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rendered_xnli/xnli-ru-test/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogItCi0LDQutCw0Y8g0Y3QstC+0LvRjtGG0LjQuCDQsdC10LfRg9C80LjRjyDQv9GA0L7QtNC+0LvQttCw0Lv(...TRUNCATED)
rendered_xnli/xnli-en-validation/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIicgIE15IGZ1cnRoZXIgcG9pbnQgaXMgdGhhdCB0byBiZSB0b3RhbGx5IHN1Y2Nlc3NmdWwsIGEgZGljdGl(...TRUNCATED)
rendered_xnli/xnli-sw-test/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIkhpeW8gaWxpa3V3YSBoYW1ha2kgeWEgd2FrYXRpIGh1by4iLCAiaHlwb3RoZXNpcyI6ICJIaWkgaGFpa3V(...TRUNCATED)
rendered_xnli/xnli-bg-train/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogItGC0L7QuSDQvNC+0LbQtSDQtNCwINC40LzQsCDQvNCw0LvRitC6INC/0YDQvtCx0LvQtdC8INGBINGC0L7(...TRUNCATED)
rendered_xnli/xnli-tr-train/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIlPEsWNhayBoYXZhIHPEsWNhayB5b2sgYmVuIGdpZGl5b3J1bSBzxLFjYWsgaGF2YSBiYWxvbiIsICJoeXB(...TRUNCATED)
rendered_xnli/xnli-zh-validation/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIuaYr+eahOS4gOS6m+eJueauiueahOWFtOi2o+e7hCIsICJoeXBvdGhlc2lzIjogIuivpee7hOe7h+Wvuee(...TRUNCATED)
rendered_xnli/xnli-en-test/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIndlbGwgeW91IHNhaWQgeW91IGhhdmUga2lkcyBob3cgb2xkIiwgImh5cG90aGVzaXMiOiAiSG93IG1hbnk(...TRUNCATED)
rendered_xnli/xnli-hi-test/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIuCkuOCkreClgCDgpIngpLkg4KSV4KWN4KSw4KWH4KSh4KS/4KSfIOCkr+ClguCkqOCkv+Ckr+CkqCDgpJX(...TRUNCATED)
rendered_xnli/xnli-ur-test/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogItiq2YLYsduM2KjYpyDbgdixINqG24zYsiDaqduMINiz24zYp9iz2KrYr9in2YYgKNin2K/YqNuMINqI2Yj(...TRUNCATED)
rendered_xnli/xnli-en-train/part-00000
hf://datasets/baidu/rendered_xnli@3c45d7f119872c75500c953cc6285c3b3d202485/rendered_xnli.tar
"eyJwcmVtaXNlIjogIlRoZSBzZW5zaXRpdml0eSBvZiBjb3N0IHRvIHZvbHVtZSBmb3IgYSBwb3N0YWwgc3lzdGVtIGNhbiBiZSB(...TRUNCATED)
End of preview.

EMNLP 2024

Dataset Card for rendered XNLI

This repository contains the rendered XNLI dataset evaluated in the paper Autoregressive Pre-Training on Pixels and Texts (EMNLP 2024). For detailed instructions on how to use the model, please visit our GitHub page.

Citation

@misc{chai2024autoregressivepretrainingpixelstexts,
  title = {Autoregressive Pre-Training on Pixels and Texts},
  author = {Chai, Yekun and Liu, Qingyi and Xiao, Jingwu and Wang, Shuohuan and Sun, Yu and Wu, Hua},
  year = {2024},
  eprint = {2404.10710},
  archiveprefix = {arXiv},
  primaryclass = {cs.CL},
  url = {https://arxiv.org/abs/2404.10710},
}
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