In this paper, we describe our entry in the gendered pronoun resolution competition which achieved fourth place without data augmentation. Our method is an ensemble system of BERTs which resolves co-reference in an interaction space. We report four insights from our work: BERT's representations involve significant redundancy; modeling interaction effects similar to natural language inference models is useful for this task; there is an optimal BERT layer to extract representations for pronoun resolution; and the difference between the attention weights from the pronoun to the candidate entities was highly correlated with the correct label, with interesting implications for future work.

In this paper, we propose Self Inference Neural Network (SINN), a simple yet efficient sentence encoder which leverages knowledge from recurrent and convolutional neural networks. SINN gathers semantic evidence in an interaction space which is subsequently fused by a shared vector gate to determine the most relevant mixture of contextual information. We evaluate the proposed method on four benchmarks among three NLP tasks. Experimental results demonstrate that our model sets a new state-of-the-art on MultiNLI, Scitail and is competitive on the remaining two datasets over all sentence encoding methods. The encoding and inference process in our model is highly interpretable. Through visualizations of the fusion component, we open the black box of our network and explore the applicability of the base encoding methods case by case.

With thousands of news articles from hundreds of sources distributing and sharing everyday, news consumption and information acquisition have been increasingly difficult for readers. Additionally, the content of news articles are becoming catchy or even inciting to attract readership, harming the accuracy of news reporting. We present Islander, an online news analyzing system for online news. The system allows users to browse trending topics with articles from multiple sources and perspectives. We define several metrics as proxies to news quality, and develop algorithms for automatic estimation. The quality estimation results are delivered through a web interface to news readers for easy access to news and information 1