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Back when I started working in Filipino NLP, my standard approach in training models is to encode linguistics knowledge via meticulous data annotation, feature engineering, and extensive testing. Take calamanCy for example: we spent countless …
I was invited to give a talk to a graduate-level NLP class about my work on Filipino resources. It was fun preparing and giving that talk because I was able to synthesize my thoughts and …
Preference data is a staple in the final step of the LLM training pipeline. During RLHF, we train a reward model by showing pairs of chosen and rejected model outputs so that it can teach …