DiSC-Med: Diffusion-based Semantic Communications for Robust Medical Image Transmission

Posted by klaurent Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Fupei Guo, Fupei Guo, , , | Summary: The rapid development of artificial intelligence has driven smart health with next-generation wireless communication technologies, stimulating exciting applications in remote diagnosis and intervention. To enable a timely and effective response for remote healthcare, efficient transmission of medical data through […]


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Deciphering the Physical Origin of GRB 240825A: A Long GRB Lacking a Bright Supernova

Posted by klaurent Stanford

Kavli Affiliate: Nicola Omodei | Summary:We present a comprehensive multiwavelength analysis of GRB 240825A, a bright gamma-ray burst (GRB) detected by Fermi and Swift, with a prompt duration ($T_rm 90$ ~ 4 sec in 50-300 keV) near the boundary separating short and long GRBs, prompting a detailed investigation into its classification and progenitor. Using classical […]


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Human Strategy Adaptation in Reinforcement Learning Resembles Policy Gradient Ascent

Posted by dbos UCSD / Salk

Kavli Affiliate: Marcelo Mattar | Authors: Hua-Dong Xiong, Li Ji-An, Robert C Wilson and Marcelo G Mattar | Summary: A hallmark of intelligence is the ability to adapt behavior to changing environments, which requires adapting one’s own learning strategies. This phenomenon is known as learning to learn in cognitive science and meta-learning in artificial intelligence. […]


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A sensitive orange fluorescent calcium ion indicator for imaging neural activity

Posted by dbos UCSD / Salk

Kavli Affiliate: Timothy Brown | Authors: Abhi Aggarwal, Heather A. Baker, Celine D. Durst, I-Wen Chen, Pablo de Chambrier, Julia Marie Gonzales, Jonathan S. Marvin, Milene Vandal, Torgny Lundberg, Kenryo Sakoi, Ronak H Patel, Ching-Yao Wang, Frank Visser, Yannick Fouad, Smrithi Sunil, Matthew Wiens, Takuya Terai, Kei Takahashi-Yamashiro, Roger J. Thompson, Timothy A. Brown, Yusuke […]


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The Simons Observatory: Assessing the Impact of Dust Complexity on the Recovery of Primordial $B$-modes

Posted by klaurent Stanford

Kavli Affiliate: Susan E. Clark | First 5 Authors: Yiqi Liu, Yiqi Liu, , , | Summary: We investigate how dust foreground complexity can affect measurements of the tensor-to-scalar ratio, $r$, in the context of the Simons Observatory, using a cross-spectrum component separation analysis. Employing a suite of simulations with realistic Galactic dust emission, we […]


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Discovery of an $rm[Fe/H] sim -4.8$ Star in $Gaia$ XP Spectra

Posted by klaurent MIT

Kavli Affiliate: Anna Frebel | Summary:We report on the discovery of GDR3_526285 ($Gaia$ DR3 Source ID 5262850721755411072), a star with $rm[Fe/H] = -4.82 pm 0.25$ and one of the lowest metal ($textatomic number > 2$) mass fractions ever found ($Z_rm GDR3_526585 lesssim 1.0 times 10^-6$). We first identified it as an ultra metal-poor (UMP; $rm[Fe/H] […]


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DivControl: Knowledge Diversion for Controllable Image Generation

Posted by klaurent Peking

Kavli Affiliate: Jing Wang | First 5 Authors: Yucheng Xie, Yucheng Xie, , , | Summary: Diffusion models have advanced from text-to-image (T2I) to image-to-image (I2I) generation by incorporating structured inputs such as depth maps, enabling fine-grained spatial control. However, existing methods either train separate models for each condition or rely on unified architectures with […]


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LLM4Rail: An LLM-Augmented Railway Service Consulting Platform

Posted by klaurent Peking

Kavli Affiliate: Zhuo Li | First 5 Authors: Zhuo Li, Zhuo Li, , , | Summary: Large language models (LLMs) have significantly reshaped different walks of business. To meet the increasing demands for individualized railway service, we develop LLM4Rail – a novel LLM-augmented railway service consulting platform. Empowered by LLM, LLM4Rail can provide custom modules […]


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FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning

Posted by klaurent Peking

Kavli Affiliate: Zhuo Li | First 5 Authors: Jiajun Cao, Jiajun Cao, , , | Summary: Vision-Language-Action (VLA) models have demonstrated significant potential in complex scene understanding and action reasoning, leading to their increasing adoption in end-to-end autonomous driving systems. However, the long visual tokens of VLA models greatly increase computational costs. Current visual token […]


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