1 citations · 1 across the 3 of their papers we have counts for
3 papers
Datasheets Aren't Enough: DataRubrics for Automated Quality Metrics and Accountability
Genta Indra Winata, David Anugraha, Emmy Liu +17
High-quality datasets are fundamental to training and evaluating machine learning models, yet their creation-especially with accurate human annotations-remains a significant challe…
MetaMetrics-MT: Tuning Meta-Metrics for Machine Translation via Human Preference Calibration
David Anugraha, Garry Kuwanto, Lucky Susanto +2
We present MetaMetrics-MT, an innovative metric designed to evaluate machine translation (MT) tasks by aligning closely with human preferences through Bayesian optimization with Ga…
Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity
Eric Khiu, Hasti Toossi, David Anugraha +6
Fine-tuning and testing a multilingual large language model is expensive and challenging for low-resource languages (LRLs). While previous studies have predicted the performance of…