291 citations · 3k across the 73 of their papers we have counts for
13 papers · 1 filter
Learning to Organize Knowledge and Answer Questions with N-Gram Machines
Fan Yang, Jiazhong Nie, William W. Cohen +1
Though deep neural networks have great success in natural language processing, they are limited at more knowledge intensive AI tasks, such as open-domain Question Answering (QA). E…
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov +1
We formulate language modeling as a matrix factorization problem, and show that the expressiveness of Softmax-based models (including the majority of neural language models) is lim…
Quasar: Datasets for Question Answering by Search and Reading
Bhuwan Dhingra, Kathryn Mazaitis, William W. Cohen
We present two new large-scale datasets aimed at evaluating systems designed to comprehend a natural language query and extract its answer from a large corpus of text. The Quasar-S…
TensorLog: Deep Learning Meets Probabilistic DBs
William W. Cohen, Fan Yang, Kathryn Rivard Mazaitis
We present an implementation of a probabilistic first-order logic called TensorLog, in which classes of logical queries are compiled into differentiable functions in a neural-netwo…
Explainable Entity-based Recommendations with Knowledge Graphs
Rose Catherine, Kathryn Mazaitis, Maxine Eskenazi +1
Explainable recommendation is an important task. Many methods have been proposed which generate explanations from the content and reviews written for items. When review text is una…
Good Semi-supervised Learning that Requires a Bad GAN
Zihang Dai, Zhilin Yang, Fan Yang +2
Semi-supervised learning methods based on generative adversarial networks (GANs) obtained strong empirical results, but it is not clear 1) how the discriminator benefits from joint…