Many types of data from fields including natural language processing,
co...
The use of language-model-based question-answering systems to aid humans...
We present the results of the NLP Community Metasurvey. Run from May to ...
Current QA systems can generate reasonable-sounding yet false answers wi...
For a natural language understanding benchmark to be useful in research,...
To enable building and testing models on long-document comprehension, we...
It is well documented that NLP models learn social biases present in the...
Crowdsourcing is widely used to create data for common natural language
...
Many crowdsourced NLP datasets contain systematic gaps and biases that a...
Pretrained language models, especially masked language models (MLMs) hav...
This paper explores the task Natural Language Understanding (NLU) by loo...
The GLUE benchmark (Wang et al., 2019b) is a suite of language understan...
The GLUE benchmark (Wang et al., 2019b) is a suite of language understan...
In the last year, new models and methods for pretraining and transfer
le...
Latent tree learning models learn to parse a sentence without syntactic
...
This paper presents the results of the RepEval 2017 Shared Task, which
e...
This paper introduces the Multi-Genre Natural Language Inference (MultiN...