Si Wei

Attention-over-Attention Neural Networks for Reading Comprehension

2017

Cloze-style reading comprehension is a representative problem in mining relationship between document and query. In this paper, we present a simple but novel model called attention-over-attention reader for better solving cloze-style reading comprehension task. The …

Enhancing and Combining Sequential and Tree LSTM for Natural Language Inference.

2016 · arXiv (Cornell University)

Reasoning and inference are central to human and artificial intelligence. Modeling inference in human language is notoriously challenging but is fundamental to natural language understanding and many applications. With the availability of large annotated data, …

Distraction-based neural networks for modeling documents

2016 · International Joint Conference on Artificial Intelligence

Distributed representation learned with neural networks has recently shown to be effective in modeling natural languages at fine granularities such as words, phrases, and even sentences. Whether and how such an approach can be extended …

Enhanced LSTM for Natural Language Inference

2017

Reasoning and inference are central to human and artificial intelligence. Modeling inference in human language is very challenging. With the availability of large annotated data In this paper, we present a new state-of-the-art result, achieving …

Neural Natural Language Inference Models Enhanced with External Knowledge

2018

Modeling natural language inference is a very challenging task. With the availability of large annotated data, it has recently become feasible to train complex models such as neural-network-based inference models, which have shown to achieve …