Photo of Jiwei Li

Artificial intelligence & robotics

Jiwei Li

He uses deep learning in a dialogue system so that the machine is no longer boring in communicating with people

Year Honored


Dialogue robots, called Dialog Systems in the NLP field, are essentially making machines understand human language through machine learning and other AI technologies. Because it relates to in-depth human language, this direction is also a very difficult and comprehensive direction in AI technology. Jiwei Li's innovative work will occupy an important part in the evolution of the dialogue system in coming years.

The undergraduate, who studied at the School of Life Sciences of Peking University, completely "derailed" from the computer field at the Ph.D. stage, and finally found his true love in the sea of computer science, NLP. He became the first person in Stanford's history to spend 3 years in earning a doctorate in computer science.

In 2014, Jiwei Li decided to give up his study at the Department of Biomedical Engineering at Cornell University and join Prof. Dan Jurafsky’s research group, which is a language processing group at the School of Computer Science at Stanford University. Since then, he has worked on paragraph analysis, machine translation, artificial dialogue generation, and has become one of the first group of pioneers who successfully used neural networks to improve dialogue systems.

Jiwei Li completed one task in 2015 to make machine answers more meaningful rather than just returning universal responses such as, "Ha." In the multi-round dialogue, such responses often appear but have no practical significance. His work, "A Diversity-Promoting Objective Function for Neural Conversation Models," explores the possibility of reducing these kinds of nonsense answers by using the mainstream model Seq2Seq in the dialogue generation task to significantly improve the quality of the generated dialogue system.

His paper, "Deep Reinforcement Learning for Dialogue Generation," received by EMNLP in 2016, explores the above issues in greater depth. Jiwei Li's method of training dialogue neural networks with reinforcement learning shows that reinforcement of deep learning can help improve the number of dialogue cycles in the dialogue system and the diversity of words in dialogue.

Now, Jiwei Li has set up his own company, "ShannonAI," in China with the hope that NLP technology can intelligently help upgrade traditional fields, such as finance. At the same time, he will also continue exploring the application of neural networks to NLP, including man-machine dialogue systems based on deep learning, information extraction based on the combination of common sense knowledge and corpus data, the study of interpretable mechanism of deep learning model, natural language semantic unit representation and language generation, and more.