5 citations · 11 across the 19 of their papers we have counts for
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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…
SynWeather: Weather Observation Data Synthesis across Multiple Regions and Variables via a General Diffusion Transformer
Kaiyi Xu, Junchao Gong, Zhiwang Zhou +7
With the advancement of meteorological instruments, abundant data has become available. Current approaches are typically focus on single-variable, single-region tasks and primarily…
LO-SDA: Latent Optimization for Score-based Atmospheric Data Assimilation
Jing-An Sun, Hang Fan, Junchao Gong +8
Data assimilation (DA) plays a pivotal role in numerical weather prediction by systematically integrating sparse observations with model forecasts to estimate optimal atmospheric i…
SynCast: Synergizing Contradictions in Precipitation Nowcasting via Diffusion Sequential Preference Optimization
Kaiyi Xu, Junchao Gong, Wenlong Zhang +3
Precipitation nowcasting based on radar echoes plays a crucial role in monitoring extreme weather and supporting disaster prevention. Although deep learning approaches have achieve…
DAWP: A framework for global observation forecasting via Data Assimilation and Weather Prediction in satellite observation space
Junchao Gong, Jingyi Xu, Ben Fei +7
Weather prediction is a critical task for human society, where impressive progress has been made by training artificial intelligence weather prediction (AIWP) methods with reanalys…
SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines
Yizhou Wang, Chen Tang, Han Deng +29
We present a scientific reasoning foundation model that aligns natural language with heterogeneous scientific representations. The model is pretrained on a 206B-token corpus spanni…
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…
A Self-Evolving AI Agent System for Climate Science
Zijie Guo, Jiong Wang, Fenghua Ling +19
Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere know…
XiChen: A global weather observation-to-forecast machine learning system via four-dimensional variational gradient-guided flexible assimilation
Wuxin Wang, Weicheng Ni, Lilan Huang +13
Machine Learning (ML) has shown great promise in revolutionizing weather forecasting, yet most ML systems still rely on initial conditions generated by Numerical Weather Prediction…
ReconMOST: Multi-Layer Sea Temperature Reconstruction with Observations-Guided Diffusion
Yuanyi Song, Pumeng Lyu, Ben Fei +3
Accurate reconstruction of ocean is essential for reflecting global climate dynamics and supporting marine meteorological research. Conventional methods face challenges due to spar…
Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning
Yuhao Zhou, Yiheng Wang, Xuming He +26
Scientific discoveries increasingly rely on complex multimodal reasoning based on information-intensive scientific data and domain-specific expertise. Empowered by expert-level sci…
EarthSE: A Benchmark for Evaluating Earth Scientific Exploration Capability of LLMs
Wanghan Xu, Xiangyu Zhao, Yuhao Zhou +5
Advancements in Large Language Models (LLMs) drive interest in scientific applications, necessitating specialized benchmarks such as Earth science. Existing benchmarks either prese…
Align-DA: Align Score-based Atmospheric Data Assimilation with Multiple Preferences
Jing-An Sun, Hang Fan, Junchao Gong +8
Data assimilation (DA) aims to estimate the full state of a dynamical system by combining partial and noisy observations with a prior model forecast, commonly referred to as the ba…
OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data
Fengxiang Wang, Mingshuo Chen, Xuming He +15
Existing benchmarks for multimodal learning in Earth science offer limited, siloed coverage of Earth's spheres and their cross-sphere interactions, typically restricting evaluation…
MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs
Xiangyu Zhao, Wanghan Xu, Bo Liu +7
The rapid advancement of multimodal large language models (MLLMs) offers new opportunities for complex scientific challenges, yet their application in earth science-especially at t…
Manalyzer: End-to-end Automated Meta-analysis with Multi-agent System
Wanghan Xu, Wenlong Zhang, Fenghua Ling +8
Meta-analysis is a systematic research methodology that synthesizes data from multiple existing studies to derive comprehensive conclusions. This approach not only mitigates limita…
Satellite Observations Guided Diffusion Model for Accurate Meteorological States at Arbitrary Resolution
Siwei Tu, Ben Fei, Weidong Yang +7
Accurate acquisition of surface meteorological conditions at arbitrary locations holds significant importance for weather forecasting and climate simulation. Due to the fact that m…
Physically Consistent Global Atmospheric Data Assimilation with Machine Learning in Latent Space
Hang Fan, Lei Bai, Ben Fei +6
Data assimilation (DA) integrates observations with model forecasts to produce optimized atmospheric states, whose physical consistency is critical for stable weather forecasting a…