79 citations · 583 across the 45 of their papers we have counts for
12 papers · 1 filter
Few Shot Network Compression via Cross Distillation
Haoli Bai, Jiaxiang Wu, Irwin King +1
Model compression has been widely adopted to obtain light-weighted deep neural networks. Most prevalent methods, however, require fine-tuning with sufficient training data to ensur…
Improving Question Generation With to the Point Context
Jingjing Li, Yifan Gao, Lidong Bing +2
Question generation (QG) is the task of generating a question from a reference sentence and a specified answer within the sentence. A major challenge in QG is to identify answer-re…
Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
Yifan Gao, Piji Li, Irwin King +1
We study the problem of generating interconnected questions in question-answering style conversations. Compared with previous works which generate questions based on a single sente…
Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards
Hou Pong Chan, Wang Chen, Lu Wang +1
Generating keyphrases that summarize the main points of a document is a fundamental task in natural language processing. Although existing generative models are capable of predicti…
Topic-Aware Neural Keyphrase Generation for Social Media Language
Yue Wang, Jing Li, Hou Pong Chan +3
A huge volume of user-generated content is daily produced on social media. To facilitate automatic language understanding, we study keyphrase prediction, distilling salient informa…
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
Jiani Zhang, Xingjian Shi, Shenglin Zhao +1
We propose a new STAcked and Reconstructed Graph Convolutional Networks (STAR-GCN) architecture to learn node representations for boosting the performance in recommender systems, e…