Four MAFT-based PLMs for Angolan languages report 12.3-point gains over AfroXLMR-base and 3.8-point gains over OFA baselines on downstream tasks.
Small data? no problem! exploring the viability of pretrained multilingual language models for low-resourced languages
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
ANGOFA: Leveraging OFA Embedding Initialization and Synthetic Data for Angolan Language Model
Four MAFT-based PLMs for Angolan languages report 12.3-point gains over AfroXLMR-base and 3.8-point gains over OFA baselines on downstream tasks.