53 citations · 97 across the 10 of their papers we have counts for
5 papers · 1 filter
Asking Crowdworkers to Write Entailment Examples: The Best of Bad Options
Clara Vania, Ruijie Chen, Samuel R. Bowman
Large-scale natural language inference (NLI) datasets such as SNLI or MNLI have been created by asking crowdworkers to read a premise and write three new hypotheses, one for each p…
CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models
Nikita Nangia, Clara Vania, Rasika Bhalerao +1
Pretrained language models, especially masked language models (MLMs) have seen success across many NLP tasks. However, there is ample evidence that they use the cultural biases tha…
VisualSem: A High-quality Knowledge Graph for Vision and Language
Houda Alberts, Teresa Huang, Yash Deshpande +4
An exciting frontier in natural language understanding (NLU) and generation (NLG) calls for (vision-and-) language models that can efficiently access external structured knowledge…
Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?
Yada Pruksachatkun, Jason Phang, Haokun Liu +6
While pretrained models such as BERT have shown large gains across natural language understanding tasks, their performance can be improved by further training the model on a data-r…
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too
Jason Phang, Iacer Calixto, Phu Mon Htut +5
Intermediate-task training---fine-tuning a pretrained model on an intermediate task before fine-tuning again on the target task---often improves model performance substantially on…