8 citations · 20 across the 22 of their papers we have counts for
23 papers
Large Knowledge Model: A Knowledge Foundation for Agentic Science at Scale
Yuan Huang, Sihan Hu, Hongyu Gu +18
Agentic science envisions many autonomous agents investigating concurrently while building on a shared, evolving body of scientific knowledge. This requires a knowledge foundation…
iCoder-27B: Recursive AI-Led Development of Frontier Industrial Coding Model
Cheng Yang, Jiayang Lyu, Shangyuan Liu +8
Recursive AI, the prospect of AI taking an increasingly complete role in building and improving AI, is a crown jewel of AI for AI. Although recursive self-development has become pr…
PRL-Bench: A Comprehensive Benchmark Evaluating LLMs' Capabilities in Frontier Physics Research
Tingjia Miao, Wenkai Jin, Muhua Zhang +19
The paradigm of agentic science requires AI systems to conduct robust reasoning and engage in long-horizon, autonomous exploration. However, current scientific benchmarks remain co…
EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale
Xinyu Zhu, Yuzhu Cai, Zexi Liu +20
The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science. However, common agent infrastructure is repeatedly rebuilt acr…
NMRPeak: a ready-to-use intelligent system for molecular structure elucidation enabled by synergistic cross-modal learning
Fanjie Xu, Jinyuan Hu, Jingxiang Zou +8
One-dimensional nuclear magnetic resonance (NMR) spectroscopy is essential for molecular structure elucidation in organic synthesis, drug discovery, natural product characterizatio…
Experimental Powder X-ray Diffraction Crystal Structure Determination with RealPXRD-Solver
Qi Li, Mingyu Guo, Rui Jiao +14
Determining crystal structures from experimental powder X-ray diffraction data remains challenging because peak overlap, preferred orientation, and impurity phases obscure atomic a…
Innovator-VL: A Multimodal Large Language Model for Scientific Discovery
Zichen Wen, Boxue Yang, Shuang Chen +30
We present Innovator-VL, a scientific multimodal large language model designed to advance understanding and reasoning across diverse scientific domains while maintaining excellent…
From Human Labels to Literature: Semi-Supervised Learning of NMR Chemical Shifts at Scale
Yongqi Jin, Yecheng Wang, Jun-jie Wang +3
Accurate prediction of nuclear magnetic resonance (NMR) chemical shifts is fundamental to spectral analysis and molecular structure elucidation, yet existing machine learning metho…
Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale
Linfeng Zhang, Siheng Chen, Yuzhu Cai +46
AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning with tool use and verification, pointing to a shift from isolated AI-assi…
PhysMaster: Building an Autonomous AI Physicist for Theoretical and Computational Physics Research
Tingjia Miao, Wenkai Jin, Jinxin Tan +22
Advances in LLM reasoning and tool use have enabled agentic science, yet frontier theoretical and computational physics remains challenging because research requires deep domain ex…
Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base
Yu Li, Yuan Huang, Tao Wang +19
Most scientific materials compress reasoning, presenting conclusions while omitting the derivational chains that justify them. This compression hinders verification by lacking expl…
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…
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…
SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam?
Jingyi Chai, Shuo Tang, Rui Ye +8
The rapid advancements of AI agents have ignited the long-held ambition of leveraging them to accelerate scientific discovery. Achieving this goal requires a deep understanding of…
pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation
Jiale Zhao, Pengzhi Mao, Kaifei Wang +12
Deep learning has advanced mass spectrometry data interpretation, yet most models remain feature extractors rather than unified scoring frameworks. We present pUniFind, the first l…
ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning
Zexi Liu, Yuzhu Cai, Xinyu Zhu +6
As AI capabilities advance toward and potentially beyond human-level performance, a natural transition emerges where AI-driven development becomes more efficient than human-centric…
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…
Discovery of High-Temperature Superconducting Ternary Hydrides via Deep Learning
Xiaoyang Wang, Chengqian Zhang, Zhenyu Wang +5
The discovery of novel high-temperature superconductor materials holds transformative potential for a wide array of technological applications. However, the combinatorially vast ch…
Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence
Yingying Sun, Jun A, Zhiwei Liu +59
Artificial intelligence (AI) is transforming scientific research, including proteomics. Advances in mass spectrometry (MS)-based proteomics data quality, diversity, and scale, comb…
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…
Towards a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts
Fanjie Xu, Wentao Guo, Feng Wang +8
The study of structure-spectrum relationships is essential for spectral interpretation, impacting structural elucidation and material design. Predicting spectra from molecular stru…
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…