Long Text Generation via Adversarial Training with Leaked Information

24 Sep 2017Jiaxian GuoSidi LuHan CaiWeinan ZhangYong YuJun Wang

Automatically generating coherent and semantically meaningful text has many applications in machine translation, dialogue systems, image captioning, etc. Recently, by combining with policy gradient, Generative Adversarial Nets (GAN) that use a discriminative model to guide the training of the generative model as a reinforcement learning policy has shown promising results in text generation... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Text Generation Chinese Poems LeakGAN BLEU-2 0.881 # 1
Text Generation COCO Captions LeakGAN BLEU-2 0.950 # 1
Text Generation COCO Captions LeakGAN BLEU-3 0.880 # 1
Text Generation COCO Captions LeakGAN BLEU-4 0.778 # 1
Text Generation COCO Captions LeakGAN BLEU-5 0.686 # 1
Text Generation EMNLP2017 WMT LeakGAN BLEU-2 0.956 # 1
Text Generation EMNLP2017 WMT LeakGAN BLEU-3 0.819 # 1
Text Generation EMNLP2017 WMT LeakGAN BLEU-4 0.627 # 1
Text Generation EMNLP2017 WMT LeakGAN BLEU-5 0.498 # 1