1 citations · 4 across the 14 of their papers we have counts for
15 papers
PCEvo: Path-Consistent Molecular Representation via Virtual Evolutionary
Kun Li, Longtao Hu, Yida Xiong +6
Molecular representation learning aims to learn vector embeddings that capture molecular structure and geometry, thereby enabling property prediction and downstream scientific appl…
FP-AbDiff: Improving Score-based Antibody Design by Capturing Nonequilibrium Dynamics through the Underlying Fokker-Planck Equation
Jiameng Chen, Yida Xiong, Kun Li +4
Computational antibody design holds immense promise for therapeutic discovery, yet existing generative models are fundamentally limited by two core challenges: (i) a lack of dynami…
Transport-Coupled Bayesian Flows for Molecular Graph Generation
Yida Xiong, Jiameng Chen, Kun Li +5
Molecular graph generation (MGG) is essentially a multi-class generative task, aimed at predicting categories of atoms and bonds under strict chemical and structural constraints. H…
Antibody Design and Optimization with Multi-scale Equivariant Graph Diffusion Models for Accurate Complex Antigen Binding
Jiameng Chen, Xiantao Cai, Jia Wu +1
Antibody design remains a critical challenge in therapeutic and diagnostic development, particularly for complex antigens with diverse binding interfaces. Current computational met…
KaFT: Knowledge-aware Fine-tuning for Boosting LLMs' Domain-specific Question-Answering Performance
Qihuang Zhong, Liang Ding, Xiantao Cai +3
Supervised fine-tuning (SFT) is a common approach to improve the domain-specific question-answering (QA) performance of large language models (LLMs). However, recent literature rev…
Reasoning-OCR: Can Large Multimodal Models Solve Complex Logical Reasoning Problems from OCR Cues?
Haibin He, Maoyuan Ye, Jing Zhang +4
Large Multimodal Models (LMMs) have become increasingly versatile, accompanied by impressive Optical Character Recognition (OCR) related capabilities. Existing OCR-related benchmar…
3D Human Interaction Generation: A Survey
Siyuan Fan, Wenke Huang, Xiantao Cai +1
3D human interaction generation has emerged as a key research area, focusing on producing dynamic and contextually relevant interactions between humans and various interactive enti…
ELBA-Bench: An Efficient Learning Backdoor Attacks Benchmark for Large Language Models
Xuxu Liu, Siyuan Liang, Mengya Han +5
Generative large language models are crucial in natural language processing, but they are vulnerable to backdoor attacks, where subtle triggers compromise their behavior. Although…
Graph-structured Small Molecule Drug Discovery Through Deep Learning: Progress, Challenges, and Opportunities
Kun Li, Yida Xiong, Hongzhi Zhang +4
Due to their excellent drug-like and pharmacokinetic properties, small molecule drugs are widely used to treat various diseases, making them a critical component of drug discovery.…
Can Molecular Evolution Mechanism Enhance Molecular Representation?
Kun Li, Longtao Hu, Xiantao Cai +2
Molecular evolution is the process of simulating the natural evolution of molecules in chemical space to explore potential molecular structures and properties. The relationships be…
TextIM: Part-aware Interactive Motion Synthesis from Text
Siyuan Fan, Bo Du, Xiantao Cai +2
In this work, we propose TextIM, a novel framework for synthesizing TEXT-driven human Interactive Motions, with a focus on the precise alignment of part-level semantics. Existing m…
Fragment-Masked Diffusion for Molecular Optimization
Kun Li, Xiantao Cai, Jia Wu +4
Molecular optimization is a crucial aspect of drug discovery, aimed at refining molecular structures to enhance drug efficacy and minimize side effects, ultimately accelerating the…
Dual-perspective Cross Contrastive Learning in Graph Transformers
Zelin Yao, Chuang Liu, Xueqi Ma +5
Graph contrastive learning (GCL) is a popular method for leaning graph representations by maximizing the consistency of features across augmented views. Traditional GCL methods uti…
Multi-modal Latent Space Learning for Chain-of-Thought Reasoning in Language Models
Liqi He, Zuchao Li, Xiantao Cai +1
Chain-of-thought (CoT) reasoning has exhibited impressive performance in language models for solving complex tasks and answering questions. However, many real-world questions requi…
Zero-shot Learning of Drug Response Prediction for Preclinical Drug Screening
Kun Li, Yong Luo, Xiantao Cai +2
Conventional deep learning methods typically employ supervised learning for drug response prediction (DRP). This entails dependence on labeled response data from drugs for model tr…