Neural substrates underlying the expectation of rewards resulting from effortful exertion

Kavli Affiliate: Vikram Chib | Authors: Aram Kim and Vikram S. Chib | Summary: Expectations as a reference point shape our decisions to motivate effortful activity. Despite the important role of reference points in human performance, little is known about how the brain processes expectations to guide motivated exertion. Participants completed a reward-based effort task […]


Continue.. Neural substrates underlying the expectation of rewards resulting from effortful exertion

Spatial domain detection using contrastive self-supervised learning for spatial multi-omics technologies

Kavli Affiliate: Brian Caffo Keri Martinowich | Authors: Jianing Yao, Jinglun Yu, Brian Caffo, Stephanie Cerceo Page, Keri Martinowich and Stephanie C Hicks | Summary: Recent advances in spatially-resolved single-omics and multi-omics technologies have led to the emergence of computational tools to detect or predict spatial domains. Additionally, histological images and immunofluorescence (IF) staining of […]


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Integration of cognitive tasks into artificial general intelligence test for large models

Kavli Affiliate: Jia Liu | First 5 Authors: Youzhi Qu, Chen Wei, Penghui Du, Wenxin Che, Chi Zhang | Summary: During the evolution of large models, performance evaluation is necessarily performed to assess their capabilities and ensure safety before practical application. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united […]


Continue.. Integration of cognitive tasks into artificial general intelligence test for large models

Integration of cognitive tasks into artificial general intelligence test for large models

Kavli Affiliate: Jia Liu | First 5 Authors: Youzhi Qu, Chen Wei, Penghui Du, Wenxin Che, Chi Zhang | Summary: During the evolution of large models, performance evaluation is necessarily performed on the intermediate models to assess their capabilities, and on the well-trained model to ensure safety before practical application. However, current model evaluations mainly […]


Continue.. Integration of cognitive tasks into artificial general intelligence test for large models

Integration of cognitive tasks into artificial general intelligence test for large models

Kavli Affiliate: Jia Liu | First 5 Authors: Youzhi Qu, Chen Wei, Penghui Du, Wenxin Che, Chi Zhang | Summary: During the evolution of large models, performance evaluation is necessarily performed on the intermediate models to assess their capabilities, and on the well-trained model to ensure safety before practical application. However, current model evaluations mainly […]


Continue.. Integration of cognitive tasks into artificial general intelligence test for large models

First detection of polarization in X-rays for PSR B0540-69 and its nebula

Kavli Affiliate: Herman L. Marshall | First 5 Authors: Fei Xie, Josephine Wong, Fabio La Monaca, Roger W. Romani, Jeremy Heyl | Summary: We report on X-ray polarization measurements of the extra-galactic Crab-like PSR B0540-69 and its Pulsar Wind Nebula (PWN) in the Large Magellanic Cloud (LMC), using a ~850 ks Imaging X-ray Polarimetry Explorer […]


Continue.. First detection of polarization in X-rays for PSR B0540-69 and its nebula

First detection of polarization in X-rays for PSR B0540-69 and its nebula

Kavli Affiliate: Herman L. Marshall | First 5 Authors: Fei Xie, Josephine Wong, Fabio La Monaca, Roger W. Romani, Jeremy Heyl | Summary: We report on X-ray polarization measurements of the extra-galactic Crab-like PSR B0540-69 and its Pulsar Wind Nebula (PWN) in the Large Magellanic Cloud (LMC), using a ~850 ks Imaging X-ray Polarimetry Explorer […]


Continue.. First detection of polarization in X-rays for PSR B0540-69 and its nebula

Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques

Kavli Affiliate: Zhuo Li | First 5 Authors: Qiheng Mao, Zemin Liu, Chenghao Liu, Zhuo Li, Jianling Sun | Summary: The integration of Large Language Models (LLMs) with Graph Representation Learning (GRL) marks a significant evolution in analyzing complex data structures. This collaboration harnesses the sophisticated linguistic capabilities of LLMs to improve the contextual understanding […]


Continue.. Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques