A Framework for Spontaneous Brillouin Noise: Unveiling Fundamental Limits in Brillouin Metrology

Posted by dbos UCAS

Kavli Affiliate: Long Zhang | First 5 Authors: Simeng Jin, Shuai Yao, Zhisheng Yang, Zixuan Du, Xiaobin Hong | Summary: Spontaneous Brillouin scattering (SpBS) provides a non-contact tool for probing the mechanical and thermodynamic properties of materials, enabling important applications such as distributed optical fiber sensing and high-resolution Brillouin microscopy. Achieving metrological precision in these […]


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Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Zijie Qiu, Jiaqi Wei, Xiang Zhang, Sheng Xu, Kai Zou | Summary: De novo peptide sequencing is a critical task in proteomics. However, the performance of current deep learning-based methods is limited by the inherent complexity of mass spectrometry data and the heterogeneous distribution of noise signals, […]


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DECT-based Space-Squeeze Method for Multi-Class Classification of Metastatic Lymph Nodes in Breast Cancer

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Hai Jiang, Chushan Zheng, Jiawei Pan, Yuanpin Zhou, Qiongting Liu | Summary: Background: Accurate assessment of metastatic burden in axillary lymph nodes is crucial for guiding breast cancer treatment decisions, yet conventional imaging modalities struggle to differentiate metastatic burden levels and capture comprehensive lymph node characteristics. This […]


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SUFFICIENT: A scan-specific unsupervised deep learning framework for high-resolution 3D isotropic fetal brain MRI reconstruction

Posted by dbos Peking

Kavli Affiliate: Li Xin Li | First 5 Authors: Jiangjie Wu, Lixuan Chen, Zhenghao Li, Xin Li, Saban Ozturk | Summary: High-quality 3D fetal brain MRI reconstruction from motion-corrupted 2D slices is crucial for clinical diagnosis. Reliable slice-to-volume registration (SVR)-based motion correction and super-resolution reconstruction (SRR) methods are essential. Deep learning (DL) has demonstrated potential […]


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Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning

Posted by dbos UCAS

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Kai Zhang, Mengxian Lyu, Hongfang Liu, Lichao Sun | Summary: To advance biomedical vison-language model capabilities through scaling up, fine-tuning, and instruction tuning, develop vision-language models with improved performance in handling long text, explore strategies to efficiently adopt vision language models for diverse multi-modal biomedical […]


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Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning

Posted by dbos UCAS

Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Kai Zhang, Mengxian Lyu, Hongfang Liu, Lichao Sun | Summary: To advance biomedical vison-language model capabilities through scaling up, fine-tuning, and instruction tuning, develop vision-language models with improved performance in handling long text, explore strategies to efficiently adopt vision language models for diverse multi-modal biomedical […]


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The Double Tidal Disruption Event AT 2022dbl Implies That at Least Some “Standard” Optical TDEs are Partial Disruptions

Posted by dbos MIT

Kavli Affiliate: Michael Fausnaugh | First 5 Authors: Lydia Makrygianni, Iair Arcavi, Megan Newsome, Ananya Bandopadhyay, Eric R. Coughlin | Summary: Flares produced following the tidal disruption of stars by supermassive black holes can reveal the properties of the otherwise dormant majority of black holes and the physics of accretion. In the past decade, a […]


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Towards Realistic Detection Pipelines of Taiji: New Challenges in Data Analysis and High-Fidelity Simulations of Space-Borne Gravitational Wave Antenna

Posted by dbos Peking

Kavli Affiliate: Xian Chen | First 5 Authors: Minghui Du, Pengcheng Wang, Ziren Luo, Wen-Biao Han, Xin Zhang | Summary: Taiji, a Chinese space-based gravitational wave detection project, aims to explore the millihertz gravitational wave universe with unprecedented sensitivity, targeting astrophysical and cosmological sources including Galactic binaries, massive black hole binaries, extreme mass-ratio inspirals, and […]


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Flow Matching based Sequential Recommender Model

Posted by dbos Cornell

Kavli Affiliate: Dan Luo | First 5 Authors: Feng Liu, Lixin Zou, Xiangyu Zhao, Min Tang, Liming Dong | Summary: Generative models, particularly diffusion model, have emerged as powerful tools for sequential recommendation. However, accurately modeling user preferences remains challenging due to the noise perturbations inherent in the forward and reverse processes of diffusion-based methods. […]


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