A context-enhanced transformer combined with formulaic expression desensitization for synthetic data generation extracts problem and method sentences from papers, achieving 3.71% and 2.67% macro F1 improvements on two datasets while finding LLM in-context learning unsuitable.
hub
Title resolution pending
1 Pith paper cite this work, alongside 1,520 external citations. Polarity classification is still indexing.
1
Pith paper citing it
1,520
external citations · OpenAlex
hub tools
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Extracting Problem and Method Sentence from Scientific Papers: A Context-enhanced Transformer Using Formulaic Expression Desensitization
A context-enhanced transformer combined with formulaic expression desensitization for synthetic data generation extracts problem and method sentences from papers, achieving 3.71% and 2.67% macro F1 improvements on two datasets while finding LLM in-context learning unsuitable.