46 citations · 75 across the 26 of their papers we have counts for
28 papers
ChargeBD: Character-Aware Heterogeneous Agent Reasoning for Guided Engineering in Battery Development
Rui Huang, Zekun Jiang, Mengran Hou +4
Redox-flow battery (RFB) research spans molecular design, electrolyte optimization, electrode and membrane materials, stack operation, system management, and safety analysis, makin…
MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry
Dongxin Lyu, Jingbo Zhou, Hongxin Xiang +2
De novo peptide sequencing from tandem mass spectrometry is pivotal in proteomics, enabling identification of novel peptides without reference databases. While recent Transformer-b…
RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
Hao Wu, Yuqi Li, Yuan Gao +10
Existing robot video world models are typically trained with low-level objectives such as reconstruction and perceptual similarity, which are poorly aligned with the capabilities t…
PolyReal: A Benchmark for Real-World Polymer Science Workflows
Wanhao Liu, Weida Wang, Jiaqing Xie +12
Multimodal Large Language Models (MLLMs) excel in general domains but struggle with complex, real-world science. We posit that polymer science, an interdisciplinary field spanning…
SciDataCopilot: An Agentic Data Preparation Framework for AGI-driven Scientific Discovery
Jiyong Rao, Yicheng Qiu, Jiahui Zhang +29
The current landscape of AI for Science (AI4S) is predominantly anchored in large-scale textual corpora, where generative AI systems excel at hypothesis generation, literature sear…
Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo Study
Shengdu Chai, Chen Lin, Xinyang Dong +4
The crystal structure of high-pressure solid hydrogen remains a fundamental open problem. Although the research frontier has mostly shifted toward ultra-high pressure phases above…
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Wanghan Xu, Yuhao Zhou, Yifan Zhou +104
Despite advances in scientific AI, a coherent framework for Scientific General Intelligence (SGI)-the ability to autonomously conceive, investigate, and reason across scientific do…
Chem-R: Learning to Reason as a Chemist
Weida Wang, Benteng Chen, Di Zhang +14
Although large language models (LLMs) have significant potential to advance chemical discovery, current LLMs lack core chemical knowledge, produce unreliable reasoning trajectories…
InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames
Haorui Li, Weitao Du, Yuqiang Li +2
Transformer-based autoregressive models have emerged as a unifying paradigm across modalities such as text and images, but their extension to 3D molecule generation remains underex…
RIV: Recursive Introspection Mask Diffusion Vision Language Model
YuQian Li, Limeng Qiao, Lin Ma
Mask Diffusion-based Vision Language Models (MDVLMs) have achieved remarkable progress in multimodal understanding tasks. However, these models are unable to correct errors in gene…
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics
Weida Wang, Dongchen Huang, Jiatong Li +32
We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than…
A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
Ming Hu, Chenglong Ma, Wei Li +117
Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…
CheMatAgent: Enhancing LLMs for Chemistry and Materials Science through Tree-Search Based Tool Learning
Mengsong Wu, YaFei Wang, Yidong Ming +7
Large language models (LLMs) have recently demonstrated promising capabilities in chemistry tasks while still facing challenges due to outdated pretraining knowledge and the diffic…
SELT: Self-Evaluation Tree Search for LLMs with Task Decomposition
Mengsong Wu, Di Zhang, Yuqiang Li +2
While Large Language Models (LLMs) have achieved remarkable success in a wide range of applications, their performance often degrades in complex reasoning tasks. In this work, we i…
On Support Samples of Next Word Prediction
Yuqian Li, Yupei Du, Yufang Liu +3
Language models excel in various tasks by making complex decisions, yet understanding the rationale behind these decisions remains a challenge. This paper investigates \emph{data-c…
Control-R: Towards controllable test-time scaling
Di Zhang, Weida Wang, Junxian Li +10
This paper target in addressing the challenges of underthinking and overthinking in long chain-of-thought (CoT) reasoning for Large Reasoning Models (LRMs) by introducing Reasoning…
MOOSE-Chem3: Toward Experiment-Guided Hypothesis Ranking via Simulated Experimental Feedback
Wanhao Liu, Zonglin Yang, Jue Wang +7
Hypothesis ranking is vital for automated scientific discovery, especially in cost-intensive, throughput-limited natural science domains. Current methods focus on pre-experiment ra…
ChemMLLM: Chemical Multimodal Large Language Model
Qian Tan, Di Zhang, Dongzhan Zhou +8
Recent years have seen rapid progress in multimodal large language models (MLLMs) in the field of chemistry. However, chemical MLLMs that can handle cross-modal understanding and g…
AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use
Yaotian Yang, Yiwen Tang, Yizhe Chen +14
Reconstructing atomistic crystal structures from a single noisy STEM projection is an ill-posed inverse problem: multiple lattices can explain similar contrast, and purely feed-for…
ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition
Yujie Liu, Zonglin Yang, Tong Xie +7
Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses remains unexamined due to the lac…
Biology-Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models
Haonan He, Yuchen Ren, Yining Tang +12
Large language models (LLMs) have shown remarkable capabilities in general domains, but their application to multi-omics biology remains underexplored. To address this gap, we intr…
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
Di Zhang, Jianbo Wu, Jingdi Lei +9
This paper presents an advanced mathematical problem-solving framework, LLaMA-Berry, for enhancing the mathematical reasoning ability of Large Language Models (LLMs). The framework…
CrystalX: High-accuracy Crystal Structure Analysis Using Deep Learning
Kaipeng Zheng, Weiran Huang, Wanli Ouyang +2
Atomic structure analysis of crystalline materials is a paramount endeavor in both chemical and material sciences. This sophisticated technique necessitates not only a solid founda…
MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses
Zonglin Yang, Wanhao Liu, Ben Gao +6
Scientific discovery plays a pivotal role in advancing human society, and recent progress in large language models (LLMs) suggests their potential to accelerate this process. Howev…