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CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark

arXiv 2112.13610 ↗First posted 27 Dec 2021cs.CLcited by 16

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Abstract (arXiv)

Realizing general-purpose language intelligence has been a longstanding goal for natural language processing, where standard evaluation benchmarks play a fundamental and guiding role. We argue that for general-purpose language intelligence evaluation, the benchmark itself needs to be comprehensive and systematic. To this end, we propose CUGE, a Chinese Language Understanding and Generation Evaluation benchmark with the following features: (1) Hierarchical benchmark framework, where datasets are principally selected and organized with a language capability-task-dataset hierarchy. (2) Multi-level scoring strategy, where different levels of model performance are provided based on the hierarchical framework. To facilitate CUGE, we provide a public leaderboard that can be customized to support flexible model judging criteria. Evaluation results on representative pre-trained language models indicate ample room for improvement towards general-purpose language intelligence. CUGE is publicly available at cuge.baai.ac.cn.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 16 of its 34 references that are in the map. First posted on arXiv 27 Dec 2021.

Builds on

16 of 34 references.

References · 16

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,899
  5. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
  6. 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,729
  7. 2020CLUE: A Chinese Language Understanding Evaluation Benchmarkcited by 278
  8. 2019Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehensioncited by 81
  9. 2015LCSTS: A Large Scale Chinese Short Text Summarization Datasetcited by 65
  10. 2019NCLS: Neural Cross-Lingual Summarizationcited by 64
  11. 2019Long and Diverse Text Generation with Planning-based Hierarchical Variational Modelcited by 62
  12. 2020KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversationcited by 59
4 more
  1. 2021CPM-2: Large-scale Cost-effective Pre-trained Language Modelscited by 52
  2. 2020GLGE: A New General Language Generation Evaluation Benchmarkcited by 47
  3. 2019Multi-channel Reverse Dictionary Modelcited by 16
  4. 2021CCPM: A Chinese Classical Poetry Matching Datasetcited by 15

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