5 citations · 14 across the 14 of their papers we have counts for
16 papers
Equivariant Neural Primal-Dual Assignment for Maximum Common Edge Subgraphs
Jiaqing Xie, Yanchao Li, Zhuo Yang +3
Maximum common edge subgraph (MCES) matching finds a partial vertex correspondence between two labeled graphs that preserves as many labeled edges as possible. Molecular similarity…
Molecular LLM Agents: From Architectural Design to Scientific Autonomy
Jiatong Li, Wengyu Zhang, Weida Wang +8
Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or web environments, molecular LLM a…
MinerU.Chem: A High-Precision System for Optical Chemical Structure and Reaction Recognition
Haote Yang, Jiang Wu, Jingchao Wang +42
In organic chemistry papers and patents, molecular structures, reaction schemes, and experimental conditions are often presented as molecular structure depictions, reaction diagram…
Reachability Is Not Realization: Tracing the Sources of LLM Benchmark Gains
Yanchao Li, Wanhao Liu, Jiaqing Xie +4
Benchmark gains are often treated as evidence of greater LLM capability. Yet the same gain can reflect different changes in model behavior. A model may reach new answers, or produc…
Disagree to Accelerate: Closing the Loop on Diffusion Feature Forecasts
Yanchao Li, Jiaqing Xie, Ben Gao +6
Training-free feature forecasting accelerates diffusion sampling by predicting features at skipped denoising steps. Recent work has mainly focused on designing stronger forecasters…
MolGVR: A Chemistry-Grounded Framework for Text-to-Molecule Generation
Qian Tan, Xuanyu Zhu, Lei Jiang +3
Text-to-molecule generation is typically formulated as a one-shot sequence generation problem, where a model directly maps target descriptions to molecular representations. However…
OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields
Wanhao Liu, Jiaqing Xie, Qian Tan +10
As multimodal language models play an increasingly important role in scientific research, materials science offers a critical testbed due to its interdisciplinary, multimodal, and…
SkillsInjector: Dynamic Skill Context Construction for LLM Agents
Yanchao Li, Wanhao Liu, Ben Gao +5
LLM agents now draw on growing skill libraries to handle complex tasks. However, injecting more skills does not always improve task completion and can even degrade it. Existing met…
NMRTrans: Structure Elucidation from Experimental NMR Spectra via Set Transformers
Liujia Yang, Zhuo Yang, Jiaqing Xie +9
Nuclear Magnetic Resonance (NMR) spectroscopy is fundamental for molecular structure elucidation, yet interpreting spectra at scale remains time-consuming and highly expertise-depe…
MolAct: An Agentic RL Framework for Molecular Editing and Property Optimization
Zhuo Yang, Yeyun Chen, Jiaqing Xie +7
Molecular editing and optimization are multi-step problems that require iteratively improving properties while keeping molecules chemically valid and structurally similar. We frame…
SpectrumWorld: Artificial Intelligence Foundation for Spectroscopy
Zhuo Yang, Jiaqing Xie, Shuaike Shen +13
Deep learning holds immense promise for spectroscopy, yet research and evaluation in this emerging field often lack standardized formulations. To address this issue, we introduce S…
SpecMol: A Spectroscopy-Grounded Foundation Model for Multi-Task Molecular Learning
Shuaike Shen, Jiaqing Xie, Zhuo Yang +6
Large language models have emerged as transformative tools in molecular science, demonstrating remarkable potential in molecular property prediction and de novo molecular design. H…
Chem3DLLM: 3D Multimodal Large Language Models for Chemistry
Lei Jiang, Shuzhou Sun, Biqing Qi +5
In the real world, a molecule is a 3D geometric structure. Compared to 1D SMILES sequences and 2D molecular graphs, 3D molecules represent the most informative molecular modality.…
QCBench: Evaluating Large Language Models on Domain-Specific Quantitative Chemistry
Jiaqing Xie, Weida Wang, Ben Gao +5
Quantitative chemistry is central to modern chemical research, yet the ability of large language models (LLMs) to perform its rigorous, step-by-step calculations remains underexplo…
Reasoning BO: Enhancing Bayesian Optimization with Long-Context Reasoning Power of LLMs
Zhuo Yang, Daolang Wang, Lingli Ge +3
Many real-world scientific and industrial applications require the optimization of expensive black-box functions. Bayesian Optimization (BO) provides an effective framework for suc…
TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets
Jintai Chen, Yaojun Hu, Mingchen Cai +13
Clinical trials are pivotal for developing new medical treatments but typically carry risks such as patient mortality and enrollment failure that waste immense efforts spanning ove…