6 citations · 8 across the 5 of their papers we have counts for
6 papers
CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion
Jiaze Song, Runhao Zhao, Minghao Xu +2
Inferring gene regulatory networks (GRNs) from single-cell transcriptomic data is crucial for biological discovery, yet existing approaches suffer from a fundamental misalignment w…
Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training
Minghao Xu, Jiaze Song, Keming Wu +3
Understanding the various properties of glycans with machine learning has shown some preliminary promise. However, previous methods mainly focused on modeling the backbone structur…
HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation
Ling Yang, Xinchen Zhang, Ye Tian +4
The remarkable success of the autoregressive paradigm has made significant advancement in Multimodal Large Language Models (MLLMs), with powerful models like Show-o, Transfusion an…
EditWorld: Simulating World Dynamics for Instruction-Following Image Editing
Ling Yang, Bohan Zeng, Jiaming Liu +4
Diffusion models have significantly improved the performance of image editing. Existing methods realize various approaches to achieve high-quality image editing, including but not…
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
Minghao Xu, Yunteng Geng, Yihang Zhang +3
Glycans are basic biomolecules and perform essential functions within living organisms. The rapid increase of functional glycan data provides a good opportunity for machine learnin…
ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training
Le Zhuo, Zewen Chi, Minghao Xu +5
We propose ProtLLM, a versatile cross-modal large language model (LLM) for both protein-centric and protein-language tasks. ProtLLM features a unique dynamic protein mounting mecha…