Functional Correspondences in the Human and Marmoset Visual Cortex During Movie Watching: Insights from Correlation, Redundancy, and Synergy

Kavli Affiliate: Ting Xu | First 5 Authors: Qiang Li, Qiang Li, , , | Summary: The world of beauty is deeply connected to the visual cortex, as perception often begins with vision in both humans and marmosets. In this study, to investigate their functional correspondences, we used 13 healthy human volunteers (9 males and […]


Continue.. Functional Correspondences in the Human and Marmoset Visual Cortex During Movie Watching: Insights from Correlation, Redundancy, and Synergy

Functional Correspondences in the Human and Marmoset Visual Cortex During Movie Watching: Insights from Correlation, Redundancy, and Synergy

Kavli Affiliate: Ting Xu | First 5 Authors: Qiang Li, Ting Xu, Vince D. Calhoun, , | Summary: The world of beauty is deeply connected to the visual cortex, as perception often begins with vision in both humans and marmosets. Quantifying functional correspondences in the visual cortex across species can help us understand how information […]


Continue.. Functional Correspondences in the Human and Marmoset Visual Cortex During Movie Watching: Insights from Correlation, Redundancy, and Synergy

Body-Hand Modality Expertized Networks with Cross-attention for Fine-grained Skeleton Action Recognition

Kavli Affiliate: Hsiao-Mei (Sherry) Cho| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:Skeleton-based Human Action Recognition (HAR) is a vital technology in robotics and human-robot interaction. However, most existing methods concentrate primarily on full-body movements and often overlook subtle hand motions that are critical for distinguishing fine-grained actions. Recent work leverages a unified graph […]


Continue.. Body-Hand Modality Expertized Networks with Cross-attention for Fine-grained Skeleton Action Recognition

Deep Contrastive Unlearning for Language Models

Kavli Affiliate: Ke Wang | First 5 Authors: Estrid He, Tabinda Sarwar, Ibrahim Khalil, Xun Yi, Ke Wang | Summary: The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual data and generating human-like languages. Large language models achieve success by being trained on vast […]


Continue.. Deep Contrastive Unlearning for Language Models