Removing dropout from single-epoch language model pretraining improves downstream task performance and model editability across multiple architectures and benchmarks.
InProceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 38–45, Online
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Drop Dropout on Single-Epoch Language Model Pretraining
Removing dropout from single-epoch language model pretraining improves downstream task performance and model editability across multiple architectures and benchmarks.