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Learning Dexterous Grasping from Sparse Taxonomy Guidance

arXiv:2604.04138v1 Announce Type: cross Abstract: Dexterous manipulation requires planning a grasp configuration suited to the object and task, which is then executed through coordinated multi-finger

Enhancing behavioral nudges with large language model-based iterative personalization: A field experiment on electricity and hot-water conservation

arXiv:2604.03881v1 Announce Type: cross Abstract: Nudging is widely used to promote behavioral change, but its effectiveness is often limited when recipients must repeatedly translate feedback

Gram-Anchored Prompt Learning for Vision-Language Models via Second-Order Statistics

arXiv:2604.03980v1 Announce Type: cross Abstract: Parameter-efficient prompt learning has become the de facto standard for adapting Vision-Language Models (VLMs) to downstream tasks. Existing approaches predominantly

Unveiling Language Routing Isolation in Multilingual MoE Models for Interpretable Subnetwork Adaptation

arXiv:2604.03592v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models exhibit striking performance disparities across languages, yet the internal mechanisms driving these gaps remain poorly understood. In

15 Years of Augmented Human(s) Research: Where Do We Stand?

arXiv:2604.03715v1 Announce Type: cross Abstract: The Augmented Human vision broadly seeks to improve or expand baseline human functioning through the restoration or extension of physical,

Learning Dexterous Grasping from Sparse Taxonomy Guidance

Enhancing behavioral nudges with large language model-based iterative personalization: A field experiment on electricity and hot-water conservation

Gram-Anchored Prompt Learning for Vision-Language Models via Second-Order Statistics

Unveiling Language Routing Isolation in Multilingual MoE Models for Interpretable Subnetwork Adaptation

15 Years of Augmented Human(s) Research: Where Do We Stand?

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