Orbital-selective band modifications in a charge-ordered kagome metal LuNb$_6$Sn$_6$

Kavli Affiliate: Yi Zhou | First 5 Authors: Rui Lou, Yumeng Zhang, Erjian Cheng, Xiaolong Feng, Alexander Fedorov | Summary: The origin of the charge order in kagome lattice materials has attracted great interest due to the unique electronic structure features connected to kagome networks and the interplay between electron and lattice degrees of freedom. […]


Continue.. Orbital-selective band modifications in a charge-ordered kagome metal LuNb$_6$Sn$_6$

pH-Sensitive Optical Nanocomposites Using Polymer-Coated Gold Nanorods

Kavli Affiliate: Xingde Li | Authors: Yongping Chen and Xingde Li | Summary: This study investigates the synthesis of pH-responsive, reversible nanocomposites comprising polystyrene sulfonate (PSS)-coated gold nanorods and poly(allylamine hydrochloride) (PAH)-coated gold nanorods, along with their optical properties. We observed a pH-dependent swelling/shrinking of the nanocomposites and a dramatic red-shift (~ 60 nm) of […]


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Identifying Instabilities with Quantum Geometry in Flat Band Systems

Kavli Affiliate: Leon Balents | Summary:The absence of a well-defined Fermi surface in flat-band systems challenges the conventional understanding of instabilities toward Landau order based on nesting. We investigate the existence of an intrinsic nesting structure encoded in the band geometry (i.e. the wavefunctions of the flat band(s)), which leads to a maximal susceptibility at […]


Continue.. Identifying Instabilities with Quantum Geometry in Flat Band Systems

Identifying Instabilities with Quantum Geometry in Flat Band Systems

Kavli Affiliate: Leon Balents | Summary:The absence of a well-defined Fermi surface in flat-band systems challenges the conventional understanding of instabilities toward Landau order based on nesting. We investigate the existence of an intrinsic nesting structure encoded in the band geometry (i.e. the wavefunctions of the flat band(s)), which leads to a maximal susceptibility at […]


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Shape My Moves: Text-Driven Shape-Aware Synthesis of Human Motions

Kavli Affiliate: Yi Zhou | First 5 Authors: Ting-Hsuan Liao, Yi Zhou, Yu Shen, Chun-Hao Paul Huang, Saayan Mitra | Summary: We explore how body shapes influence human motion synthesis, an aspect often overlooked in existing text-to-motion generation methods due to the ease of learning a homogenized, canonical body shape. However, this homogenization can distort […]


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HumanDreamer-X: Photorealistic Single-image Human Avatars Reconstruction via Gaussian Restoration

Kavli Affiliate: Lihong Wang | First 5 Authors: Boyuan Wang, Boyuan Wang, , , | Summary: Single-image human reconstruction is vital for digital human modeling applications but remains an extremely challenging task. Current approaches rely on generative models to synthesize multi-view images for subsequent 3D reconstruction and animation. However, directly generating multiple views from a […]


Continue.. HumanDreamer-X: Photorealistic Single-image Human Avatars Reconstruction via Gaussian Restoration

HumanDreamer-X: Photorealistic Single-image Human Avatars Reconstruction via Gaussian Restoration

Kavli Affiliate: Zheng Zhu | First 5 Authors: Boyuan Wang, Runqi Ouyang, Xiaofeng Wang, Zheng Zhu, Guosheng Zhao | Summary: Single-image human reconstruction is vital for digital human modeling applications but remains an extremely challenging task. Current approaches rely on generative models to synthesize multi-view images for subsequent 3D reconstruction and animation. However, directly generating […]


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Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data?

Kavli Affiliate: Peter Ford | Summary:Large language models (LLMs) are increasingly used in the creation of online content, creating feedback loops as subsequent generations of models will be trained on this synthetic data. Such loops were shown to lead to distribution shifts – models misrepresenting the true underlying distributions of human data (also called model […]


Continue.. Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data?

Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data?

Kavli Affiliate: Peter Ford| First 5 Authors: Grgur Kovač, Grgur Kovač, , , | Summary:Large language models (LLMs) are increasingly used in the creation of online content, creating feedback loops as subsequent generations of models will be trained on this synthetic data. Such loops were shown to lead to distribution shifts – models misrepresenting the […]


Continue.. Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data?

Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks

Kavli Affiliate: Axel Scherer| First 5 Authors: Alexander Mattick, Alexander Mattick, , , | Summary:Quantum computing is currently strongly limited by the impact of noise, in particular introduced by the application of two-qubit gates. For this reason, reducing the number of two-qubit gates is of paramount importance on noisy intermediate-scale quantum hardware. To advance towards […]


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