Tootfinder

LeanGeo: Formalizing Competitional Geometry problems in Lean
Chendong Song, Zihan Wang, Frederick Pu, Haiming Wang, Xiaohan Lin, Junqi Liu, Jia Li, Zhengying Liu
https://arxiv.org/abs/2508.14644

LeanGeo: Formalizing Competitional Geometry problems in Lean
Geometry problems are a crucial testbed for AI reasoning capabilities. Most existing geometry solving systems cannot express problems within a unified framework, thus are difficult to integrate with other mathematical fields. Besides, since most geometric proofs rely on intuitive diagrams, verifying geometry problems is particularly challenging. To address these gaps, we introduce LeanGeo, a unified formal system for formalizing and solving competition-level geometry problems within the Lean 4 …

Hey LGBTQIA community!
I'm sharing my trans and gender-fluid journey over at my Pixelfed.
You can check out my profile at: @…
#GenderFluid

🇺🇦 #NowPlaying on KEXP's #90TEEN
Gunn-Truscinski Duo:
🎵 Shell
#GunnTruscinskiDuo
https://gunntruscinskiduo.bandcamp.com/track/shell
https://open.spotify.com/track/372cRraoXERnLhXNOYayWR

ExtraGS: Geometric-Aware Trajectory Extrapolation with Uncertainty-Guided Generative Priors
Kaiyuan Tan, Yingying Shen, Haohui Zhu, Zhiwei Zhan, Shan Zhao, Mingfei Tu, Hongcheng Luo, Haiyang Sun, Bing Wang, Guang Chen, Hangjun Ye
https://arxiv.org/abs/2508.15529

ExtraGS: Geometric-Aware Trajectory Extrapolation with Uncertainty-Guided Generative Priors
Synthesizing extrapolated views from recorded driving logs is critical for simulating driving scenes for autonomous driving vehicles, yet it remains a challenging task. Recent methods leverage generative priors as pseudo ground truth, but often lead to poor geometric consistency and over-smoothed renderings. To address these limitations, we propose ExtraGS, a holistic framework for trajectory extrapolation that integrates both geometric and generative priors. At the core of ExtraGS is a novel R…

When Algorithms Infer Gender: Revisiting Computational Phenotyping with Electronic Health Records Data
Jessica Gronsbell, Hilary Thurston, Lillian Dong, Vanessa Ferguson, Diksha Sen Chaudhury, Braden O'Neill, Katrina S. Sha, Rebecca Bonneville
https://arxiv.org/abs/2508.14150

When Algorithms Infer Gender: Revisiting Computational Phenotyping with Electronic Health Records Data
Computational phenotyping has emerged as a practical solution to the incomplete collection of data on gender in electronic health records (EHRs). This approach relies on algorithms to infer a patient's gender using the available data in their health record, such as diagnosis codes, medication histories, and information in clinical notes. Although intended to improve the visibility of trans and gender-expansive populations in EHR-based biomedical research, computational phenotyping raises signif…

Holomorphic parabolic geometries on smooth projective varieties
Benjamin McKay
https://arxiv.org/abs/2507.15691 https://arxiv.org/pdf…

Holomorphic parabolic geometries on smooth projective varieties
We classify the holomorphic parabolic geometries on compact complex manifolds of general type. We accomplish this by bounding the numerical dimension of any smooth projective variety in terms of geometric invariants of the flag variety model of any holomorphic parabolic geometry on that variety. Along the way, we uncover foliations and fibrations on smooth projective varieties that admit holomorphic parabolic geometries.

Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
Jacek Karwowski, Frank Nielsen
https://arxiv.org/abs/2508.14369

Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
The extended Gaussian family is the closure of the Gaussian family obtained by completing the Gaussian family with the counterpart elements induced by degenerate covariance or degenerate precision matrices, or a mix of both degeneracies. The parameter space of the extended Gaussian family forms a symmetric positive semi-definite matrix bicone, i.e. two partial symmetric positive semi-definite matrix cones joined at their bases. In this paper, we study the Hilbert geometry of such an open bounde…

As a gender-fluid, bisexual femboy, I figured it’s about time I treated myself to some high heels, starting with wearing them around my apartment!
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GaussianArt: Unified Modeling of Geometry and Motion for Articulated Objects
Licheng Shen, Saining Zhang, Honghan Li, Peilin Yang, Zihao Huang, Zongzheng Zhang, Hao Zhao
https://arxiv.org/abs/2508.14891

GaussianArt: Unified Modeling of Geometry and Motion for Articulated Objects
Reconstructing articulated objects is essential for building digital twins of interactive environments. However, prior methods typically decouple geometry and motion by first reconstructing object shape in distinct states and then estimating articulation through post-hoc alignment. This separation complicates the reconstruction pipeline and restricts scalability, especially for objects with complex, multi-part articulation. We introduce a unified representation that jointly models geometry and …

New #Pixelfed post:
#GenderFluid