Coreference resolution models are often evaluated on multiple datasets.
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Many state-of-the-art natural language understanding (NLU) models are ba...
There are many ways to express similar things in text, which makes evalu...
In a conversational question answering scenario, a questioner seeks to
e...
Understanding natural language requires common sense, one aspect of whic...
The Winograd Schema Challenge (WSC) and variants inspired by it have bec...
Modeling semantic plausibility requires commonsense knowledge about the ...
In this paper, we propose a method for incorporating world knowledge (li...
We propose a two-agent game wherein a questioner must be able to conjure...
The NLP and ML communities have long been interested in developing model...
We introduce a new benchmark task for coreference resolution, Hard-CoRe,...
We introduce an automatic system that achieves state-of-the-art results ...
This paper presents the Frames dataset (Frames is available at
http://da...
We present NewsQA, a challenging machine comprehension dataset of over
1...
User simulation is essential for generating enough data to train a
stati...
Natural language generation plays a critical role in spoken dialogue sys...
In this paper, we propose to use deep policy networks which are trained ...
We present the EpiReader, a novel model for machine comprehension of tex...
Understanding unstructured text is a major goal within natural language
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