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cs.CL2023
Structural Transfer Learning in NL-to-Bash Semantic Parsers
Kyle Duffy, Satwik Bhattamishra, Phil Blunsom
Large-scale pre-training has made progress in many fields of natural language processing, though little is understood about the design of pre-training datasets. We propose a method…
cs.CL2023
On "Scientific Debt" in NLP: A Case for More Rigour in Language Model Pre-Training Research
Made Nindyatama Nityasya, Haryo Akbarianto Wibowo, Alham Fikri Aji +4
This evidence-based position paper critiques current research practices within the language model pre-training literature. Despite rapid recent progress afforded by increasingly be…