291 citations · 3k across the 73 of their papers we have counts for
7 papers · 2 filters
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…
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks
Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen
Recent papers have shown that neural networks obtain state-of-the-art performance on several different sequence tagging tasks. One appealing property of such systems is their gener…
Linguistic Knowledge as Memory for Recurrent Neural Networks
Bhuwan Dhingra, Zhilin Yang, William W. Cohen +1
Training recurrent neural networks to model long term dependencies is difficult. Hence, we propose to use external linguistic knowledge as an explicit signal to inform the model wh…
A Comparative Study of Word Embeddings for Reading Comprehension
Bhuwan Dhingra, Hanxiao Liu, Ruslan Salakhutdinov +1
The focus of past machine learning research for Reading Comprehension tasks has been primarily on the design of novel deep learning architectures. Here we show that seemingly minor…