3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Scaling Parameter-Constrained Language Models with Quality Data
Ernie Chang, Matteo Paltenghi, Yang Li +7
Scaling laws in language modeling traditionally quantify training loss as a function of dataset size and model parameters, providing compute-optimal estimates but often neglecting…
cs.CL2024
Target-Aware Language Modeling via Granular Data Sampling
Ernie Chang, Pin-Jie Lin, Yang Li +6
Language model pretraining generally targets a broad range of use cases and incorporates data from diverse sources. However, there are instances where we desire a model that excels…
cs.CL2022★ 3 cited
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding
Ting Hua, Yilin Shen, Changsheng Zhao +2
Domain classification is the fundamental task in natural language understanding (NLU), which often requires fast accommodation to new emerging domains. This constraint makes it imp…