Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect

Despite being impactful on a variety of problems and applications, the generative adversarial nets (GANs) are remarkably difficult to train. This issue is formally analyzed by \cite{arjovsky2017towards}, who also propose an alternative direction to avoid the caveats in the minmax two-player training of GANs. The corresponding algorithm, called Wasserstein GAN (WGAN), hinges on the 1-Lipschitz continuity of the discriminator. In this paper, we propose a novel approach to enforcing the Lipschitz continuity in the training procedure of WGANs. Our approach seamlessly connects WGAN with one of the recent semi-supervised learning methods. As a result, it gives rise to not only better photo-realistic samples than the previous methods but also state-of-the-art semi-supervised learning results. In particular, our approach gives rise to the inception score of more than 5.0 with only 1,000 CIFAR-10 images and is the first that exceeds the accuracy of 90% on the CIFAR-10 dataset using only 4,000 labeled images, to the best of our knowledge.Comment: Accepted as a conference paper in International Conference on Learning Representation(ICLR). Xiang Wei and Boqing Gong contributed equally in this wor

Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect

Despite being impactful on a variety of problems and applications, the generative adversarial nets (GANs) are remarkably difficult to train. This issue is formally analyzed by \cite{arjovsky2017towards}, who also propose an alternative direction to avoid the caveats in the minmax two-player training of GANs. The corresponding algorithm, called Wasserstein GAN (WGAN), hinges on the 1-Lipschitz continuity of the discriminator. In this paper, we propose a novel approach to enforcing the Lipschitz continuity in the training procedure of WGANs. Our approach seamlessly connects WGAN with one of the recent semi-supervised learning methods. As a result, it gives rise to not only better photo-realistic samples than the previous methods but also state-of-the-art semi-supervised learning results. In particular, our approach gives rise to the inception score of more than 5.0 with only 1,000 CIFAR-10 images and is the first that exceeds the accuracy of 90% on the CIFAR-10 dataset using only 4,000 labeled images, to the best of our knowledge.Comment: Accepted as a conference paper in International Conference on Learning Representation(ICLR). Xiang Wei and Boqing Gong contributed equally in this wor

Twisted van der Waals Quantum Materials: Fundamentals, Tunability and Applications

Twisted vdW quantum materials have emerged as a rapidly developing field of 2D semiconductors. These materials establish a new central research area and provide a promising platform for studying quantum phenomena and investigating the engineering of novel optoelectronic properties such as single-photon emission, non-linear optical response, magnon physics, and topological superconductivity. These captivating electronic and optical properties result from, and can be tailored by, the interlayer coupling using moir\'e patterns formed by vertically stacking atomic layers with controlled angle misorientation or lattice mismatch. Their outstanding properties and the high degree of tunability position them as compelling building blocks for both compact quantum-enabled devices and classical optoelectronics. This article offers a comprehensive review of recent advancements in the understanding and manipulation of twisted van der Waals structures and presents a survey of the state-of-the-art research on moir\'e superlattices, encompassing interdisciplinary interests. It delves into fundamental theories, synthesis and fabrication, and visualization techniques, and the wide range of novel physical phenomena exhibited by these structures, with a focus on their potential for practical device integration in applications ranging from quantum information to biosensors, and including classical optoelectronics such as modulators, light emitting diodes (LEDs), lasers, and photodetectors. It highlights the unique ability of moir\'e superlattices to connect multiple disciplines, covering chemistry, electronics, optics, photonics, magnetism, topological and quantum physics. This comprehensive review provides a valuable resource for researchers interested in moir\'e superlattices, shedding light on their fundamental characteristics and their potential for transformative applications in various fields.Comment: 179 pages, 42 figures, Chemical Review

Extraordinary second harmonic generation modulated by divergent strain field in pressurized monolayer domes

The most prominent form of nonlinear optical (NLO) frequency conversion is second harmonic generation (SHG), where incident light interacts with a nonlinear medium producing photons at double the input frequency, which has vast applications in material and biomedical science. Emerging two-dimensional nonlinear optical materials led by transition metal dichalcogenides (TMDs) have fascinating optical and mechanical properties and are highly anticipated to overcome the technical limitations imposed by traditional bulky NLO materials. However, the atomic scale interaction length and low conversion efficiency in TMD materials prevent their further implementation in NLO applications. While some uniaxial strain-engineering studies intensively investigated the anisotropic SHG response in TMDs, they did not realize giant SHG enhancement by exploiting the opto-mechanical characteristics. Herein, we employ proton (H+) irradiation to successfully fabricate large pressurized monolayer TMD domes (d ≥ 10 μm) and conduct a comprehensive investigation and characterization of their SHG performance enhancement. We show that the intensity of SHG is effectively enhanced by around two orders of magnitude at room temperature. Such giant enhancement arises from the distinct separation distance induced by capped pressurized gas and the hemi-spherical morphology, enabling constructive optical interference. Moreover, the unique divergent strain field in TMD domes promotes the first experimental study on the anisotropic nonlinear optical behavior based on biaxial strain conditions in terms of varying strain orientation and relative weights. Our work demonstrates a promising system with enhanced NLO performance and well-preserved biocompatibility, paving a way toward the future nano-scaled quantum optics design and biomedical applications

VideoGLUE: Video General Understanding Evaluation of Foundation Models

We evaluate existing foundation models video understanding capabilities using a carefully designed experiment protocol consisting of three hallmark tasks (action recognition, temporal localization, and spatiotemporal localization), eight datasets well received by the community, and four adaptation methods tailoring a foundation model (FM) for a downstream task. Moreover, we propose a scalar VideoGLUE score (VGS) to measure an FMs efficacy and efficiency when adapting to general video understanding tasks. Our main findings are as follows. First, task-specialized models significantly outperform the six FMs studied in this work, in sharp contrast to what FMs have achieved in natural language and image understanding. Second,video-native FMs, whose pretraining data contains the video modality, are generally better than image-native FMs in classifying motion-rich videos, localizing actions in time, and understanding a video of more than one action. Third, the video-native FMs can perform well on video tasks under light adaptations to downstream tasks(e.g., freezing the FM backbones), while image-native FMs win in full end-to-end finetuning. The first two observations reveal the need and tremendous opportunities to conduct research on video-focused FMs, and the last confirms that both tasks and adaptation methods matter when it comes to the evaluation of FMs

Efficient and Layer-Dependent Exciton Pumping across Atomically Thin Organic–Inorganic Type-I Heterostructures

The fundamental light–matter interactions in monolayer transition metal dichalcogenides might be significantly engineered by hybridization with their organic counterparts, enabling intriguing optoelectronic applications. Here, atomically thin organic–inorganic (O–I) heterostructures, comprising monolayer MoSe2 and mono‐/few‐layer single‐crystal pentacene samples, are fabricated. These heterostructures show type‐I band alignments, allowing efficient and layer‐dependent exciton pumping across the O–I interfaces. The interfacial exciton pumping has much higher efficiency (>86 times) than the photoexcitation process in MoSe2, although the pentacene layer has much lower optical absorption than MoSe2. This highly enhanced pumping efficiency is attributed to the high quantum yield in pentacene and the ultrafast energy transfer between the O–I interface. Furthermore, those organic counterparts significantly modulate the bindings of charged excitons in monolayer MoSe2 via their precise dielectric environment engineering. The results open new avenues for exploring fundamental phenomena and novel optoelectronic applications using atomically thin O–I heterostructures.The authors also acknowledge financial support from ANU Ph.D. student scholarship, China Scholarship Council, ANU Major Equipment Committee fund (No. 14MEC34), and Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) (DE140100805). ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET), ANU node; this work is also supported by NSFC 61734003, 61521001 and National Key Basic Research Program of China 2015CB921600

Psychometric Evaluation of the Affective Reactivity Index Among Children and Adolescents in China: A Multi-Method Assessment Approach

The Affective Reactivity Index (ARI) is one of the most studied scales for assessing youth irritability, but little is known about its measurement performance in community populations. This study applied item response theory (IRT), network analysis, and classical test theory (CTT) to examine the psychometric properties of the ARI in a sample of n = 395 community-based children (M-age = 13.44, SD = 2.51) and n = 403 parents. In this sample, the ARI demonstrated good reliability, as well as convergent and concurrent validity. The one-factor structure was supported by both confirmatory factor analysis (CFA) and network analysis. IRT analysis revealed that the ARI effectively distinguished between various levels of irritability within the community population. Network analysis identified "Loses temper easily,""Gets angry frequently," and "Often loses temper" are central aspects of irritability. The findings support the ARI as a brief, reliable, and valid instrument to assess irritability in community children and adolescents

Improving The Improved Training Of Wasserstein Gans: A Consistency Term And Its Dual Effect

Despite being impactful on a variety of problems and applications, the generative adversarial nets (GANs) are remarkably difficult to train. This issue is formally analyzed by Arjovsky & Bottou (2017), who also propose an alternative direction to avoid the caveats in the minmax two-player training of GANs. The corresponding algorithm, called Wasserstein GAN (WGAN), hinges on the 1-Lipschitz continuity of the discriminator. In this paper, we propose a novel approach to enforcing the Lipschitz continuity in the training procedure of WGANs. Our approach seamlessly connects WGAN with one of the recent semi-supervised learning methods. As a result, it gives rise to not only better photo-realistic samples than the previous methods but also state-of-the-art semi-supervised learning results. In particular, our approach gives rise to the inception score of more than 5.0 with only 1,000 CIFAR-10 images and is the first that exceeds the accuracy of 90% on the CIFAR-10 dataset using only 4,000 labeled images, to the best of our knowledge