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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
TIE: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: double, d_rho_CI: list< (... 91 chars omitted)
child 0, n: int64
child 1, n_scored: int64
child 2, rho_chiK: double
child 3, rho_chi0: double
child 4, d_rho: double
child 5, d_rho_CI: list<item: double>
child 0, item: double
child 6, F1_chiK: double
child 7, F1_chi0: double
child 8, d_F1: double
child 9, d_F1_CI: list<item: double>
child 0, item: double
SRIG: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: double, d_rho_CI: list< (... 91 chars omitted)
child 0, n: int64
child 1, n_scored: int64
child 2, rho_chiK: double
child 3, rho_chi0: double
child 4, d_rho: double
child 5, d_rho_CI: list<item: double>
child 0, item: double
child 6, F1_chiK: double
child 7, F1_chi0: double
child 8, d_F1: double
child 9, d_F1_CI: list<item: double>
child 0, item: double
SRIE: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: double, d_rho_CI: list< (... 91 chars omitted)
child 0, n: int64
child 1, n_scored: int64
child 2, rho_chiK: double
child 3, rho_chi0: double
child 4, d_rho: double
child 5, d_rho_CI: list<item: double>
child 0, item: double
child 6, F1_chiK: double
child 7, F1_chi0: double
child 8, d_F1: double
child 9, d_F1_CI: list<item: double>
child 0, item: double
MRIG: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: doubl
...
child 0, item: double
child 1, IoU_p: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 2, pq_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 3, sc_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 2, viescore2_v3_rl_eval_suite: struct<F1: struct<point: double, ci95: list<item: double>>, IoU_p: struct<point: double, ci95: list< (... 129 chars omitted)
child 0, F1: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 1, IoU_p: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 2, pq_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 3, sc_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
n_samples: int64
n_boot: int64
to
{'n_samples': Value('int64'), 'n_boot': Value('int64'), 'models': {'viescore2_v3_sft_eval_suite': {'F1': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'IoU_p': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'pq_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'sc_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}}, 'viescore2_v3_5ep_eval_suite': {'F1': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'IoU_p': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'pq_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'sc_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}}, 'viescore2_v3_rl_eval_suite': {'F1': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'IoU_p': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'pq_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'sc_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}}}, 'paired': {'viescore2_v3_5ep_eval_suite - viescore2_v3_sft_eval_suite': {'F1': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'IoU_p': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'pq_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'sc_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}}, 'viescore2_v3_rl_eval_suite - viescore2_v3_sft_eval_suite': {'F1': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'IoU_p': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'pq_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'sc_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}}}}
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 483, 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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
TIE: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: double, d_rho_CI: list< (... 91 chars omitted)
child 0, n: int64
child 1, n_scored: int64
child 2, rho_chiK: double
child 3, rho_chi0: double
child 4, d_rho: double
child 5, d_rho_CI: list<item: double>
child 0, item: double
child 6, F1_chiK: double
child 7, F1_chi0: double
child 8, d_F1: double
child 9, d_F1_CI: list<item: double>
child 0, item: double
SRIG: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: double, d_rho_CI: list< (... 91 chars omitted)
child 0, n: int64
child 1, n_scored: int64
child 2, rho_chiK: double
child 3, rho_chi0: double
child 4, d_rho: double
child 5, d_rho_CI: list<item: double>
child 0, item: double
child 6, F1_chiK: double
child 7, F1_chi0: double
child 8, d_F1: double
child 9, d_F1_CI: list<item: double>
child 0, item: double
SRIE: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: double, d_rho_CI: list< (... 91 chars omitted)
child 0, n: int64
child 1, n_scored: int64
child 2, rho_chiK: double
child 3, rho_chi0: double
child 4, d_rho: double
child 5, d_rho_CI: list<item: double>
child 0, item: double
child 6, F1_chiK: double
child 7, F1_chi0: double
child 8, d_F1: double
child 9, d_F1_CI: list<item: double>
child 0, item: double
MRIG: struct<n: int64, n_scored: int64, rho_chiK: double, rho_chi0: double, d_rho: doubl
...
child 0, item: double
child 1, IoU_p: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 2, pq_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 3, sc_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 2, viescore2_v3_rl_eval_suite: struct<F1: struct<point: double, ci95: list<item: double>>, IoU_p: struct<point: double, ci95: list< (... 129 chars omitted)
child 0, F1: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 1, IoU_p: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 2, pq_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
child 3, sc_rho: struct<point: double, ci95: list<item: double>>
child 0, point: double
child 1, ci95: list<item: double>
child 0, item: double
n_samples: int64
n_boot: int64
to
{'n_samples': Value('int64'), 'n_boot': Value('int64'), 'models': {'viescore2_v3_sft_eval_suite': {'F1': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'IoU_p': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'pq_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'sc_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}}, 'viescore2_v3_5ep_eval_suite': {'F1': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'IoU_p': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'pq_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'sc_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}}, 'viescore2_v3_rl_eval_suite': {'F1': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'IoU_p': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'pq_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}, 'sc_rho': {'point': Value('float64'), 'ci95': List(Value('float64'))}}}, 'paired': {'viescore2_v3_5ep_eval_suite - viescore2_v3_sft_eval_suite': {'F1': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'IoU_p': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'pq_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'sc_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}}, 'viescore2_v3_rl_eval_suite - viescore2_v3_sft_eval_suite': {'F1': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'IoU_p': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'pq_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}, 'sc_rho': {'diff': Value('float64'), 'ci95': List(Value('float64')), 'p_positive': Value('float64'), 'significant': Value('bool')}}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
VIEScore2 — raw evaluation results
Raw result files behind every number reported in the VIEScore2 paper, for
independent verification. Produced by run_eval.py and the analyze_*.py
scripts in the accompanying code release, under the frozen evaluation
protocol (configs/eval_protocol.json).
Layout
eval_results/— main 1,300-example multi-source suite: VIEScore2, VIEScore2 (w/o GRPO), replication seeds, equal-compute controls, reward ablations (dev_b*= F_β sweeps), and analysis summaries (bootstrap CIs, χ0 context intervention).eval_results_external/— six external localization benchmarks (RichHF, AbHuman, HAD, SynthScars, PAL4VST, SDG-30K): our models, specialist baselines under their native contracts (RAHF, ImageDoctor, PAL4VST, SegFormer, HADM, LEGION, SDG), closed models under our frozen contract (gpt56terra_*,gpt56sol_*,gemini3flash_*,opus55_*), MMRB2 preference results, and per-benchmark analysis files (extern_*_analysis.json,table4_new_rows.json).
Each result file contains a summary block (protocol, support) and per-row
results (per-sample predictions, cell confusion counts, grid IoU, raw
model responses). Model checkpoints referenced by neutral labels;
$DATA_ROOT is a placeholder for the local data root.
Naming: VIEScore2 denotes the full post-GRPO model; ablated variants are
marked by what they lack (e.g. viescore2_sft_* files = w/o GRPO).
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