An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation

EMNLP 2018 Liangchen LuoJingjing XuJunyang LinQi ZengXu Sun

Generating semantically coherent responses is still a major challenge in dialogue generation. Different from conventional text generation tasks, the mapping between inputs and responses in conversations is more complicated, which highly demands the understanding of utterance-level semantic dependency, a relation between the whole meanings of inputs and outputs... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Text Generation DailyDialog AEM+Attention BLEU-1 14.17 # 1
Text Generation DailyDialog AEM+Attention BLEU-2 5.69 # 1
Text Generation DailyDialog AEM+Attention BLEU-3 3.78 # 1
Text Generation DailyDialog AEM+Attention BLEU-4 2.84 # 1