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20242026
most citedSpectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

math.PR2026

Fractional Macroscopic Fluctuation Theory for a Superdiffusive Ginzburg-Landau dynamics

Cedric Bernardin, Patricia Gonçalves, João Pedro Mangi

We investigate a boundary-driven Ginzburg-Landau dynamics with long-range interactions. In the hydrodynamic limit, the macroscopic evolution is governed by a fractional heat equati…

cs.CV2025

PhysCorr: Dual-Reward DPO for Physics-Constrained Text-to-Video Generation with Automated Preference Selection

Peiyao Wang, Weining Wang, Qi Li

Recent advances in text-to-video generation have achieved impressive perceptual quality, yet generated content often violates fundamental principles of physical plausibility - mani…

cs.CV2025

SVQA-R1: Reinforcing Spatial Reasoning in MLLMs via View-Consistent Reward Optimization

Peiyao Wang, Haibin Ling

Spatial reasoning remains a critical yet underdeveloped capability in existing vision-language models (VLMs), especially for Spatial Visual Question Answering (Spatial VQA) tasks t…

cs.LG2025★ 1 cited

Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table

Yufeng Wang, Peiyao Wang, Lu Wei +4

X-ray Absorption Spectroscopy (XAS) is a powerful technique for probing local atomic environments, yet its interpretation remains limited by the need for expert-driven analysis, co…

q-bio.BM2025

XDIP: A Curated X-ray Absorption Spectrum Dataset for Iron-Containing Proteins

Yufeng Wang, Peiyao Wang, Lu Wei +6

Earth-abundant iron is an essential metal in regulating the structure and function of proteins. This study presents the development of a comprehensive X-ray Absorption Spectroscopy…

cs.CV2024★ 1 cited

Efficient Temporal Action Segmentation via Boundary-aware Query Voting

Peiyao Wang, Yuewei Lin, Erik Blasch +2

Although the performance of Temporal Action Segmentation (TAS) has improved in recent years, achieving promising results often comes with a high computational cost due to dense inp…