Benchmark Almanac

CMRC

Dropped

Models extract answer spans from Chinese Wikipedia paragraphs for about 20,000 human-written questions. Scoring is exact match and F1.

Released
October 2018
Kind
Reading in many languages
Level
Everyday
Scored
Checked automatically
Answers
Short answer
Tasks
All public
Strongest model tested
DeepSeek-V3 #154 on the capability index
Last in a launch post
December 2024, dropped before it saturated
Last model added
December 2024

In the authors’ words

Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, the existing reading comprehension datasets are mostly in English. In this paper, we introduce a Span-Extraction dataset for Chinese machine reading comprehension to add language diversities in this area. The dataset is composed by near 20,000 real questions annotated on Wikipedia paragraphs by human experts. We also annotated a challenge set which contains the questions that need comprehensive understanding and multi-sentence inference throughout the context. We present several baseline systems as well as anonymous submissions for demonstrating the difficulties in this dataset. With the release of the dataset, we hosted the Second Evaluation Workshop on Chinese Machine Reading Comprehension (CMRC 2018). We hope the release of the dataset could further accelerate the Chinese machine reading comprehension research. Resources are available: https://github.com/ymcui/cmrc2018

Abstract of A Span-Extraction Dataset for Chinese Machine Reading Comprehension (arXiv:1810.07366, CC0)
1
Model scored in lab cards
1
Launch post lists it, from 1 lab

DeepSeek-V3 leads with 76.3%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 DeepSeek-V3 76.3%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 DeepSeek-V3 76.3% Dec 2024 Lab model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) DeepSeek-V3 0% 20% 40% 60% 80% 100% 2025 Near the ceiling (85%) DeepSeek-V3

Source: Labs’ model cards

No launch post has listed it since December 2024

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

DeepSeek
DateLaunch postScoreAs the post writes it
Dec 26, 2024 DeepSeek-V3 76.3 CMRC (EM)

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