2019
Novel positional encodings to enable tree-based transformers
NeurIPS 2019poster
Neural models optimized for tree-based problems are of great value in tasks like SQL query extraction and program synthesis. On sequence-structured data, transformers have been shown to learn relationships across arbitrary pairs of positions more reliably than recurrent models. Motivated by this pro…