2 citations · 2 across the 14 of their papers we have counts for
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cs.LG2024★ 2 cited
On the Comparison between Multi-modal and Single-modal Contrastive Learning
Wei Huang, Andi Han, Yongqiang Chen +3
Multi-modal contrastive learning with language supervision has presented a paradigm shift in modern machine learning. By pre-training on a web-scale dataset, multi-modal contrastiv…
cs.LG2024
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
Dake Bu, Wei Huang, Andi Han +4
Transformer-based large language models (LLMs) have displayed remarkable creative prowess and emergence capabilities. Existing empirical studies have revealed a strong connection b…
cs.LG2024
On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
Bingrui Li, Wei Huang, Andi Han +4
The Adam optimizer is widely used for transformer optimization in practice, which makes understanding the underlying optimization mechanisms an important problem. However, due to t…