3 citations · 6 across the 8 of their papers we have counts for
10 papers
FLaG: Frequency-Domain Latent-attention Gated Pooling for Token Aggregation
Kewei Li, Rongying Zhang, Xueli Wang +6
Token aggregation converts token-level representations into fixed-dimensional sample representations, but most pooling methods operate only in the original token space. We introduc…
Frequency-Domain Latent Attention Gating for Cross-Domain Token Aggregation
Kewei Li, Rongying Zhang, Xueli Wang +5
Token aggregation is a common bottleneck in models that map token representations to sample-level predictions, yet most pooling methods operate only in the original token domain. W…
HeFS: Helper-Enhanced Feature Selection via Pareto-Optimized Genetic Search
Yusi Fan, Tian Wang, Zhiying Yan +8
Feature selection is a combinatorial optimization problem that is NP-hard. Conventional approaches often employ heuristic or greedy strategies, which are prone to premature converg…
A transformer-BiGRU-based framework with data augmentation and confident learning for network intrusion detection
Jiale Zhang, Pengfei He, Fei Li +5
In today's fast-paced digital communication, the surge in network traffic data and frequency demands robust and precise network intrusion solutions. Conventional machine learning m…
MolProphecy: Bridging Medicinal Chemists' Knowledge and Molecular Pre-Trained Models via a Multi-Modal Framework
Jianping Zhao, Qiong Zhou, Tian Wang +8
MolProphecy is a human-in-the-loop (HITL) multi-modal framework designed to integrate chemists' domain knowledge into molecular property prediction models. While molecular pre-trai…
DeepSelective: Interpretable Prognosis Prediction via Feature Selection and Compression in EHR Data
Ruochi Zhang, Qian Yang, Xiaoyang Wang +10
The rapid accumulation of Electronic Health Records (EHRs) has transformed healthcare by providing valuable data that enhance clinical predictions and diagnoses. While conventional…
Information Entropy Invariance: Enhancing Length Extrapolation in Attention Mechanisms
Kewei Li, Yanwen Kong, Yiping Xu +4
Since the emergence of research on improving the length extrapolation capabilities of large language models in 2021, some studies have made modifications to the scaling factor in t…
AMPCliff: quantitative definition and benchmarking of activity cliffs in antimicrobial peptides
Kewei Li, Yuqian Wu, Yinheng Li +7
Since the mechanism of action of drug molecules in the human body is difficult to reproduce in the in vitro environment, it becomes difficult to reveal the causes of the activity c…
PepHarmony: A Multi-View Contrastive Learning Framework for Integrated Sequence and Structure-Based Peptide Encoding
Ruochi Zhang, Haoran Wu, Chang Liu +8
Recent advances in protein language models have catalyzed significant progress in peptide sequence representation. Despite extensive exploration in this field, pre-trained models t…
PepLand: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids
Ruochi Zhang, Haoran Wu, Yuting Xiu +6
In recent years, the scientific community has become increasingly interested on peptides with non-canonical amino acids due to their superior stability and resistance to proteolyti…