44 citations · 280 across the 48 of their papers we have counts for
6 papers · 1 filter
Interactive Language Learning by Question Answering
Xingdi Yuan, Marc-Alexandre Cote, Jie Fu +4
Humans observe and interact with the world to acquire knowledge. However, most existing machine reading comprehension (MRC) tasks miss the interactive, information-seeking componen…
Interactive Machine Comprehension with Information Seeking Agents
Xingdi Yuan, Jie Fu, Marc-Alexandre Cote +3
Existing machine reading comprehension (MRC) models do not scale effectively to real-world applications like web-level information retrieval and question answering (QA). We argue t…
Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
Yi Tay, Aston Zhang, Luu Anh Tuan +5
Many state-of-the-art neural models for NLP are heavily parameterized and thus memory inefficient. This paper proposes a series of lightweight and memory efficient neural architect…
Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives
Yi Tay, Shuohang Wang, Luu Anh Tuan +6
This paper tackles the problem of reading comprehension over long narratives where documents easily span over thousands of tokens. We propose a curriculum learning (CL) based Point…
TIGS: An Inference Algorithm for Text Infilling with Gradient Search
Dayiheng Liu, Jie Fu, Pengfei Liu +1
Text infilling is defined as a task for filling in the missing part of a sentence or paragraph, which is suitable for many real-world natural language generation scenarios. However…
Graph Neural Networks with Generated Parameters for Relation Extraction
Hao Zhu, Yankai Lin, Zhiyuan Liu +3
Recently, progress has been made towards improving relational reasoning in machine learning field. Among existing models, graph neural networks (GNNs) is one of the most effective…