STEER: Reducing Inference Cost in Relational Foundation Models through Semantically Informed Sampling
Paper • 2610.00907 • Published
Datasets:
ArXiv:
License:
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
user-ltv:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-churn:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
product:Db: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-ltv:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-ltv:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-churn:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-churn:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-ltv:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-ltv:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
customer:Db: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-churn:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-churn:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-ltv:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-churn:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
review:Db: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
product_id of review: int64
brand of product: int64
product_id of product: int64
verified of review: int64
customer_id of customer: int64
product_id of item-churn: int64
timestamp of item-churn: int64
ltv of user-ltv: int64
churn of user-churn: int64
customer_id of user-ltv: int64
price of product: int64
customer_name of customer: int64
rating of review: int64
description of product: int64
customer_id of user-churn: int64
ltv of item-ltv: int64
category of product: int64
customer_id of review: int64
timestamp of user-ltv: int64
timestamp of item-ltv: int64
review_text of review: int64
churn of item-churn: int64
product_id of item-ltv: int64
title of product: int64
timestamp of user-churn: int64
review_time of review: int64
summary of review: int64
to
{'summary of review': Value('int64'), 'product_id of item-churn': Value('int64'), 'timestamp of item-ltv': Value('int64'), 'customer_name of customer': Value('int64'), 'category of product': Value('int64'), 'title of product': Value('int64'), 'review_time of review': Value('int64'), 'customer_id of review': Value('int64'), 'rating of review': Value('int64'), 'verified of review': Value('int64'), 'description of product': Value('int64'), 'price of product': Value('int64'), 'timestamp of user-ltv': Value('int64'), 'brand of product': Value('int64'), 'review_text of review': Value('int64'), 'product_id of item-ltv': Value('int64'), 'ltv of user-ltv': Value('int64'), 'customer_id of user-ltv': Value('int64'), 'timestamp of user-churn': Value('int64'), 'product_id of review': Value('int64'), 'product_id of product': Value('int64'), 'timestamp of item-churn': Value('int64'), 'customer_id of customer': Value('int64'), 'ltv of item-ltv': Value('int64'), 'churn of item-churn': Value('int64'), 'customer_id of user-churn': Value('int64'), 'churn of user-churn': 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 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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
user-ltv:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-churn:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
product:Db: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-ltv:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-ltv:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-churn:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-churn:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-ltv:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-ltv:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
customer:Db: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-churn:Train: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-churn:Val: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
user-ltv:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
item-churn:Test: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
review:Db: struct<node_idx_offset: int64, num_nodes: int64>
child 0, node_idx_offset: int64
child 1, num_nodes: int64
product_id of review: int64
brand of product: int64
product_id of product: int64
verified of review: int64
customer_id of customer: int64
product_id of item-churn: int64
timestamp of item-churn: int64
ltv of user-ltv: int64
churn of user-churn: int64
customer_id of user-ltv: int64
price of product: int64
customer_name of customer: int64
rating of review: int64
description of product: int64
customer_id of user-churn: int64
ltv of item-ltv: int64
category of product: int64
customer_id of review: int64
timestamp of user-ltv: int64
timestamp of item-ltv: int64
review_text of review: int64
churn of item-churn: int64
product_id of item-ltv: int64
title of product: int64
timestamp of user-churn: int64
review_time of review: int64
summary of review: int64
to
{'summary of review': Value('int64'), 'product_id of item-churn': Value('int64'), 'timestamp of item-ltv': Value('int64'), 'customer_name of customer': Value('int64'), 'category of product': Value('int64'), 'title of product': Value('int64'), 'review_time of review': Value('int64'), 'customer_id of review': Value('int64'), 'rating of review': Value('int64'), 'verified of review': Value('int64'), 'description of product': Value('int64'), 'price of product': Value('int64'), 'timestamp of user-ltv': Value('int64'), 'brand of product': Value('int64'), 'review_text of review': Value('int64'), 'product_id of item-ltv': Value('int64'), 'ltv of user-ltv': Value('int64'), 'customer_id of user-ltv': Value('int64'), 'timestamp of user-churn': Value('int64'), 'product_id of review': Value('int64'), 'product_id of product': Value('int64'), 'timestamp of item-churn': Value('int64'), 'customer_id of customer': Value('int64'), 'ltv of item-ltv': Value('int64'), 'churn of item-churn': Value('int64'), 'customer_id of user-churn': Value('int64'), 'churn of user-churn': 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.
steer-rt-data
Preprocessed RelBench data for RT. The seven v1 databases come from stanford-star/relbench-preprocessed (CC BY 4.0); rel-arxiv and rel-ratebeer are derived from stanford-star/relbench-v2-extra (CC BY-SA 4.0), so this repository is shared under CC BY-SA 4.0. Cite RelBench and the RT-J paper.
Part of STEER: STEER: Reducing Inference Cost in Relational Foundation Models through Semantically Informed Sampling (Mohamed and Aboulnaga, arXiv:2610.00907).
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