Datasets:
File size: 8,586 Bytes
5fd04ea 0f11060 5fd04ea 6f24f7f 8081183 001189f 41ec9e9 c25e9b1 26e182e c25e9b1 3891af7 c25e9b1 3099d67 c25e9b1 3891af7 c25e9b1 41ec9e9 5f0bb4c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 |
---
Paper: arxiv.org/abs/2406.16772
license: cc-by-nc-sa-4.0
dataset_info:
- config_name: Math
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 3153019
num_examples: 2977
- name: val
num_bytes: 484904
num_examples: 244
download_size: 1402261
dataset_size: 3637923
- config_name: Physics
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 3139836
num_examples: 1303
- name: val
num_bytes: 283157
num_examples: 90
download_size: 1613993
dataset_size: 3422993
- config_name: Chemistry
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 3102033
num_examples: 1354
- name: val
num_bytes: 284518
num_examples: 65
download_size: 1389141
dataset_size: 3386551
- config_name: Biology
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 3483679
num_examples: 1495
- name: val
num_bytes: 238015
num_examples: 63
download_size: 1814227
dataset_size: 3721694
- config_name: Geography
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 2555530
num_examples: 1522
- name: val
num_bytes: 138082
num_examples: 68
download_size: 1212126
dataset_size: 2693612
- config_name: Astronomy
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 3161275
num_examples: 1110
- name: val
num_bytes: 320943
num_examples: 90
download_size: 1685604
dataset_size: 3482218
- config_name: CS
features:
- name: id
dtype: string
- name: problem
dtype: string
- name: prompt
dtype: string
- name: figure_urls
sequence: string
- name: answer
sequence: string
- name: solution
dtype: string
- name: answer_type
dtype: string
- name: unit
sequence: string
- name: answer_sequence
sequence: string
- name: type_sequence
sequence: string
- name: test_cases
sequence:
- name: input
dtype: string
- name: output
dtype: string
- name: subject
dtype: string
- name: language
dtype: string
- name: modality
dtype: string
splits:
- name: test
num_bytes: 1235615
num_examples: 216
- name: val
num_bytes: 496838967
num_examples: 18
download_size: 256590378
dataset_size: 498074582
configs:
- config_name: Math
data_files:
- split: test
path: Math/test-*
- split: val
path: Math/val-*
- config_name: Physics
data_files:
- split: test
path: Physics/test-*
- split: val
path: Physics/val-*
- config_name: Chemistry
data_files:
- split: test
path: Chemistry/test-*
- split: val
path: Chemistry/val-*
- config_name: Biology
data_files:
- split: test
path: Biology/test-*
- split: val
path: Biology/val-*
- config_name: Geography
data_files:
- split: test
path: Geography/test-*
- split: val
path: Geography/val-*
- config_name: Astronomy
data_files:
- split: test
path: Astronomy/test-*
- split: val
path: Astronomy/val-*
- config_name: CS
data_files:
- split: test
path: CS/test-*
- split: val
path: CS/val-*
task_categories:
- question-answering
language:
- en
- zh
pretty_name: OlympicArena
size_categories:
- 10K<n<100K
tags:
- croissant
- image
- text
---
# OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI
**OlympicArena** is a comprehensive, highly-challenging, and rigorously curated benchmark featuring a detailed, fine-grained evaluation mechanism designed to assess advanced AI capabilities across a broad spectrum of Olympic-level challenges.
This benchmark encompasses seven disciplines: Mathematics, Physics, Chemistry, Biology, Geography, Astronomy, and Computer Science. Each discipline is divided into two splits: validation (val) and test. The validation split includes publicly available answers for small-scale testing and evaluation, while the test split does not disclose the answers, users could submit their results.
# An Example to load the data
```python
from datasets import load_dataset
dataset=load_dataset("GAIR/OlympicArena", "Math", split="val")
print(dataset[0])
```
More details on loading and using the data are at our [github page](https://github.com/GAIR-NLP/OlympicArena).
If you do find our code helpful or use our benchmark dataset, please citing our paper.
```
@article{huang2024olympicarena,
title={OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI},
author={Zhen Huang and Zengzhi Wang and Shijie Xia and Xuefeng Li and Haoyang Zou and Ruijie Xu and Run-Ze Fan and Lyumanshan Ye and Ethan Chern and Yixin Ye and Yikai Zhang and Yuqing Yang and Ting Wu and Binjie Wang and Shichao Sun and Yang Xiao and Yiyuan Li and Fan Zhou and Steffi Chern and Yiwei Qin and Yan Ma and Jiadi Su and Yixiu Liu and Yuxiang Zheng and Shaoting Zhang and Dahua Lin and Yu Qiao and Pengfei Liu},
year={2024},
journal={arXiv preprint arXiv:2406.12753},
url={https://arxiv.org/abs/2406.12753}
}
```
|