Baolin Peng

Towards Neural Network-based Reasoning

2015 · arXiv (Cornell University)

We propose Neural Reasoner, a framework for neural network-based reasoning over natural language sentences. Given a question, Neural Reasoner can infer over multiple supporting facts and find an answer to the question in specific forms. …

Deep Dyna-Q: Integrating Planning for Task-Completion Dialogue Policy Learning

2018

Training a task-completion dialogue agent via reinforcement learning (RL) is costly because it requires many interactions with real users. One common alternative is to use a user simulator. However, a user simulator usually lacks the …

Task-oriented Dialogue System for Automatic Diagnosis

2018

Zhongyu Wei, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-fai Wong, Xiangying Dai. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 2018.

Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space

2020

When trained effectively, the Variational Autoencoder (VAE) In this paper, we propose the first large-scale language VAE model OPTIMUS 1 . A universal latent embedding space for sentences is first pre-trained on large text corpus, …