arXiv subjects

Ping Yang

Publications and source records attributed to Ping Yang.

At least 73 records · Page 4Linked to original sources

arXiv2023

Hawkeye: Change-targeted Testing for Android Apps based on Deep Reinforcement Learning

Android Apps are frequently updated to keep up with changing user, hardware, and business demands. Ensuring the correctness of App updates through extensive testing is crucial to avoid potential bugs reaching the end user. Existing Android testing tools generate GUI events focussing on improving the test coverage of the entire App rather than prioritising updates and its impacted elements. Recent research has proposed change-focused testing but relies on random exploration to exercise the updates and impacted GUI elements that is ineffective and slow for large complex Apps with a huge input exploration space. We propose directed testing of App updates with Hawkeye that is able to prioritise executing GUI actions associated with code changes based on deep reinforcement learning from historical exploration data. Our empirical evaluation compares Hawkeye with state-of-the-art model-based and reinforcement learning-based testing tools FastBot2 and ARES using 10 popular open-source and 1 commercial App. We find that Hawkeye is able to generate GUI event sequences targeting changed functions more reliably than FastBot2 and ARES for the open source Apps and the large commercial App. Hawkeye achieves comparable performance on smaller open source Apps with a more tractable exploration space. The industrial deployment of Hawkeye in the development pipeline also shows that Hawkeye is ideal to perform smoke testing for merge requests of a complicated commercial App.

cs.SE↗

arXiv2023

Direct observation of two-dimensional small polarons at correlated oxide interface

Two-dimensional (2D) perovskite oxide interfaces are ideal systems where diverse emergent properties can be uncovered.The formation and modification of polaronic properties due to short-range strong charge-lattice interactions of 2D interfaces remains hugely intriguing.Here, we report the direct observation of small-polarons at the LaAlO3/SrTiO3 (LAO/STO) conducting interface using high-resolution spectroscopic ellipsometry.First-principles investigations further reveals that strong coupling between the interfacial electrons and the Ti-lattice result in the formation of localized 2D small polarons.These findings resolve the longstanding issue where the excess experimentally measured interfacial carrier density is significantly lower than theoretically predicted values.The charge-phonon induced lattice distortion further provides an analogue to the superconductive states in magic-angle twisted bilayer graphene attributed to the many-body correlations induced by broken periodic lattice symmetry.Our study sheds light on the multifaceted complexity of broken periodic lattice induced quasi-particle effects and its relationship with superconductivity.

cond-mat.str-el↗

arXiv2023

Self-passivated freestanding superconducting oxide film for flexible electronics

The integration of high-temperature superconducting YBa2Cu3O6+x (YBCO) into flexible electronic devices has the potential to revolutionize the technology industry. The effective preparation of high-quality flexible YBCO films therefore plays a key role in this development. We present a novel approach for transferring water-sensitive YBCO films onto flexible substrates without any buffer layer. Freestanding YBCO film on a polydimethylsiloxane substrate is extracted by etching the Sr3Al2O6 sacrificial layer from the LaAlO3 substrate. In addition to the obtained freestanding YBCO thin film having a Tc of 89.1 K, the freestanding YBCO thin films under inward and outward bending conditions have Tc of 89.6 K and 88.9 K, respectively. A comprehensive characterization involving multiple experimental techniques including high-resolution transmission electron microscopy, scanning electron microscopy, Raman and X-ray Absorption Spectroscopy is conducted to investigate the morphology, structural and electronic properties of the YBCO film before and after the extraction process where it shows the preservation of the structural and superconductive properties of the freestanding YBCO virtually in its pristine state. Further investigation reveals the formation of a YBCO passivated layer serves as a protective layer which effectively preserves the inner section of the freestanding YBCO during the etching process. This work plays a key role in actualizing the fabrication of flexible oxide thin films and opens up new possibilities for a diverse range of device applications involving thin-films and low-dimensional materials.

cond-mat.supr-con↗

arXiv2023

UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective

We propose a new paradigm for universal information extraction (IE) that is compatible with any schema format and applicable to a list of IE tasks, such as named entity recognition, relation extraction, event extraction and sentiment analysis. Our approach converts the text-based IE tasks as the token-pair problem, which uniformly disassembles all extraction targets into joint span detection, classification and association problems with a unified extractive framework, namely UniEX. UniEX can synchronously encode schema-based prompt and textual information, and collaboratively learn the generalized knowledge from pre-defined information using the auto-encoder language models. We develop a traffine attention mechanism to integrate heterogeneous factors including tasks, labels and inside tokens, and obtain the extraction target via a scoring matrix. Experiment results show that UniEX can outperform generative universal IE models in terms of performance and inference-speed on $14$ benchmarks IE datasets with the supervised setting. The state-of-the-art performance in low-resource scenarios also verifies the transferability and effectiveness of UniEX.

cs.CL↗

arXiv2023

Oxygen Octahedral Tilt Controlled Topological Hall Effect in Epitaxial and Freestanding SrRuO3/SrIrO3 Heterostructures

The fabrication technique of freestanding oxide flakes by epitaxial lift-off has made significant contributions to the multifunctional oxide thin film research. Several highly impactful work have recently demonstrated the robustness of freestanding oxide flakes retaining their desirable properties after detachment from the substrate by dissolving away the water-soluble Sr3Al2O6 buffer layer. Firstly, in epitaxial SrRuO3/SrIrO3 systems showing Hall-humps reminiescence of Topological Hall Effect, first-principle calculations revealed that octahedral tilts can modify the sign of Dzyaloshinskii-Moriya interaction and avoid cancellation in a symmetric trilayer structure. Secondly, freestanding flakes of the trilayer is also able to retain the Hall-humps across a wide temperature range. The behaviour of humps' peak field does not vary with field direction rotation away from surface normal, consistent to a micromagnetic simulation result of Néel-type magnetic Skyrmions. The layer-resolved octahedral tilts in the freestanding heterostructures also crucially controls the occurrence of Hall-humps, consistent to the insight from the epitaxial ones. This work offers a new perspective to understanding Hall-humps in perovskite oxides, as well as demonstrates the fabrication of oxide heterostructure membranes with high interfacial quality.

cond-mat.mtrl-sci↗

arXiv2023

A Robust High-temperature Multiferroic Device with Tunable Topological Hall Effect

We fabricated Pt/La0.5Ba0.5MnO3 ultrathin films with integration to the PbZr0.2Ti0.8O3 ferroelectric. Strong Topological Hall Effect can be measured across a wide temperature range, which can be turned on and off corresponding to the ferroelectric polarization switching driven by short voltage pulses, indicating creation and annihilation of magnetic Skyrmions. However, its magnetoelectric coupling polarity was found to be opposite to the earlier consensus, which involves a phase transition between ferromagnetic and A-type antiferromagnetic in manganites due to electrostatic doping into the eg-orbitals by the ferroelectric bound charges. In our case, we propose a novel yet complementary picture where the transition occurs between C-type antiferromagnetic and ferromagnetic. The distinction between the earlier consensus and our picture lies at the tetragonal distortion of the manganite unit cell, resulting in an opposite magnetoelectric coupling polarity. We support the perceived relationship between the phase transition and tuning of Topological Hall Effect by micromagnetic simulations.

cond-mat.mtrl-sci↗

arXiv2023

An independent determination of the distance to supernova SN 1987A by means of the light echo AT 2019xis

Accurate distance determination to astrophysical objects is essential for the understanding of their intrinsic brightness and size. The distance to SN 1987A has been previously measured by the expanding photosphere method, and by using the angular size of the circumstellar rings with absolute sizes derived from light curves of narrow UV emission lines, with reported distances ranging from 46.77 kpc to 55 kpc. In this study, we independently determined the distance to SN 1987A using photometry and imaging polarimetry observations of AT 2019xis, a light echo of SN 1987A, by adopting a radiative transfer model of the light echo developed in Ding et al. (2021). We obtained distances to SN 1987A in the range from 49.09 $\pm$ 2.16 kpc to 59.39 $\pm$ 3.27 kpc, depending on the interstellar polarization and extinction corrections, which are consistent with the literature values. This study demonstrates the potential of using light echoes as a tool for distance determination to astrophysical objects in the Milky Way, up to kiloparsec level scales.

astro-ph.HE↗

arXiv2023

Existence and multiplicity of nontrivial solutions for a $(p,q)$-Laplacian system on locally finite graphs

We generalize two embedding theorems and investigate the existence and multiplicity of nontrivial solutions for a $(p,q)$-Laplacian coupled system with perturbations and two parameters $λ_1$ and $λ_2$ on locally finite graph. By using the Ekeland's variational principle, we obtain that system has at least one nontrivial solution when the nonlinear term satisfies the sub-$(p,q)$ conditions. We also obtain a necessary condition for the existence of semi-trivial solutions to the system. Moreover, by using the mountain pass theorem and Ekeland's variational principle, we obtain that system has at least one solution of positive energy and one solution of negative energy when the nonlinear term satisfies the super-$(p,q)$ conditions which is weaker than the well-known Ambrosetti-Rabinowitz condition. Especially, in all of the results, we present the concrete ranges of the parameters $λ_1$ and $λ_2$.

math.AP↗

arXiv2023

Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence

Nowadays, foundation models become one of fundamental infrastructures in artificial intelligence, paving ways to the general intelligence. However, the reality presents two urgent challenges: existing foundation models are dominated by the English-language community; users are often given limited resources and thus cannot always use foundation models. To support the development of the Chinese-language community, we introduce an open-source project, called Fengshenbang, which leads by the research center for Cognitive Computing and Natural Language (CCNL). Our project has comprehensive capabilities, including large pre-trained models, user-friendly APIs, benchmarks, datasets, and others. We wrap all these in three sub-projects: the Fengshenbang Model, the Fengshen Framework, and the Fengshen Benchmark. An open-source roadmap, Fengshenbang, aims to re-evaluate the open-source community of Chinese pre-trained large-scale models, prompting the development of the entire Chinese large-scale model community. We also want to build a user-centered open-source ecosystem to allow individuals to access the desired models to match their computing resources. Furthermore, we invite companies, colleges, and research institutions to collaborate with us to build the large-scale open-source model-based ecosystem. We hope that this project will be the foundation of Chinese cognitive intelligence.

cs.CL↗

arXiv2023

Giant Magneto-Optical Schäfer-Hubert Effect in Two-Dimensional van der Waals Antiferromagnets \textit{M}PS$_3$ (\textit{M}=Mn, Fe, Ni)

The recent discovery of long-range magnetic order in atomically thin films has triggered particular interest in two-dimensional (2D) van der Waals (vdW) magnetic materials. In this paper, we perform a systematic theoretical study of the magneto-optical Schäfer-Hubert effect (MOSHE) in 2D vdW antiferromagnetic \textit{M}PS$_3$ (\textit{M} = Mn, Fe, Ni) with multifold intralayer and interlayer magnetic orders. The formula for evaluating the MOSHE in 2D magnets is derived by considering the influence of a non-magnetic substrate. The MOSHE of monolayer and bilayer \textit{M}PS$_3$ are considerably large ($>2^{\circ}$), originating from the strong anisotropy of in-plane optical conductivity. The Schäfer-Hubert rotation angles are surprisingly insensitive to the orientations of the Néel vector, while the Schäfer-Hubert ellipticities are identified to be a good criterion to distinguish different interlayer magnetic orders. Our work establishes a theoretical framework for exploring novel 2D vdW magnets and facilitates the promising applications of the 2D \textit{M}PS$_3$ family in antiferromagnetic nanophotonic devices.

cond-mat.mtrl-sci↗

arXiv2022

Orbital hybridization-driven charge density wave transition in CsV3Sb5 kagome superconductor

Owing to its inherent non-trivial geometry, the unique structural motif of the recently discovered Kagome topological superconductor AV3Sb5 is an ideal host of diverse topologically non-trivial phenomena, including giant anomalous Hall conductivity, topological charge order, charge density wave, and unconventional superconductivity. Despite possessing a normal-state CDW order in the form of topological chiral charge order and diverse superconducting gaps structures, it remains unclear how fundamental atomic-level properties and many-body effects including Fermi surface nesting, electron-phonon coupling, and orbital hybridization contribute to these symmetry-breaking phenomena. Here, we report the direct participation of the V3d-Sb5p orbital hybridization in mediating the CDW phase transition in CsV3Sb5. The combination of temperature-dependent X-ray absorption and first principles studies clearly indicate the Inverse Star of David structure as the preferred reconstruction in the low-temperature CDW phase. Our results highlight the critical role that Sb orbitals plays and establish orbital hybridization as the direct mediator of the CDW states and structural transition dynamics in Kagome unconventional superconductors. This is a significant step towards the fundamental understanding and control of the emerging correlated phases from the Kagome lattice through the orbital interactions and provide promising approaches to novel regimes in unconventional orders and topology.

cond-mat.supr-con↗

arXiv2022

Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective

We propose a new paradigm for zero-shot learners that is format agnostic, i.e., it is compatible with any format and applicable to a list of language tasks, such as text classification, commonsense reasoning, coreference resolution, and sentiment analysis. Zero-shot learning aims to train a model on a given task such that it can address new learning tasks without any additional training. Our approach converts zero-shot learning into multiple-choice tasks, avoiding problems in commonly used large-scale generative models such as FLAN. It not only adds generalization ability to models but also significantly reduces the number of parameters. Our method shares the merits of efficient training and deployment. Our approach shows state-of-the-art performance on several benchmarks and produces satisfactory results on tasks such as natural language inference and text classification. Our model achieves this success with only 235M parameters, which is substantially smaller than state-of-the-art models with billions of parameters. The code and pre-trained models are available at https://github.com/IDEA-CCNL/Fengshenbang-LM .

cs.CL↗

arXiv2022

Second-order topological magneto-optical effects in noncoplanar antiferromagnets

The second-order magneto-optical effects, represented by Voigt and Schäfer-Hubert effects, are effective methods to detect the spin textures in antiferromagnets, whereas the previous studies are usually limited to collinear antiferromagnets. In noncollinear antiferromagnets, the spin textures characterized by spin chirality have been revealed to play a critical role in many exciting physics. In particular, the first-order topological magneto-optical effects originated from scalar spin chirality have been discovered recently. In this work, using the first-principles calculations and group theory analysis, we generalize the first-order topological magneto-optical effects to the second-order cases, that is, topological Voigt and Schäfer-Hubert effects, by taking the noncoplanar 3Q spin state of $γ$-Fe$_{x}$Mn$_{1-x}$ alloy as an example. The conventional Voigt and Schäfer-Hubert effects are comparatively studied in the collinear 1Q and 2Q spin states of $γ$-Fe$_{x}$Mn$_{1-x}$ alloy. In addition, the natural linear birefringence due to crystal anisotropy is discussed in the strained 1Q, 2Q, and 3Q states, and a unique fingerprint for experimentally distinguishing the second-order topological magneto-optical effects and natural linear birefringence is identified. Our work brings a topological insight into the second-order magneto-optical effects in noncoplanar antiferromagnets and also provides $γ$-Fe$_{x}$Mn$_{1-x}$ as an attractive material platform for future experimental exploration.

cond-mat.mtrl-sci↗

arXiv2022

Unified BERT for Few-shot Natural Language Understanding

Even as pre-trained language models share a semantic encoder, natural language understanding suffers from a diversity of output schemas. In this paper, we propose UBERT, a unified bidirectional language understanding model based on BERT framework, which can universally model the training objects of different NLU tasks through a biaffine network. Specifically, UBERT encodes prior knowledge from various aspects, uniformly constructing learning representations across multiple NLU tasks, which is conducive to enhancing the ability to capture common semantic understanding. By using the biaffine to model scores pair of the start and end position of the original text, various classification and extraction structures can be converted into a universal, span-decoding approach. Experiments show that UBERT wins the first price in the 2022 AIWIN - World Artificial Intelligence Innovation Competition, Chinese insurance few-shot multi-task track, and realizes the unification of extensive information extraction and linguistic reasoning tasks.

cs.CL↗

arXiv2022

The first- and second-order magneto-optical effects and intrinsically anomalous transport in 2D van der Waals layered magnets CrXY (X = S, Se, Te; Y = Cl, Br, I)

Recently, the two-dimensional magnetic semiconductor CrSBr has attracted considerable attention due to its excellent air-stable property and high magnetic critical temperature. Here, we systematically investigate the electronic structure, magnetocrystalline anisotropy energy, first-order magneto-optical effects (Kerr and Faraday effects) and second-order magneto-optical effects (Schafer-Hubert and Voigt effects) as well as intrinsically anomalous transport properties (anomalous Hall, anomalous Nernst, and anomalous thermal Hall effects) of two-dimensional van der Waals layered magnets CrXY (X = S, Se, Te; Y = Cl, Br, I) by using the first-principles calculations. Our results show that monolayer and bilayer CrXY (X = S, Se) are narrow band gap semiconductors, whereas monolayer and bilayer CrTeY are multi-band metals. The magnetic ground states of bilayer CrXY and the easy magnetization axis of monolayer and bilayer CrXY are confirmed by the magnetocrystalline anisotropy energy calculations. Utilizing magnetic group theory analysis, the first-order magneto-optical effects as well as anomalous Hall, anomalous Nernst, and anomalous thermal Hall effects are identified to exist in ferromagnetic state with out-of-plane magnetization. The second-order magneto-optical effects are not restricted by the above symmetry requirements, and therefore can arise in ferromagnetic and antiferromagnetic states with in-plane magnetization. The calculated results are compared with the available theoretical and experimental data of other two-dimensional magnets and some conventional ferromagnets. The present work reveals that monolayer and bilayer CrXY with superior magneto-optical responses and anomalous transport properties provide an excellent material platform for the promising applications of magneto-optical devices, spintronics, and spin caloritronics.

cond-mat.mtrl-sci↗

arXiv2022

Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss

This report describes a pre-trained language model Erlangshen with propensity-corrected loss, the No.1 in CLUE Semantic Matching Challenge. In the pre-training stage, we construct a dynamic masking strategy based on knowledge in Masked Language Modeling (MLM) with whole word masking. Furthermore, by observing the specific structure of the dataset, the pre-trained Erlangshen applies propensity-corrected loss (PCL) in the fine-tuning phase. Overall, we achieve 72.54 points in F1 Score and 78.90 points in Accuracy on the test set. Our code is publicly available at: https://github.com/IDEA-CCNL/Fengshenbang-LM/tree/hf-ds/fengshen/examples/clue_sim.

cs.CL↗

arXiv2022

Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval

Passage retrieval is a fundamental task in information retrieval (IR) research, which has drawn much attention recently. In the English field, the availability of large-scale annotated dataset (e.g, MS MARCO) and the emergence of deep pre-trained language models (e.g, BERT) has resulted in a substantial improvement of existing passage retrieval systems. However, in the Chinese field, especially for specific domains, passage retrieval systems are still immature due to quality-annotated dataset being limited by scale. Therefore, in this paper, we present a novel multi-domain Chinese dataset for passage retrieval (Multi-CPR). The dataset is collected from three different domains, including E-commerce, Entertainment video and Medical. Each dataset contains millions of passages and a certain amount of human annotated query-passage related pairs. We implement various representative passage retrieval methods as baselines. We find that the performance of retrieval models trained on dataset from general domain will inevitably decrease on specific domain. Nevertheless, a passage retrieval system built on in-domain annotated dataset can achieve significant improvement, which indeed demonstrates the necessity of domain labeled data for further optimization. We hope the release of the Multi-CPR dataset could benchmark Chinese passage retrieval task in specific domain and also make advances for future studies.

cs.IR↗

arXiv2022

Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosis

The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively handling and fully utilizing the accumulation of such enormous amounts of data. Machine learning-based approaches play a critical role in integrating and analyzing these large and complex datasets, which have extensively characterized lung cancer through the use of different perspectives from these accrued data. In this article, we provide an overview of machine learning-based approaches that strengthen the varying aspects of lung cancer diagnosis and therapy, including early detection, auxiliary diagnosis, prognosis prediction and immunotherapy practice. Moreover, we highlight the challenges and opportunities for future applications of machine learning in lung cancer.

cs.LG↗