2 citations · 3 across the 11 of their papers we have counts for
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cs.LG2024
Unlocking Continual Learning Abilities in Language Models
Wenyu Du, Shuang Cheng, Tongxu Luo +5
Language models (LMs) exhibit impressive performance and generalization capabilities. However, LMs struggle with the persistent challenge of catastrophic forgetting, which undermin…
cs.CL2024★ 2 cited
Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training
Wenyu Du, Tongxu Luo, Zihan Qiu +5
LLMs are computationally expensive to pre-train due to their large scale. Model growth emerges as a promising approach by leveraging smaller models to accelerate the training of la…
cs.LG2024★ 1 cited
m2mKD: Module-to-Module Knowledge Distillation for Modular Transformers
Ka Man Lo, Yiming Liang, Wenyu Du +5
Modular neural architectures are gaining attention for their powerful generalization and efficient adaptation to new domains. However, training these models poses challenges due to…