Objectives Regular participation in late-life cognitive activities is associated with a reduced risk of dementia. In a prior randomized controlled trial, we demonstrated that increased calligraphy practice improved working memory and strengthened functional connectivity (FC) with…
The spring deployment began with a focus on capturing the initial sea ice conditions.On 28 May, the passage of an Arctic cyclone across the Lincoln Sea on 27 May resulted in a thinning of the cloud layer, relatively low predicted AODs (< 0.1) from the NASA Goddard Earth Observing…
Tight dolomite gas reservoirs are promising exploration targets, yet their evaluation is complicated by multiscale pore-throat heterogeneity and poor seepage connectivity. Here, high-pressure mercury intrusion (HPMI), nuclear magnetic resonance (NMR), scanning electron microscopy…
Objective Grounded in the context of physical education and based on the Technology Acceptance Model (TAM), this study examined the time-separated associations between physical activity self-efficacy and the continuance use of AI learning tools among physical education students t…
Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pressure, non-overlapped communication overhead, and inefficient kernel execution. While most large-sca…
Multimodal humor in memes, cartoons, and comics remains difficult for AI systems because intended meaning depends on non-literal mechanisms, shared cultural knowledge, and communicative intent rather than literal scene description. This survey focuses on visual humor understandin…
Source-free universal domain adaptation (SF-UniDA) adapts a pre-trained source model to an unlabeled target domain under both covariate and label shifts, without access to source data. However, existing SF-UniDA methods rely on inefficient techniques such as threshold tuning and…
Creating photorealistic 3D assets requires bridging the appearance gap between real-world observations and synthetic models. A promising approach is to transfer visual attributes from real images onto synthetic 3D surfaces. Traditional methods struggle with resolution mismatch an…
LiDAR-based collaborative 3D perception in Vehicle-to-Everything (V2X) systems typically relies on fusing bird's-eye-view (BEV) features across agents. However, current BEV representations, typically extracted by LiDAR backbones trained from scratch, are geometry-dominated and la…
Automatic speech recognition (ASR) has become a critical component of modern robotic systems because it is one of the most natural and intuitive ways for humans to interact with robots. A commonly used method is to directly use API services online. But is that all we can do? This…
Large language model (LLM) agents have shown strong decision-making capabilities in long-horizon interactive tasks, yet they still struggle to effectively leverage failed trajectories: full retries incur high interaction costs, while experience retrieval tends to dilute critical…
Online multimodal knowledge editing requires injecting a continual stream of visual-textual corrections into multimodal large language models (MLLMs) with bounded overhead and minimal disruption to unrelated behaviors. Existing editors mainly emphasize edit reliability and long-h…
We present Home3D 1.0, a modular image-to-3D generation system that produces high-quality 3D assets from a single reference image, targeting interior design and e-commerce applications. Given a photograph of a furniture or decor item, the system outputs a mesh with physically-bas…