We present a novel approach to paraphrase generation that enables precise control and fine-tuning of 40 linguistic attributes for English. Our model is an encoder-decoder architecture that takes as input a source sentence and desired linguistic attributes, and produces paraphrases of the source that satisfy the desired attributes. To guarantee high-quality outputs at inference time, our method is equipped with a quality control mechanism that gradually adjusts the embedding of linguistic attributes to find the nearest and most attainable configuration of desired attributes for paraphrase generation. We evaluate the effectiveness of our method by comparing it to recent controllable generation models. Experimental results demonstrate that the proposed model outperforms baselines in generating paraphrases that satisfy desired linguistic attributes.

翻译：我们提出了一种新颖的复述生成方法，能够对英语的40种语言属性进行精确控制和微调。我们的模型采用编码器-解码器架构，以源语句和期望的语言属性作为输入，生成满足目标属性的源句复述。为保证推理时的高质量输出，本方法配备了质量控制机制，通过逐步调整语言属性的嵌入表示，寻找最接近且最可实现的期望属性配置以生成复述。我们通过将本方法与近期可控生成模型进行对比来评估其有效性。实验结果表明，所提出的模型在生成满足期望语言属性的复述方面优于基线模型。