8 citations · 13 across the 5 of their papers we have counts for
5 papers
InstructProtein: Aligning Human and Protein Language via Knowledge Instruction
Zeyuan Wang, Qiang Zhang, Keyan Ding +4
Large Language Models (LLMs) have revolutionized the field of natural language processing, but they fall short in comprehending biological sequences such as proteins. To address th…
Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment
Zhuo Chen, Lingbing Guo, Yin Fang +6
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting assoc…
NeuralKG-ind: A Python Library for Inductive Knowledge Graph Representation Learning
Wen Zhang, Zhen Yao, Mingyang Chen +2
Since the dynamic characteristics of knowledge graphs, many inductive knowledge graph representation learning (KGRL) works have been proposed in recent years, focusing on enabling…
Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
Wen Zhang, Yushan Zhu, Mingyang Chen +5
Knowledge graphs (KG) are essential background knowledge providers in many tasks. When designing models for KG-related tasks, one of the key tasks is to devise the Knowledge Repres…
Multi-modal Protein Knowledge Graph Construction and Applications
Siyuan Cheng, Xiaozhuan Liang, Zhen Bi +2
Existing data-centric methods for protein science generally cannot sufficiently capture and leverage biology knowledge, which may be crucial for many protein tasks. To facilitate r…