From the 1 of 1.3k papers with an AI index.
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- Peking UniversityCN335 papers
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- Institute of High Energy PhysicsCN194 papers
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- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT184 papers
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24 papers · 1 filter
UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors
Houyuan Chen, Hong Li, Xianghao Kong +8
Recent progress has shown that video diffusion models (VDMs) can be repurposed for diverse multimodal graphics tasks. However, existing methods often train separate models for each…
Calibrating the Role of Entanglement in Variational Quantum Algorithms from a Geometric Perspective
Chunxiao Du, Yang Zhou, Zhichen Huang +4
Calibrating the role of entanglement in quantum algorithms is a crucial task in the development of quantum computing. Most existing studies have primarily focused on how the static…
Spatiotemporal Degradation-Aware 3D Gaussian Splatting for Realistic Underwater Scene Reconstruction
Shaohua Liu, Ning Gao, Zuoya Gu +3
Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatiotemporal degradations in und…
Carrier scattering considerations and thermoelectric power factors of half-Heuslers
Rajeev Dutt, Bhawna Sahni, Yao Zhao +7
The electronic and thermoelectric (TE) transport properties of 13 n-type and p-type half-Heusler alloys are computationally examined using Boltzmann transport. The electronic scatt…
Auxiliary counterterms and their role in effective field theory
Manuel Pavon Valderrama
Effective field theories include contact-range interactions (or counterterms) for two reasons: representing the unknown short-range physics in a model independent manner and ensuri…
Generative AI Agent Empowered Power Allocation for HAP Propulsion and Communication Systems
Xiaoyu Xing, Dingyi Lu, Peng Yang +3
High altitude platforms (HAPs) are emerging as a key enabler for 6G coverage, yet limited energy must be split between propulsion and communications. Most prior HAP studies ignore…