3 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
Rethinking the Role of Text Complexity in Language Model Pretraining
Dan John Velasco, Matthew Theodore Roque
Improving pretraining data quality and size is known to boost downstream performance, but the role of text complexity--how hard a text is to read--remains less explored. We reduce…
Beyond Repetition: Text Simplification and Curriculum Learning for Data-Constrained Pretraining
Matthew Theodore Roque, Dan John Velasco
Most studies on language model pretraining focus on large datasets, leaving open questions about optimization in data-constrained settings. In such settings, the effects of trainin…
Scaling, Simplification, and Adaptation: Lessons from Pretraining on Machine-Translated Text
Dan John Velasco, Matthew Theodore Roque
Most languages lack sufficient data for large-scale monolingual pretraining, creating a "data wall." Multilingual pretraining helps but is limited by language imbalance and the "cu…
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89
Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…