# CCPM: A Chinese Classical Poetry Matching Dataset

arXiv: https://arxiv.org/abs/2106.01979 · HTML: https://mlsanity.com/paper/2106.01979/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 10 references that are in the map.
- First posted on arXiv 3 Jun 2021.

## Builds on (most cited first, 4 of 4)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Ancient-Modern Chinese Translation with a Large Training Dataset](https://mlsanity.com/paper/1808.03738/) (2018)

## Built on by (most cited first, 15 of 15)

- [A Comprehensive Overview of Large Language Models](https://mlsanity.com/paper/2307.06435/) (2023)
- [Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models](https://mlsanity.com/paper/2601.07372/) (2026)
- [CPM-2: Large-scale Cost-effective Pre-trained Language Models](https://mlsanity.com/paper/2106.10715/) (2021)
- [Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought](https://mlsanity.com/paper/2505.15431/) (2025)
- [CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark](https://mlsanity.com/paper/2112.13610/) (2021)
- [CLEVA: Chinese Language Models EVAluation Platform](https://mlsanity.com/paper/2308.04813/) (2023)
- [WYWEB: A NLP Evaluation Benchmark For Classical Chinese](https://mlsanity.com/paper/2305.14150/) (2023)
- [KULTURE Bench: A Benchmark for Assessing Language Model in Korean Cultural Context](https://mlsanity.com/paper/2412.07251/) (2024)
- [ZhuJiu: A Multi-dimensional, Multi-faceted Chinese Benchmark for Large Language Models](https://mlsanity.com/paper/2308.14353/) (2023)
- [InteChar: A Unified Oracle Bone Character List for Ancient Chinese Language Modeling](https://mlsanity.com/paper/2508.15791/) (2025)
- [AncientBench: Towards Comprehensive Evaluation on Excavated and Transmitted Chinese Corpora](https://mlsanity.com/paper/2512.17756/) (2025)
- [LyricSIM: A novel Dataset and Benchmark for Similarity Detection in Spanish Song LyricS](https://mlsanity.com/paper/2306.01325/) (2023)
- [Exploring the Capabilities of ChatGPT in Ancient Chinese Translation and Person Name Recognition](https://mlsanity.com/paper/2312.15304/) (2023)
- [Neo-Classic: A Benchmark for Evaluating Linguistic-Aesthetic Reasoning in Classical Chinese Poetry](https://mlsanity.com/paper/2609.19154/) (2026)
- [Trajectory Soup: Pushing the Compute-Scaling Frontier of LLM Mid-training via Diverse Trajectories](https://mlsanity.com/paper/2609.37169/) (2026)

## Abstract (arXiv)

Poetry is one of the most important art forms of human languages. Recently many studies have focused on incorporating some linguistic features of poetry, such as style and sentiment, into its understanding or generation system. However, there is no focus on understanding or evaluating the semantics of poetry. Therefore, we propose a novel task to assess a model's semantic understanding of poetry by poem matching. Specifically, this task requires the model to select one line of Chinese classical poetry among four candidates according to the modern Chinese translation of a line of poetry. To construct this dataset, we first obtain a set of parallel data of Chinese classical poetry and modern Chinese translation. Then we retrieve similar lines of poetry with the lines in a poetry corpus as negative choices. We name the dataset Chinese Classical Poetry Matching Dataset (CCPM) and release it at https://github.com/THUNLP-AIPoet/CCPM. We hope this dataset can further enhance the study on incorporating deep semantics into the understanding and generation system of Chinese classical poetry. We also preliminarily run two variants of BERT on this dataset as the baselines for this dataset.