Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework

Kavli Affiliate: Jing Wang | First 5 Authors: Mengmeng Zhang, Xingyuan Dai, Yicheng Sun, Jing Wang, Yueyang Yao | Summary: Although the Segment Anything Model (SAM) is highly effective in natural image segmentation, it requires dependencies on prompts, which limits its applicability to medical imaging where manual prompts are often unavailable. Existing efforts to fine-tune […]


Continue.. Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework

Quantum Random Number Generator (QRNG): Theoretical and Experimental Investigations

Kavli Affiliate: Zeeshan Ahmed | First 5 Authors: Zeshan Haider, Muhammad Haroon Saeed, Muhammad Ehsan-ul-Haq Zaheer, Zeeshan Ahmed Alvi, Muhammad Ilyas | Summary: Quantum Random Number Generators (QRNGs) emerged as a promising solution for generating truly random numbers. In the present article, we give an overview of QRNGs highlighting the merits and demerits of various […]


Continue.. Quantum Random Number Generator (QRNG): Theoretical and Experimental Investigations

The Relationship Between Eddington Ratio and Column Density in U/LIRG AGN

Kavli Affiliate: Claudio Ricci | First 5 Authors: Jaya Nagarajan-Swenson, George C. Privon, Aaron S. Evans, Loreto Barcos-Muñoz, Claudio Ricci | Summary: The local X-ray AGN population appears to follow a growth cycle regulated by the AGN’s own radiation, marked by changes in their obscuration and Eddington ratio during accretion events. Because AGN in infrared-selected […]


Continue.. The Relationship Between Eddington Ratio and Column Density in U/LIRG AGN

Rapid rebalancing of co-tuned ensemble activity in the auditory cortex

Kavli Affiliate: Patrick Kanold | Authors: HiJee Kang, Travis Babola and Patrick O Kanold | Summary: Sensory information is represented by small neuronal ensembles in sensory cortices. Neuronal activity shows high trial-by-trial variability in that repeated presentation of the same stimulus, e. g., multiple presentations of the same sound activate differing ensembles in the auditory […]


Continue.. Rapid rebalancing of co-tuned ensemble activity in the auditory cortex

Low-velocity precessing jets can explain observed morphologies in the Twin Radio Galaxy TRG J104454+354055

Kavli Affiliate: Luis C. Ho | First 5 Authors: Santanu Mondal, Gourab Giri, Ravi Joshi, Paul J. Wiita, Gopal-Krishna | Summary: Our understanding of large-scale radio jets in merger systems has been drastically improved in the era of VLA, VLBA/EVN, uGMRT, and MeerKAT. Twin Radio Galaxies (TRGs) are the rare interacting galaxy pairs where both […]


Continue.. Low-velocity precessing jets can explain observed morphologies in the Twin Radio Galaxy TRG J104454+354055

Chicago-Carnegie Hubble Program (CCHP) A Multi-Wavelength Search for the Effects of Metallicity on the Cepheid Distance Scale. Part II: Theoretical Models and Synthetic Spectra

Kavli Affiliate: Wendy L. Freedman | First 5 Authors: Barry F. Madore, Wendy L. Freedman, Kayla Owens, , | Summary: This is the second of two papers exploring the effects of metallicity on the multi-wavelength properties of Cepheids in terms of their multi-wavelength period-luminosity (PL) relations, impacting their use as extragalactic distance indicators, underpinning one […]


Continue.. Chicago-Carnegie Hubble Program (CCHP) A Multi-Wavelength Search for the Effects of Metallicity on the Cepheid Distance Scale. Part II: Theoretical Models and Synthetic Spectra

L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Run He, Jiao Chen, Di Fang, Ming Li | Summary: Class-incremental learning (CIL) enables models to learn new classes continually without forgetting previously acquired knowledge. Multi-label CIL (MLCIL) extends CIL to a real-world scenario where each sample may belong to multiple classes, introducing several challenges: […]


Continue.. L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning