arxivJun 12

Minimal surfaces, Knots, and Neural Networks

arXiv:2605.26234v2 Announce Type: replace-cross Abstract: A recent conjecture by Joel Fine posits a relationship between the coefficients of the HOMFLY polynomial of a knot $K$ in the 3-sphere $S^3$, and the signed count of minimal surfaces in hyperbolic 4-space $\mathrm{H}^4$ meeting the sphere at

PH1 model #mathematics #machine-learning #geometry Read on arxiv →

arxivMay 25bullish

Scaling-Aware Adapter for Structure-Grounded LLM Reasoning

arXiv:2602.02780v3 Announce Type: replace Abstract: Large language models (LLMs) are enabling reasoning over 2D and 3D structures, yet existing methods remain modality-specific and typically compress structural inputs through sequence-based tokenization or fixed-length query connectors. Such archite

CU1 model #large-language-models #multimodal #reasoning Read on arxiv →

arxivMay 16

Numerical exploration of the range of shape functionals using neural networks

arXiv:2602.14881v2 Announce Type: replace-cross Abstract: We introduce a novel numerical framework for the exploration of Blaschke--Santal\'o diagrams, which are efficient tools characterizing the possible inequalities relating some given shape functionals. We introduce a parametrization of convex b

IN1 model #optimization #neural-networks #geometry Read on arxiv →

Minimal surfaces, Knots, and Neural Networks

Geodesic Flow Matching for Denoising High-Dimensional Structured Representations

Scaling-Aware Adapter for Structure-Grounded LLM Reasoning

Numerical exploration of the range of shape functionals using neural networks