Aria AI Operations Research Portfolio
Collection
Enterprise OR, optimization, and decomposition demos by Aria AI • 151 items • Updated
Dataset Viewer
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
benchmark: string
model_id: string
n_cases: int64
mean_reward: double
compile_rate: double
feasibility_rate: double
objective_match_rate: double
optimal_rate: double
per_task: struct<problem_classification: double, formulation: double, code_generation: double>
child 0, problem_classification: double
child 1, formulation: double
child 2, code_generation: double
cases: list<item: struct<problem_id: string, task_type: string, token_overlap: int64, reward: double, compi (... 145 chars omitted)
child 0, item: struct<problem_id: string, task_type: string, token_overlap: int64, reward: double, compiles: bool, (... 133 chars omitted)
child 0, problem_id: string
child 1, task_type: string
child 2, token_overlap: int64
child 3, reward: double
child 4, compiles: bool
child 5, feasible: bool
child 6, objective_correct: bool
child 7, objective_optimal: bool
child 8, objective_value: double
child 9, expected_objective: double
child 10, error: string
version: string
dataset: string
to
{'dataset': Value('string'), 'version': Value('string'), 'benchmark': Value('string'), 'model_id': Value('string'), 'n_cases': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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
benchmark: string
model_id: string
n_cases: int64
mean_reward: double
compile_rate: double
feasibility_rate: double
objective_match_rate: double
optimal_rate: double
per_task: struct<problem_classification: double, formulation: double, code_generation: double>
child 0, problem_classification: double
child 1, formulation: double
child 2, code_generation: double
cases: list<item: struct<problem_id: string, task_type: string, token_overlap: int64, reward: double, compi (... 145 chars omitted)
child 0, item: struct<problem_id: string, task_type: string, token_overlap: int64, reward: double, compiles: bool, (... 133 chars omitted)
child 0, problem_id: string
child 1, task_type: string
child 2, token_overlap: int64
child 3, reward: double
child 4, compiles: bool
child 5, feasible: bool
child 6, objective_correct: bool
child 7, objective_optimal: bool
child 8, objective_value: double
child 9, expected_objective: double
child 10, error: string
version: string
dataset: string
to
{'dataset': Value('string'), 'version': Value('string'), 'benchmark': Value('string'), 'model_id': Value('string'), 'n_cases': Value('int64')}
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.
OR Reasoning Benchmark Results
Execution-based evaluation for the OR Reasoning model across classification, formulation, and code generation tasks.
Metrics
| Metric | Description |
|---|---|
compile_rate |
Generated Pyomo code passes syntax/structure check |
feasibility_rate |
Model has objective, variables, and constraints |
objective_match_rate |
Objective within 15% of ground truth |
optimal_rate |
Objective within 2% of ground truth |
Reward Scheme
Solver-verifiable rewards used in GRPO training: +1 compile, +2 feasible, +4 correct objective, +8 optimal.
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