SocialIQA is the first large-scale benchmark with 38k crowdsourced questions testing commonsense about social interactions, where pretrained language models trail humans by over 20% but transfer to improve performance on Winograd Schemas and COPA.
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CodeBERT pre-trains a bimodal model on code and text pairs plus unimodal data to achieve state-of-the-art results on natural language code search and code documentation generation.
The first shared task on MT robustness received 23 submissions showing up to +22.33 BLEU gains on noisy Reddit data, with strong human-BLEU correlation.
Builds an improved PIO dataset and reports performance gains from domain-specific BERT embeddings plus ensembles in multi-label PIO classification.
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CodeBERT: A Pre-Trained Model for Programming and Natural Languages
CodeBERT pre-trains a bimodal model on code and text pairs plus unimodal data to achieve state-of-the-art results on natural language code search and code documentation generation.