, n: int64
  child 2, cp95: list<item: double>
      child 0, item: double
correct_blocked_7of7: struct<k: int64, n: int64, cp95: list<item: double>>
  child 0, k: int64
  child 1, n: int64
  child 2, cp95: list<item: double>
      child 0, item: double
ask_repair_0of36: struct<k: int64, n: int64, cp95: list<item: double>>
  child 0, k: int64
  child 1, n: int64
  child 2, cp95: list<item: double>
      child 0, item: double
s0_requested_given_canonical_frame_correct: struct<k: int64, n: int64, cp95: list<item: double>>
  child 0, k: int64
  child 1, n: int64
  child 2, cp95: list<item: double>
      child 0, item: double
gold_input_requested: struct<k: int64, n: int64, cp95: list<item: double>, complete: bool>
  child 0, k: int64
  child 1, n: int64
  child 2, cp95: list<item: double>
      child 0, item: double
  child 3, complete: bool
gold_input_either_goal: struct<k: int64, n: int64, cp95: list<item: double>>
  child 0, k: int64
  child 1, n: int64
  child 2, cp95: list<item: double>
      child 0, item: double
recovery_cases: struct<n: int64, UNSUPPORTED_FRAME_RECONSTRUCTION: int64, REQUIRES_NATIVE_REVIEW: int64, detail: lis (... 135 chars omitted)
  child 0, n: int64
  child 1, UNSUPPORTED_FRAME_RECONSTRUCTION: int64
  child 2, REQUIRES_NATIVE_REVIEW: int64
  child 3, detail: list<item: struct<condition_id: string, language: string, requested: string, asr: strin
...
language: string
          child 2, requested: string
          child 3, asr: string
          child 4, normalized_instruction: string
          child 5, label: string
n_conditions: int64
by_language: struct<en: struct<n: int64, asr_preserved: int64, frame_correct: int64>, ru: struct<n: int64, asr_pr (... 185 chars omitted)
  child 0, en: struct<n: int64, asr_preserved: int64, frame_correct: int64>
      child 0, n: int64
      child 1, asr_preserved: int64
      child 2, frame_correct: int64
  child 1, ru: struct<n: int64, asr_preserved: int64, frame_correct: int64>
      child 0, n: int64
      child 1, asr_preserved: int64
      child 2, frame_correct: int64
  child 2, kk: struct<n: int64, asr_preserved: int64, frame_correct: int64>
      child 0, n: int64
      child 1, asr_preserved: int64
      child 2, frame_correct: int64
  child 3, kk_ru_code_switch: struct<n: int64, asr_preserved: int64, frame_correct: int64>
      child 0, n: int64
      child 1, asr_preserved: int64
      child 2, frame_correct: int64
analysis: string
crosstab: struct<asr_preserved: struct<frame_correct: int64, frame_incorrect: int64>, asr_corrupted: struct<fr (... 44 chars omitted)
  child 0, asr_preserved: struct<frame_correct: int64, frame_incorrect: int64>
      child 0, frame_correct: int64
      child 1, frame_incorrect: int64
  child 1, asr_corrupted: struct<frame_correct: int64, frame_incorrect: int64>
      child 0, frame_correct: int64
      child 1, frame_incorrect: int64
method: string
to
{'analysis': Value('string'), 'method': Value('string'), 'n_conditions': Value('int64'), 'crosstab': {'asr_preserved': {'frame_correct': Value('int64'), 'frame_incorrect': Value('int64')}, 'asr_corrupted': {'frame_correct': Value('int64'), 'frame_incorrect': Value('int64')}}, 'recovery_cases': {'n': Value('int64'), 'UNSUPPORTED_FRAME_RECONSTRUCTION': Value('int64'), 'REQUIRES_NATIVE_REVIEW': Value('int64'), 'detail': List({'condition_id': Value('string'), 'language': Value('string'), 'requested': Value('string'), 'asr': Value('string'), 'normalized_instruction': Value('string'), 'label': Value('string')})}, 'by_language': {'en': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}, 'ru': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}, 'kk': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}, 'kk_ru_code_switch': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}}}
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
              wrong_goal_prevented_5of5: struct<k: int64, n: int64, cp95: list<item: double>>
                child 0, k: int64
                child 1, n: int64
                child 2, cp95: list<item: double>
                    child 0, item: double
              correct_blocked_7of7: struct<k: int64, n: int64, cp95: list<item: double>>
                child 0, k: int64
                child 1, n: int64
                child 2, cp95: list<item: double>
                    child 0, item: double
              ask_repair_0of36: struct<k: int64, n: int64, cp95: list<item: double>>
                child 0, k: int64
                child 1, n: int64
                child 2, cp95: list<item: double>
                    child 0, item: double
              s0_requested_given_canonical_frame_correct: struct<k: int64, n: int64, cp95: list<item: double>>
                child 0, k: int64
                child 1, n: int64
                child 2, cp95: list<item: double>
                    child 0, item: double
              gold_input_requested: struct<k: int64, n: int64, cp95: list<item: double>, complete: bool>
                child 0, k: int64
                child 1, n: int64
                child 2, cp95: list<item: double>
                    child 0, item: double
                child 3, complete: bool
              gold_input_either_goal: struct<k: int64, n: int64, cp95: list<item: double>>
                child 0, k: int64
                child 1, n: int64
                child 2, cp95: list<item: double>
                    child 0, item: double
              recovery_cases: struct<n: int64, UNSUPPORTED_FRAME_RECONSTRUCTION: int64, REQUIRES_NATIVE_REVIEW: int64, detail: lis (... 135 chars omitted)
                child 0, n: int64
                child 1, UNSUPPORTED_FRAME_RECONSTRUCTION: int64
                child 2, REQUIRES_NATIVE_REVIEW: int64
                child 3, detail: list<item: struct<condition_id: string, language: string, requested: string, asr: strin
              ...
              language: string
                        child 2, requested: string
                        child 3, asr: string
                        child 4, normalized_instruction: string
                        child 5, label: string
              n_conditions: int64
              by_language: struct<en: struct<n: int64, asr_preserved: int64, frame_correct: int64>, ru: struct<n: int64, asr_pr (... 185 chars omitted)
                child 0, en: struct<n: int64, asr_preserved: int64, frame_correct: int64>
                    child 0, n: int64
                    child 1, asr_preserved: int64
                    child 2, frame_correct: int64
                child 1, ru: struct<n: int64, asr_preserved: int64, frame_correct: int64>
                    child 0, n: int64
                    child 1, asr_preserved: int64
                    child 2, frame_correct: int64
                child 2, kk: struct<n: int64, asr_preserved: int64, frame_correct: int64>
                    child 0, n: int64
                    child 1, asr_preserved: int64
                    child 2, frame_correct: int64
                child 3, kk_ru_code_switch: struct<n: int64, asr_preserved: int64, frame_correct: int64>
                    child 0, n: int64
                    child 1, asr_preserved: int64
                    child 2, frame_correct: int64
              analysis: string
              crosstab: struct<asr_preserved: struct<frame_correct: int64, frame_incorrect: int64>, asr_corrupted: struct<fr (... 44 chars omitted)
                child 0, asr_preserved: struct<frame_correct: int64, frame_incorrect: int64>
                    child 0, frame_correct: int64
                    child 1, frame_incorrect: int64
                child 1, asr_corrupted: struct<frame_correct: int64, frame_incorrect: int64>
                    child 0, frame_correct: int64
                    child 1, frame_incorrect: int64
              method: string
              to
              {'analysis': Value('string'), 'method': Value('string'), 'n_conditions': Value('int64'), 'crosstab': {'asr_preserved': {'frame_correct': Value('int64'), 'frame_incorrect': Value('int64')}, 'asr_corrupted': {'frame_correct': Value('int64'), 'frame_incorrect': Value('int64')}}, 'recovery_cases': {'n': Value('int64'), 'UNSUPPORTED_FRAME_RECONSTRUCTION': Value('int64'), 'REQUIRES_NATIVE_REVIEW': Value('int64'), 'detail': List({'condition_id': Value('string'), 'language': Value('string'), 'requested': Value('string'), 'asr': Value('string'), 'normalized_instruction': Value('string'), 'label': Value('string')})}, 'by_language': {'en': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}, 'ru': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}, 'kk': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}, 'kk_ru_code_switch': {'n': Value('int64'), 'asr_preserved': Value('int64'), 'frame_correct': Value('int64')}}}
              because column names don't match

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Multilingual Robot Grounding: A Causal Speech–Vision–Action Audit

Frozen manifests, per-condition traces, semantic-preservation analyses, instruction-dependence controls, counterfactual robot outcomes, and reproducibility scripts for a multilingual speech–vision–action grounding audit.

A compact multilingual (Kazakh / Russian / English) speech→ASR→parser→perception→policy→TTS pipeline is evaluated on a frozen benchmark of 60 counterfactual VLABench states (480 conditions, 960 paired closed-loop episodes), with and without a deterministic six-action safeguard. This repository contains read-only trace data and derived tables/figures only; no model weights and no secrets are included.

Provenance

Frozen results package final_results_package.json, sha256 prefix b1c42a62bc46b0b2.
Normalizer e7b53b46…; guard deterministic_compact_guard.v1; command spec 53487b00cd7a6b2a; fixtures 93181e7a6b25add8; frames 2889872014f3ff49; ASK fixtures 027dae74be94338a; episodes a626e682d055e03c; gold results 47b41f2d2dbeb9ea; policy checkpoint lerobot/smolvla_vlabench.
No large-model supervision, distillation or oracle leakage. All 960 primary episodes completed with zero technical failures. SHA256SUMS.txt fixes every file below.

Pipeline components (referenced, not redistributed here)

ASR — nur-dev/Qwen3-ASR-0.6B-kk-ru-en
Semantic parser — nur-dev/farabi-0.6B-agent-rag
TTS — nur-dev/ait-syn-0.6b-trilingual-v30
Policy — lerobot/smolvla_vlabench

Path	What
`final_results_package.json`	Single frozen package; source of every headline number.
`analyses/`	Canonical ASR×frame cross-tab, stage decomposition, exact intervals, gold-input analysis, paired study analysis.
`traces/`	Per-condition raw traces: episodes, fixtures, S0 frames, ASK fixtures, benchmark conditions.
`figures/`	The five paper figures (vector PDF).
`tables/`	The ten paper tables (LaTeX `tabular` bodies).
`native_review_worksheet.csv`	The 26 cross-script ASR recoveries pending native Kazakh/Russian review.
`SHA256SUMS.txt`	Checksums for all of the above.

Reproducing the tables and figures

The tables and figures are regenerated purely from final_results_package.json (plus the frozen instruction-dependence audit) by the paper's reproduce/ scripts:

python make_tables.py  --package final_results_package.json --e1b <audit.json> --out tables/
python make_figures.py --package final_results_package.json --e1b <audit.json> --out figures/

Scope and limitations

Simulation only; synthetic integration speech, not human speech. Object results are exploratory (2 templates); the attribute axis is primary (5 templates). Destination and relation axes are not claimed. 26 cross-script ASR-recovery labels are pending native review and can affect only those 26 condition labels, none of the execution results.