Ru He
Vision-language models (VLMs) are increasingly attractive for multimodal quality assessment, but their default reliance on autoregressive text generation and dynamic visual processing is poorly matched to scalar regression under strict…
This paper reports an innovative process to fabricate $\beta$-Ga$_{2}$O$_{3}$ microtubes and nanomembranes based on ion implantation in (100)-oriented single-crystals. We show that, under specific flux and fluence conditions, the…
While $\beta$-Ga$_2$O$_3$ is considered a promising wide bandgap semiconductor, the impact of ion-induced defect formation and anisotropic elasticity remains poorly understood. Here, we combine a simulation and experiment X-ray diffraction…
Disorder-induced ordering and unprecedentedly high radiation tolerance in $\gamma$-phase of gallium oxide is a recent spectacular discovery at the intersection of the fundamental physics and electronic applications. Importantly, by far,…
Radiation tolerance is determined as the ability of crystalline materials to withstand the accumulation of the radiation induced disorder. Nevertheless, for sufficiently high fluences, in all by far known semiconductors it ends up with…
$\beta$ phase gallium oxide ($\beta$-$\rm Ga_2O_3$) demonstrates tremendous potential for electronics applications and offers promising prospects for integration into future space systems with the necessity of high radiation resistance.…
Recently reported remarkably high radiation tolerance of $\gamma$/$\beta$-Ga$_2$O$_3$ double-polymorphic structure brings this ultrawide bandgap semiconductor to the frontiers of power electronics applications that are able to operate in…
Disordering of solids typically leads to amorphization, but polymorph transitions, facilitated by favorable atomic rearrangements, may temporarily help to maintain long-range periodicity in the solid state. In far-from-equilibrium…
The core of self-supervised learning for pre-training language models includes pre-training task design as well as appropriate data augmentation. Most data augmentations in language model pre-training are context-independent. A seminal…
Our goal is to build general representation (embedding) for each user and each product item across Alibaba's businesses, including Taobao and Tmall which are among the world's biggest e-commerce websites. The representation of users and…
Pre-trained language models, such as BERT, have achieved significant accuracy gain in many natural language processing tasks. Despite its effectiveness, the huge number of parameters makes training a BERT model computationally very…
We study the Bayesian model averaging approach to learning Bayesian network structures (DAGs) from data. We develop new algorithms including the first algorithm that is able to efficiently sample DAGs according to the exact structure…
We study the problem of learning Bayesian network structures from data. Koivisto and Sood (2004) and Koivisto (2006) presented algorithms that can compute the exact marginal posterior probability of a subnetwork, e.g., a single edge, in…
We study the problem of learning Bayesian network structures from data. We develop an algorithm for finding the k-best Bayesian network structures. We propose to compute the posterior probabilities of hypotheses of interest by Bayesian…