23 citations · 104 across the 24 of their papers we have counts for
26 papers
Beyond Benchmark Accuracy: A Diagnostic Test for LLM Chemical Prediction
Yanyi Su, Yu Zeng, Hongshuai Wang +3
LLMs have achieved strong performance on chemical prediction benchmarks. However, existing evaluation methods typically provide target entity identity information directly, making…
Agentic-MatriBO: Capability-Compiled Agentic Bayesian Optimization for Materials and Chemical Design
Yu Zeng, Yuchuan Chen, Ziyue Zhang +5
Materials and chemical optimization must choose the next synthesis, characterization, or high-fidelity simulation from sequential observations under a limited budget. Large languag…
NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning
Yanyi Su, Hongshuai Wang, Zhifeng Gao +1
Olfaction lies at the intersection of chemical structure, neural encoding, and linguistic perception, yet existing representation methods fail to fully capture this pathway. Curren…
ProtoCycle: Reflective Tool-Augmented Planning for Text-Guided Protein Design
Yutang Ge, Guojiang Zhao, Sihang Li +7
Designing proteins that satisfy natural language functional requirements is a central goal in protein engineering. A straightforward baseline is to fine-tune generic instruction-tu…
Scaffold-Conditioned Preference Triplets for Controllable Molecular Optimization with Large Language Models
Yi Xiong, Liang Xiong, Xiaohong Ji +4
Molecular property optimization is central to drug discovery, yet many deep learning methods rely on black-box scoring and offer limited control over scaffold preservation, often p…
On the Design of One-step Diffusion via Shortcutting Flow Paths
Haitao Lin, Peiyan Hu, Minsi Ren +5
Recent advances in few-step diffusion models have demonstrated their efficiency and effectiveness by shortcutting the probabilistic paths of diffusion models, especially in trainin…
Multi-Alignment Contrastive Learning for Enzyme--Reaction Retrieval
Gengmo Zhou, Feng Yu, Wenda Wang +4
Identifying enzymes that catalyze target biochemical reactions is a key step in computational enzyme discovery and biocatalyst design. Recent representation-learning methods formul…
Masked-and-Reordered Self-Supervision for Reinforcement Learning from Verifiable Rewards
Zhen Wang, Zhifeng Gao, Guolin Ke
Test-time scaling has been shown to substantially improve large language models' (LLMs) mathematical reasoning. However, for a large portion of mathematical corpora, especially the…
NMR-Solver: Automated Structure Elucidation via Large-Scale Spectral Matching and Physics-Guided Fragment Optimization
Yongqi Jin, Jun-Jie Wang, Fanjie Xu +6
Nuclear Magnetic Resonance (NMR) spectroscopy is one of the most powerful and widely used tools for molecular structure elucidation in organic chemistry. However, the interpretatio…
Uni-Mol3: A Multi-Molecular Foundation Model for Advancing Organic Reaction Modeling
Lirong Wu, Junjie Wang, Zhifeng Gao +6
Organic reaction, the foundation of modern chemical industry, is crucial for new material development and drug discovery. However, deciphering reaction mechanisms and modeling mult…
MolReasoner: Toward Effective and Interpretable Reasoning for Molecular LLMs
Guojiang Zhao, Zixiang Lu, Yutang Ge +13
Large Language Models (LLMs) have shown impressive performance across various domains, but their ability to perform molecular reasoning remains underexplored. Existing methods most…
SynBridge: Bridging Reaction States via Discrete Flow for Bidirectional Reaction Prediction
Haitao Lin, Junjie Wang, Zhifeng Gao +5
The essence of a chemical reaction lies in the redistribution and reorganization of electrons, which is often manifested through electron transfer or the migration of electron pair…
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
Shuqi Lu, Xiaohong Ji, Bohang Zhang +5
Molecular pretrained representations (MPR) has emerged as a powerful approach for addressing the challenge of limited supervised data in applications such as drug discovery and mat…
Unified Cross-Scale 3D Generation and Understanding via Autoregressive Modeling
Shuqi Lu, Haowei Lin, Lin Yao +6
3D structure modeling is essential across scales, enabling applications from fluid simulation and 3D reconstruction to protein folding and molecular docking. Yet, despite shared 3D…
Intelligent System for Automated Molecular Patent Infringement Assessment
Yaorui Shi, Sihang Li, Taiyan Zhang +12
Automated drug discovery offers significant potential for accelerating the development of novel therapeutics by substituting labor-intensive human workflows with machine-driven pro…
Auto-resolving the atomic structure at van der Waals interfaces using a generative model
Wenqiang Huang, Yuchen Jin, Zhemin Li +12
The high-resolution visualization of atomic structures is significant for understanding the relationship between the microscopic configurations and macroscopic properties of materi…
Uni-ELF: A Multi-Level Representation Learning Framework for Electrolyte Formulation Design
Boshen Zeng, Sian Chen, Xinxin Liu +7
Advancements in lithium battery technology heavily rely on the design and engineering of electrolytes. However, current schemes for molecular design and recipe optimization of elec…
Uni-Mol2: Exploring Molecular Pretraining Model at Scale
Xiaohong Ji, Zhen Wang, Zhifeng Gao +4
In recent years, pretraining models have made significant advancements in the fields of natural language processing (NLP), computer vision (CV), and life sciences. The significant…
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction
Eric Alcaide, Zhifeng Gao, Guolin Ke +4
In recent years, machine learning (ML) methods have emerged as promising alternatives for molecular docking, offering the potential for high accuracy without incurring prohibitive…
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Hengxing Cai, Xiaochen Cai, Shuwen Yang +14
In scientific research and its application, scientific literature analysis is crucial as it allows researchers to build on the work of others. However, the fast growth of scientifi…
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Hengxing Cai, Xiaochen Cai, Junhan Chang +20
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of…
End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction
Qingsi Lai, Fanjie Xu, Lin Yao +8
Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most auto…
Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction
Zhifeng Gao, Xiaohong Ji, Guojiang Zhao +4
Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in d…
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+
Shuqi Lu, Zhifeng Gao, Di He +2
Recent developments in deep learning have made remarkable progress in speeding up the prediction of quantum chemical (QC) properties by removing the need for expensive electronic s…