5 papers
PACUTE: Phonology-, Affix-, and Character-level Understanding of Tokens for Filipino
Jann Railey Montalan, David Demitri Africa, Jimson Paulo Layacan +3
Large language models (LLMs) process text as sequences of subword tokens, which can obscure the character-level and morphological structure that underlies word formation. This limi…
Robust Bias Evaluation with FilBBQ: A Filipino Bias Benchmark for Question-Answering Language Models
Lance Calvin Lim Gamboa, Yue Feng, Mark Lee
With natural language generation becoming a popular use case for language models, the Bias Benchmark for Question-Answering (BBQ) has grown to be an important benchmark format for…
Social Bias in Multilingual Language Models: A Survey
Lance Calvin Lim Gamboa, Yue Feng, Mark Lee
Pretrained multilingual models exhibit the same social bias as models processing English texts. This systematic review analyzes emerging research that extends bias evaluation and m…
Bias Attribution in Filipino Language Models: Extending a Bias Interpretability Metric for Application on Agglutinative Languages
Lance Calvin Lim Gamboa, Yue Feng, Mark Lee
Emerging research on bias attribution and interpretability have revealed how tokens contribute to biased behavior in language models processing English texts. We build on this line…
Filipino Benchmarks for Measuring Sexist and Homophobic Bias in Multilingual Language Models from Southeast Asia
Lance Calvin Lim Gamboa, Mark Lee
Bias studies on multilingual models confirm the presence of gender-related stereotypes in masked models processing languages with high NLP resources. We expand on this line of rese…