Author

Ben Fei

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Preprint Aug 2026

Diagnosing and narrowing the simulation-to-real gap in powder X-ray diffraction with a wet-dry agentic loop

Powder X-ray diffraction (PXRD) is the routine probe of crystalline matter, yet its analysis is the rate-limiting step as laboratories automate acquisition. Deep-learning analyzers excel on simulated patterns and degrade on measured ones. This simulation-to-real gap is structural, not additive: synthetic denoising give...

Shaoguang Wang, Weiyu Guo, Ben Fei et al. · 0 citations

Preprint Sep 2026

SpecCoder: Specification-Aware Code Generation with Curriculum Dual-Task Reinforcement Learning

Large language models (LLMs) have made substantial progress in code generation but still struggle with challenging programming tasks that require understanding rich natural language requirements. These requirements often specify problem goals, input/output formats, constraints, examples, and edge cases. Overlooking eve...

Yi-Xuan Li, Min Huang, Jia-Jing Wang et al. · 0 citations

2026

The Geometric Nature and a Free Proxy for Flow-Matching Uncertainty

This work provides a geometric interpretation of FM uncertainty in the velocity field, showing that uncertainty manifests as deviation from an ideal affine-isotropic contraction field, and introduces denoising acceleration ( accel), a highly-generalizable and cost-free uncertainty proxy that measures the bending of the...

Zi-Yang Rao, Yi-Ren Zhao, Wei-Yu Guo et al. · arXiv.org · 0 citations

Aug 2026

FengYuan: An End-to-End Global Weather Forecasting Model Driven by Multi-Source Observational Data

The complete end-to-end system of FengYuan achieves forecast quality very close to the reanalysis-driven version while consistently outperforming IFS throughout the 10-day forecast period, demonstrating that FengYuan successfully bridges observations to forecasts while maintaining high accuracy.

Zhao-Ming Liang, Yang Li, Ya-Qiang Wang et al. · Journal of Meteorological Re... · 0 citations

2025

LoRA-EnVar: Parameter-Efficient Hybrid Ensemble Variational Assimilation for Weather Forecasting

Experimental results show that LoRA-EnVar significantly improves assimilation accuracy over models assuming static background error distribution and achieves comparable or better performance than full finetuning while reducing the number of trainable parameters by three orders of magnitude.

Yi Xiao, Hang Fan, Kun Chen et al. · Neural Information Processin... · 3 citations

Preprint Aug 2026

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density

ED-DiT, a physics-guided Diffusion Transformer for self-supervised pretraining on electron-density point clouds, demonstrates the effectiveness of physics-guided electron-density pretraining for learning transferable molecular representations.

Shuang Liang, Haocheng Wang, Jiayi Song et al. · 0 citations