The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ValueError
Message: Value is too big!
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
yield from 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 251, in _generate_tables
batch = "\n".join(ujson_dumps(x) for x in ujson_loads(full_data)).encode()
~~~~~~~~~~~^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Value is too big!Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
SenseMath: Do LLMs Have Number Sense? Evaluating Shortcut Use, Judgment, and Generation
SenseMath contains 4,800 Apply items across eight number-sense categories and four
nominal digit-scale conditions, with strong, weak, and control variants. The
paper's Judge setting contains exactly J1 shortcut appropriateness and J2 strategy
identification. Current data version: paper-aligned-v1.
Files and Task Definitions
| File | Task | Records |
|---|---|---|
data/sensemath_v2_d2.json |
Apply, d2 | 400 families / 1,200 items |
data/sensemath_v2_d4.json |
Apply, d4 | 400 families / 1,200 items |
data/sensemath_v2_d8.json |
Apply, d8 | 400 families / 1,200 items |
data/sensemath_v2_d16.json |
Apply, d16 | 400 families / 1,200 items |
data/judge_j1.json |
J1: is a shortcut appropriate? YES / NO | 300 items |
data/judge_j2.json |
J2: classify a supplied solution as SHORTCUT / COMPUTATION | 80 items |
data/subsets/judge_j1_paper_filtered_261.json |
Separate J1 reporting subset | 261 of the 300 J1 items |
The full J1 and filtered J1 profiles are reported separately in the paper. Do not
pool their scores or add the subset to the total item count. J2 has 54 SHORTCUT
and 26 COMPUTATION labels. Task identity must be determined from the manifest and
task_type, not from a filename in an earlier revision.
data/manifest.json records task identities, counts, and SHA256 hashes. The GitHub
repository uses the same data filenames under benchmark/ rather than data/.
Questions, options, prompts and reference labels are retained from their source
sets; this version alignment is not a new model evaluation or a semantic
revalidation of every strategy label.
Usage
Read original JSON with Python to preserve large integer values exactly:
import json
from pathlib import Path
families = json.loads(Path("data/sensemath_v2_d4.json").read_bytes())
j1 = json.loads(Path("data/judge_j1.json").read_bytes())
j2 = json.loads(Path("data/judge_j2.json").read_bytes())
The named configurations above separate the different schemas; do not combine all JSON files into a single task. For exact arithmetic, original JSON integers are authoritative rather than any floating-point conversion by downstream tools.
Use the GitHub Judge runner with --step validate to verify hashes and task types.
J1 defaults to the 300-item profile; select --j1-profile paper-filtered for the
261-item subset. The runner accepts an HF checkout via --data-dir /path/to/data.
中文说明
本版本严格对应论文的 J1、J2:J1 判断捷径是否适用,J2 判断给定解法属于捷径还是逐步计算。J1 全量 300 题与论文筛选 261 题分别使用,不能混算。完整说明见 数据版本与使用口径。
Citation
@article{zhuang2026sensemath,
title={SenseMath: Do LLMs Have Number Sense? Evaluating Shortcut Use, Judgment, and Generation},
author={Zhuang, Haomin and Wang, Xiangqi and Shen, Yili and Cheng, Ying and Zhang, Xiangliang},
journal={arXiv preprint arXiv:2604.01988},
year={2026}
}
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