102 citations · 314 across the 20 of their papers we have counts for
20 papers
Deep EEG Super-Resolution: Upsampling EEG Spatial Resolution with Generative Adversarial Networks
Isaac Corley, Yufei Huang
Electroencephalography (EEG) activity contains a wealth of information about what is happening within the human brain. Recording more of this data has the potential to unlock endle…
Large Language Model Alignment: A Survey
Tianhao Shen, Renren Jin, Yufei Huang +6
Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various c…
Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs
Lirong Wu, Haitao Lin, Yufei Huang +1
To bridge the gaps between topology-aware Graph Neural Networks (GNNs) and inference-efficient Multi-Layer Perceptron (MLPs), GLNN proposes to distill knowledge from a well-trained…
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework
Lirong Wu, Haitao Lin, Yufei Huang +2
Recent years have witnessed the great success of Graph Neural Networks (GNNs) in handling graph-related tasks. However, MLPs remain the primary workhorse for practical industrial a…
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration
Haitao Lin, Yufei Huang, Odin Zhang +4
In recent years, AI-assisted drug design methods have been proposed to generate molecules given the pockets' structures of target proteins. Most of them are atom-level-based method…
CCPL: Cross-modal Contrastive Protein Learning
Jiangbin Zheng, Stan Z. Li
Effective protein representation learning is crucial for predicting protein functions. Traditional methods often pretrain protein language models on large, unlabeled amino acid seq…