699 citations · 783 across the 13 of their papers we have counts for
5 papers · 1 filter
Memformer: A Memory-Augmented Transformer for Sequence Modeling
Qingyang Wu, Zhenzhong Lan, Kun Qian +3
Transformers have reached remarkable success in sequence modeling. However, these models have efficiency issues as they need to store all the history token-level representations as…
Perception Score, A Learned Metric for Open-ended Text Generation Evaluation
Jing Gu, Qingyang Wu, Zhou Yu
Automatic evaluation for open-ended natural language generation tasks remains a challenge. Existing metrics such as BLEU show a low correlation with human judgment. We propose a no…
On the Generation of Medical Dialogues for COVID-19
Wenmian Yang, Guangtao Zeng, Bowen Tan +9
Under the pandemic of COVID-19, people experiencing COVID19-related symptoms or exposed to risk factors have a pressing need to consult doctors. Due to hospital closure, a lot of c…
A Tailored Pre-Training Model for Task-Oriented Dialog Generation
Jing Gu, Qingyang Wu, Chongruo Wu +2
The recent success of large pre-trained language models such as BERT and GPT-2 has suggested the effectiveness of incorporating language priors in downstream dialog generation task…
TextGAIL: Generative Adversarial Imitation Learning for Text Generation
Qingyang Wu, Lei Li, Zhou Yu
Generative Adversarial Networks (GANs) for text generation have recently received many criticisms, as they perform worse than their MLE counterparts. We suspect previous text GANs'…