1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2024
Why Larger Language Models Do In-context Learning Differently?
Zhenmei Shi, Junyi Wei, Zhuoyan Xu +1
Large language models (LLM) have emerged as a powerful tool for AI, with the key ability of in-context learning (ICL), where they can perform well on unseen tasks based on a brief…
cs.LG2024★ 1 cited
Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
Zhuoyan Xu, Zhenmei Shi, Junyi Wei +3
Foundation models have emerged as a powerful tool for many AI problems. Despite the tremendous success of foundation models, effective adaptation to new tasks, particularly those w…
cs.LG2023
Provable Guarantees for Neural Networks via Gradient Feature Learning
Zhenmei Shi, Junyi Wei, Yingyu Liang
Neural networks have achieved remarkable empirical performance, while the current theoretical analysis is not adequate for understanding their success, e.g., the Neural Tangent Ker…