# Generating Chinese Classical Poems with RNN Encoder-Decoder

arXiv: https://arxiv.org/abs/1604.01537 · HTML: https://mlsanity.com/paper/1604.01537/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Apr 2016.

## Built on by (most cited first, 16 of 16)

- [CharPoet: A Chinese Classical Poetry Generation System Based on Token-free LLM](https://mlsanity.com/paper/2401.03512/) (2024)
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- [Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk](https://mlsanity.com/paper/2207.00735/) (2022)
- [WenyanGPT: A Large Language Model for Classical Chinese Tasks](https://mlsanity.com/paper/2504.20609/) (2025)
- [SP-GPT2: Semantics Improvement in Vietnamese Poetry Generation](https://mlsanity.com/paper/2110.15723/) (2021)
- [Generate and Revise: Reinforcement Learning in Neural Poetry](https://mlsanity.com/paper/2102.04114/) (2021)
- [Multi-Modal Experience Inspired AI Creation](https://mlsanity.com/paper/2209.02427/) (2022)
- [PoeTone: A Framework for Constrained Generation of Structured Chinese Songci with LLMs](https://mlsanity.com/paper/2508.02515/) (2025)
- [TPPoet: Transformer-Based Persian Poem Generation using Minimal Data and Advanced Decoding Techniques](https://mlsanity.com/paper/2312.02125/) (2023)
- [POEMetric: The Last Stanza of Humanity](https://mlsanity.com/paper/2604.03695/) (2026)
- [AfriKI: Machine-in-the-Loop Afrikaans Poetry Generation](https://mlsanity.com/paper/2103.16190/) (2021)
- [Song Form-aware Full-Song Text-to-Lyrics Generation with Multi-Level Granularity Syllable Count Control](https://mlsanity.com/paper/2411.13100/) (2024)
- [Who Wrote This Line? Evaluating the Detection of LLM-Generated Classical Chinese Poetry](https://mlsanity.com/paper/2604.10101/) (2026)

## Abstract (arXiv)

We take the generation of Chinese classical poem lines as a sequence-to-sequence learning problem, and build a novel system based on the RNN Encoder-Decoder structure to generate quatrains (Jueju in Chinese), with a topic word as input. Our system can jointly learn semantic meaning within a single line, semantic relevance among lines in a poem, and the use of structural, rhythmical and tonal patterns, without utilizing any constraint templates. Experimental results show that our system outperforms other competitive systems. We also find that the attention mechanism can capture the word associations in Chinese classical poetry and inverting target lines in training can improve performance.