Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

Kavli Affiliate: Philip Marshall | First 5 Authors: Alex Brooks, Philip Marshall, David Ozog, Md. Wasi-ur- Rahman, Lawrence Stewart | Summary: Modern high-end systems are increasingly becoming heterogeneous, providing users options to use general purpose Graphics Processing Units (GPU) and other accelerators for additional performance. High Performance Computing (HPC) and Artificial Intelligence (AI) applications are […]


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Detecting Acoherence in Radiation Fields

Kavli Affiliate: Frank Wilczek | First 5 Authors: Sreenath K. Manikandan, Frank Wilczek, , , | Summary: We propose simple quantitative criteria, based on counting statistics in resonant harmonic detectors, that probe the quantum mechanical character of radiation fields. They provide, in particular, practical means to test the null hypothesis that a given field is […]


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Intermediate-Mass Black Holes in Green Pea Galaxies (IMBH-GP) I: a Candidate Sample from LAMOST and SDSS

Kavli Affiliate: Linhua Jiang | First 5 Authors: Ruqiu Lin, Zhen-Ya Zheng, Fang-Ting Yuan, Jun-Xian Wang, Chunyan Jiang | Summary: The scaling relation of central massive black holes (MBHs) and their host galaxies is well-studied for supermassive BHs (SMBHs, $M_{rm BH} ge 10^6, M_{rm odot}$). However, this relation has large uncertainties in the mass range […]


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Local HI Absorption towards the Magellanic Cloud foreground using ASKAP

Kavli Affiliate: Susan E. Clark | First 5 Authors: Hiep Nguyen, N. M. McClure-Griffiths, James Dempsey, John M. Dickey, Min-Young Lee | Summary: We present the largest Galactic neutral hydrogen HI absorption survey to date, utilizing the Australian SKA Pathfinder Telescope at an unprecedented spatial resolution of 30”. This survey, GASKAP-HI, unbiasedly targets 2,714 continuum […]


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Explanation of high redshift luminous galaxies from JWST by early dark energy model

Kavli Affiliate: Hu Zhan | First 5 Authors: Jun-Qian Jiang, Weiyang Liu, Hu Zhan, Bin Hu, | Summary: Recent observations from the James Webb Space Telescope (JWST) have uncovered massive galaxies at high redshifts, with their abundance significantly surpassing expectations. This finding poses a substantial challenge to both galaxy formation models and our understanding of […]


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PEAR: Position-Embedding-Agnostic Attention Re-weighting Enhances Retrieval-Augmented Generation with Zero Inference Overhead

Kavli Affiliate: Feng Wang | First 5 Authors: Tao Tan, Yining Qian, Ang Lv, Hongzhan Lin, Songhao Wu | Summary: Large language models (LLMs) enhanced with retrieval-augmented generation (RAG) have introduced a new paradigm for web search. However, the limited context awareness of LLMs degrades their performance on RAG tasks. Existing methods to enhance context […]


Continue.. PEAR: Position-Embedding-Agnostic Attention Re-weighting Enhances Retrieval-Augmented Generation with Zero Inference Overhead

PEAR: Position-Embedding-Agnostic Attention Re-weighting Enhances Retrieval-Augmented Generation with Zero Inference Overhead

Kavli Affiliate: Feng Wang | First 5 Authors: Tao Tan, Yining Qian, Ang Lv, Hongzhan Lin, Songhao Wu | Summary: Large language models (LLMs) enhanced with retrieval-augmented generation (RAG) have introduced a new paradigm for web search. However, the limited context awareness of LLMs degrades their performance on RAG tasks. Existing methods to enhance context […]


Continue.. PEAR: Position-Embedding-Agnostic Attention Re-weighting Enhances Retrieval-Augmented Generation with Zero Inference Overhead

Gravitational Wave Astronomy With TianQin

Kavli Affiliate: Kohei Inayoshi | First 5 Authors: En-Kun Li, Shuai Liu, Alejandro Torres-Orjuela, Xian Chen, Kohei Inayoshi | Summary: The opening of the gravitational wave window has significantly enhanced our capacity to explore the universe’s most extreme and dynamic sector. In the mHz frequency range, a diverse range of compact objects, from the most […]


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Multimodal Misinformation Detection by Learning from Synthetic Data with Multimodal LLMs

Kavli Affiliate: Wei Gao | First 5 Authors: Fengzhu Zeng, Wenqian Li, Wei Gao, Yan Pang, | Summary: Detecting multimodal misinformation, especially in the form of image-text pairs, is crucial. Obtaining large-scale, high-quality real-world fact-checking datasets for training detectors is costly, leading researchers to use synthetic datasets generated by AI technologies. However, the generalizability of […]


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