6 citations · 13 across the 12 of their papers we have counts for
12 papers
Learning the Interaction Prior for Protein-Protein Interaction Prediction: A Model-Agnostic Approach
Ziqi Gao, Chenyi Zi, Zijing Liu +3
Protein-protein interactions (PPIs) are fundamental to cellular function and disease mechanisms. Current learning-based PPI predictors focus on learning powerful protein representa…
ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design
Yulin Zhang, He Cao, Zihao Jiang +6
Designing proteins with desired functions or properties represents a core goal in synthetic biology and drug discovery. Recent advances in protein language models (PLMs) have enabl…
RAPTOR: Ridge-Adaptive Logistic Probes
Ziqi Gao, Yaotian Zhu, Qingcheng Zeng +4
Probing studies what information is encoded in a frozen LLM's layer representations by training a lightweight predictor on top of them. Beyond analysis, probes are often used opera…
Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps
Jiashun Cheng, Aochuan Chen, Nuo Chen +4
Low-Rank Adaptation (LoRA) has emerged as a prominent technique for fine-tuning large foundation models. Despite its successes, the substantial parameter redundancy, which limits t…
Mini-Game Lifetime Value Prediction in WeChat
Aochuan Chen, Yifan Niu, Ziqi Gao +5
The LifeTime Value (LTV) prediction, which endeavors to forecast the cumulative purchase contribution of a user to a particular item, remains a vital challenge that advertisers are…
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
Yifan Niu, Ziqi Gao, Tingyang Xu +5
Exploring chemical space to find novel molecules that simultaneously satisfy multiple properties is crucial in drug discovery. However, existing methods often struggle with trading…
Molecule Generation for Target Protein Binding with Hierarchical Consistency Diffusion Model
Guanlue Li, Chenran Jiang, Ziqi Gao +5
Effective generation of molecular structures, or new chemical entities, that bind to target proteins is crucial for lead identification and optimization in drug discovery. Despite…
Parameter-Efficient Fine-Tuning via Circular Convolution
Aochuan Chen, Jiashun Cheng, Zijing Liu +4
Low-Rank Adaptation (LoRA) has gained popularity for fine-tuning large foundation models, leveraging low-rank matrices and to represent weight changes (i.…
Deep Reinforcement Learning for Modelling Protein Complexes
Ziqi Gao, Tao Feng, Jiaxuan You +4
AlphaFold can be used for both single-chain and multi-chain protein structure prediction, while the latter becomes extremely challenging as the number of chains increases. In this…
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen +4
Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank m…
Protein Multimer Structure Prediction via Prompt Learning
Ziqi Gao, Xiangguo Sun, Zijing Liu +3
Understanding the 3D structures of protein multimers is crucial, as they play a vital role in regulating various cellular processes. It has been empirically confirmed that the mult…
MMTSA: Multimodal Temporal Segment Attention Network for Efficient Human Activity Recognition
Ziqi Gao, Yuntao Wang, Jianguo Chen +4
Multimodal sensors provide complementary information to develop accurate machine-learning methods for human activity recognition (HAR), but introduce significantly higher computati…