Canonical multiple-choice reading comprehension benchmark built from English exams for Chinese middle and high school students. ~28K passages and ~100K questions. Evaluated as accuracy over RACE-M (middle) + RACE-H (high) combined.
2 results indexed across 1 metric. Shaded row marks current SOTA; ties broken by submission date.
| # | Model | Org | Submitted | Paper / code | accuracy |
|---|---|---|---|---|---|
| 01 | ALBERT ensemble | — | Sep 2019 | ALBERT: A Lite BERT for Self-supervised Learning of Lang… · code | 89.40 |
| 02 | RoBERTa | — | Jul 2019 | RoBERTa: A Robustly Optimized BERT Pretraining Approach · code | 83.20 |
Each row below marks a model that broke the previous record on accuracy. Intermediate submissions are kept in the leaderboard above; only SOTA-setting entries are re-listed here.
Higher scores win. Each subsequent entry improved upon the previous best.
Every paper below corresponds to at least one row in the leaderboard above. Click through for the arXiv preprint and, when available, the reference implementation.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.