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Pei Wang

Publications and source records attributed to Pei Wang.

At least 145 records · Page 8Linked to original sources
arXiv2023

Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent Recognition

In a practical dialogue system, users may input out-of-domain (OOD) queries. The Generalized Intent Discovery (GID) task aims to discover OOD intents from OOD queries and extend them to the in-domain (IND) classifier. However, GID only considers one stage of OOD learning, and needs to utilize the data in all previous stages for joint training, which limits its wide application in reality. In this paper, we introduce a new task, Continual Generalized Intent Discovery (CGID), which aims to continuously and automatically discover OOD intents from dynamic OOD data streams and then incrementally add them to the classifier with almost no previous data, thus moving towards dynamic intent recognition in an open world. Next, we propose a method called Prototype-guided Learning with Replay and Distillation (PLRD) for CGID, which bootstraps new intent discovery through class prototypes and balances new and old intents through data replay and feature distillation. Finally, we conduct detailed experiments and analysis to verify the effectiveness of PLRD and understand the key challenges of CGID for future research.

cs.CL↗
arXiv2023

Reciprocating Magnetic Fields in the Pulsar Wind Observed from the Black Widow Pulsar J1720-0534

We report the radio observations of the eclipsing black widow pulsar J1720-0534, a 3.26 ms pulsar in orbit with a low mass companion of mass 0.029 to 0.034 M$_{\odot}$. We obtain the phase-connected timing ephemeris and polarization profile of this millisecond pulsar (MSP) using the Five-hundred-meter Aperture Spherical Radio Telescope (FAST), the Green Bank Telescope (GBT), and the Parkes Telescope. For the first time from such a system, an oscillatory polarisation angle change was observed from a particular eclipse egress with partial depolarization, indicating 10-milliGauss-level reciprocating magnetic fields oscillating in a length scale of 5000 km (assuming an orbital inclination angle of 90 degrees) outside the companion's magnetosphere. The dispersion measure variation observed during the ingresses and egresses shows the rapid raising of the electron density in the shock boundary between the companion's magnetosphere and the surrounding pulsar wind. We suggest that the observed oscillatory magnetic fields originate from the pulsar wind outside the companion's magnetosphere.

astro-ph.HE↗
arXiv2023

Ethosight: A Reasoning-Guided Iterative Learning System for Nuanced Perception based on Joint-Embedding & Contextual Label Affinity

Traditional computer vision models often necessitate extensive data acquisition, annotation, and validation. These models frequently struggle in real-world applications, resulting in high false positive and negative rates, and exhibit poor adaptability to new scenarios, often requiring costly retraining. To address these issues, we present Ethosight, a flexible and adaptable zero-shot video analytics system. Ethosight begins from a clean slate based on user-defined video analytics, specified through natural language or keywords, and leverages joint embedding models and reasoning mechanisms informed by ontologies such as WordNet and ConceptNet. Ethosight operates effectively on low-cost edge devices and supports enhanced runtime adaptation, thereby offering a new approach to continuous learning without catastrophic forgetting. We provide empirical validation of Ethosight's promising effectiveness across diverse and complex use cases, while highlighting areas for further improvement. A significant contribution of this work is the release of all source code and datasets to enable full reproducibility and to foster further innovation in both the research and commercial domains.

cs.CV↗
arXiv2023

Galactic Interstellar Scintillation Observed from Four Globular Cluster Pulsars by FAST

We report detections of scintillation arcs for pulsars in globular clusters M5, M13 and M15 for the first time using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). From observations of these arcs at multiple epochs, we infer that screen-like scattering medium exists at distances $4.1_{-0.3}^{+0.2}$ kpc, $6.7_{-0.2}^{+0.2}$ kpc and $1.3_{-1.0}^{+0.7}$ kpc from Earth in the directions of M5, M13 and M15, respectively. This means M5's and M13's scattering screens are located at $3.0_{-0.2}^{+0.1}$ kpc and $4.4_{-0.1}^{+0.1}$ kpc above the galactic plane, whereas, M15's is at $0.6_{-0.5}^{+0.3}$ kpc below the plane. We estimate the scintillation timescale and decorrelation bandwidth for each pulsar at each epoch using the one-dimensional auto-correlation in frequency and time of the dynamic spectra. We found that the boundary of the Local Bubble may have caused the scattering of M15, and detected the most distant off-plane scattering screens to date through pulsar scintillation, which provides evidence for understanding the medium circulation in the Milky Way.

astro-ph.GA↗
arXiv2023

PCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving

Traditional online advertising systems for sponsored search follow a cascade paradigm with retrieval, pre-ranking,ranking, respectively. Constrained by strict requirements on online inference efficiency, it tend to be difficult to deploy useful but computationally intensive modules in the ranking stage. Moreover, ranking models currently used in the industry assume the user click only relies on the advertisements itself, which results in the ranking stage overlooking the impact of organic search results on the predicted advertisements (ads). In this work, we propose a novel framework PCDF(Parallel-Computing Distributed Framework), allowing to split the computation cost into three parts and to deploy them in the pre-module in parallel with the retrieval stage, the middle-module for ranking ads, and the post-module for re-ranking ads with external items. Our PCDF effectively reduces the overall inference latency compared with the classic framework. The whole module is end-to-end offline training and adapt for the online learning paradigm. To our knowledge, we are the first to propose an end-to-end solution for online training and deployment on complex CTR models from the system framework side.

cs.IR↗
arXiv2023

Blinkverse: A Database of Fast Radio Bursts

The volume of research on fast radio bursts (FRBs) observation have been seeing a dramatic growth. To facilitate the systematic analysis of the FRB population, we established a database platform, Blinkverse (https://blinkverse.alkaidos.cn), as a central inventory of FRBs from various observatories and with published properties, particularly dynamic spectra from FAST, CHIME, GBT, Arecibo, etc. Blinkverse thus not only forms a superset of FRBCAT, TNS, and CHIME/FRB, but also provides convenient access to thousands of FRB dynamic spectra from FAST, some of which were not available before. Blinkverse is regularly maintained and will be updated by external users in the future. Data entries of FRBs can be retrieved through parameter searches through FRB location, fluence, etc., and their logical combinations. Interactive visualization was built into the platform. We analyzed the energy distribution, period analysis, and classification of FRBs based on data downloaded from Blinkverse. The energy distributions of repeaters and non-repeaters are found to be distinct from one another.

astro-ph.HE↗
arXiv2023

A radio pulsar phase from SGR J1935+2154 provides clues to the magnetar FRB mechanism

The megajansky radio burst, FRB 20200428, and other bright radio bursts detected from the Galactic source SGR J1935+2154 suggest that magnetars can make fast radio bursts (FRBs), but the emission site and mechanism of FRB-like bursts are still unidentified. Here we report the emergence of a radio pulsar phase of the magnetar five months after FRB 20200428. 795 pulses were detected in 16.5 hours over 13 days by the Five-hundred-meter Aperture Spherical Radio telescope, with luminosities about eight decades fainter than FRB 20200428. The pulses were emitted in a narrow phase window anti-aligned with the X-ray pulsation profile observed by the X-ray telescopes. The bursts, conversely, appear in random phases. This dichotomy suggests that radio pulses originate from a fixed region within the magnetosphere, but bursts occur in random locations and are possibly associated with explosive events in a dynamically evolving magnetosphere. This picture reconciles the lack of periodicity in cosmological repeating FRBs within the magnetar engine model.

astro-ph.HE↗
arXiv2023

Sub-second periodic radio oscillations in a microquasar

Powerful relativistic jets are one of the ubiquitous features of accreting black holes in all scales. GRS 1915+105 is a well-known fast-spinning black-hole X-ray binary with a relativistic jet, termed as a ``microquasar'', as indicated by its superluminal motion of radio emission. It exhibits persistent x-ray activity over the last 30 years, with quasi-periodic oscillations of $\sim 1-10$ Hz and 34 and 67 Hz in the x-ray band. These oscillations likely originate in the inner accretion disk, but other origins have been considered. Radio observations found variable light curves with quasi-periodic flares or oscillations with periods of $\sim 20-50$ minutes. Here we report two instances of $\sim$5 Hz transient periodic oscillation features from the source detected in the 1.05-1.45 GHz radio band that occurred in January 2021 and June 2022, respectively. Circular polarization was also observed during the oscillation phase.

astro-ph.HE↗
arXiv2023

High-altitude Magnetospheric Emissions from Two Pulsars

We discover three new weak pulse components in two known pulsars, one in PSR J0304+1932 and two in PSR J1518+4904. These components are emitted about half way between the main emission beam and the interpulse beam (beam from the opposite pole). They are separated from their main pulse peak by $99^{\circ}\pm{3}^{\circ}$ for J0304+1932, $123^{\circ}.6\pm{0^{\circ}.7}$ (leading) and $93^{^{\circ}}\pm 0^{\circ}.4$ (trailing) for J1518+4904, respectively. Their peak-intensity ratios to main pulses are: $\sim$ 0.06% for J0304+1932, $\sim$ 0.17% and $\sim$ 0.83% for J1518+4904. We also analyzed flux fluctuation and profile variation of the emissions for two pulsars. The results show correlations between the weak pulses and their main pulses, indicating that these emissions come from the same pole. We estimated the emission altitude of these weak pulses and derived a height of about half of the pulsar's light-cylinder radius. These pulse components are a unique sample of high-altitude emissions from pulsars, and challenge the current pulsar emission models.

astro-ph.HE↗
arXiv2023

Confidence Ranking for CTR Prediction

Model evolution and constant availability of data are two common phenomena in large-scale real-world machine learning applications, e.g. ads and recommendation systems. To adapt, the real-world system typically retrain with all available data and online learn with recently available data to update the models periodically with the goal of better serving performance. In this paper, we propose a novel framework, named Confidence Ranking, which designs the optimization objective as a ranking function with two different models. Our confidence ranking loss allows direct optimization of the logits output for different convex surrogate functions of metrics, e.g. AUC and Accuracy depending on the target task and dataset. Armed with our proposed methods, our experiments show that the introduction of confidence ranking loss can outperform all baselines on the CTR prediction tasks of public and industrial datasets. This framework has been deployed in the advertisement system of JD.com to serve the main traffic in the fine-rank stage.

cs.IR↗
arXiv2023

Categorize Radio Interference using component and temporal analysis

Radio frequency interference (RFI) is a significant challenge faced by today's radio astronomers. While most past efforts were devoted to cleaning the RFI from the data, we develop a novel method for categorizing and cataloguing RFI for forensic purpose. We present a classifier that categorizes RFI into different types based on features extracted using Principal Component Analysis (PCA) and Fourier analysis. The classifier can identify narrowband non-periodic RFI above 2 sigma, narrowband periodic RFI above 3 sigma, and wideband impulsive RFI above 5 sigma with F1 scores between 0.87 and 0.91 in simulation. This classifier could be used to identify the sources of RFI as well as to clean RFI contamination (particularly in pulsar search). In the long-term analysis of the categorized RFI, we found a special type of drifting periodic RFI that is detrimental to pulsar search. We also found evidences of an increased rate of impulsive RFI when the telescope is pointing toward the cities. These results demonstrate this classifier's potential as a forensic tool for RFI environment monitoring of radio telescopes.

astro-ph.IM↗
arXiv2023

The mixing-spacetime symmetry in the Floquet-Bloch band theory

We discover a class of spacetime symmetries unique to time-periodic systems, which we term "mixing symmetry" due to its combination of space and time coordinates in the symmetry transformation. We systematically enumerate the symmetry groups, and classify the corresponding Floquet-Bloch band theories by utilizing the winding number of quasi-energy. Moreover, we provide a comprehensive scheme for the experimental realization of these symmetries. The particle propagator exhibits an intriguing pattern that remains invariant even under transformations mixing space and time coordinates. We anticipate that this distinct feature can be observed in current cold atom experiments.

cond-mat.quant-gas↗
arXiv2023

Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery

Generalized intent discovery aims to extend a closed-set in-domain intent classifier to an open-world intent set including in-domain and out-of-domain intents. The key challenges lie in pseudo label disambiguation and representation learning. Previous methods suffer from a coupling of pseudo label disambiguation and representation learning, that is, the reliability of pseudo labels relies on representation learning, and representation learning is restricted by pseudo labels in turn. In this paper, we propose a decoupled prototype learning framework (DPL) to decouple pseudo label disambiguation and representation learning. Specifically, we firstly introduce prototypical contrastive representation learning (PCL) to get discriminative representations. And then we adopt a prototype-based label disambiguation method (PLD) to obtain pseudo labels. We theoretically prove that PCL and PLD work in a collaborative fashion and facilitate pseudo label disambiguation. Experiments and analysis on three benchmark datasets show the effectiveness of our method.

cs.CL↗
arXiv2023

Learning from Multi-Perception Features for Real-Word Image Super-resolution

Currently, there are two popular approaches for addressing real-world image super-resolution problems: degradation-estimation-based and blind-based methods. However, degradation-estimation-based methods may be inaccurate in estimating the degradation, making them less applicable to real-world LR images. On the other hand, blind-based methods are often limited by their fixed single perception information, which hinders their ability to handle diverse perceptual characteristics. To overcome this limitation, we propose a novel SR method called MPF-Net that leverages multiple perceptual features of input images. Our method incorporates a Multi-Perception Feature Extraction (MPFE) module to extract diverse perceptual information and a series of newly-designed Cross-Perception Blocks (CPB) to combine this information for effective super-resolution reconstruction. Additionally, we introduce a contrastive regularization term (CR) that improves the model's learning capability by using newly generated HR and LR images as positive and negative samples for ground truth HR. Experimental results on challenging real-world SR datasets demonstrate that our approach significantly outperforms existing state-of-the-art methods in both qualitative and quantitative measures.

cs.CV↗
arXiv2023

Magnetic field reversal in the turbulent environment around a repeating fast radio burst

Fast radio bursts (FRBs) are brief, intense flashes of radio waves from unidentified extragalactic sources. Polarized FRBs originate in highly magnetized environments. We report observations of the repeating FRB 20190520B spanning seventeen months , which show its amount of Faraday rotation is highly variable and twice changes its sign. The FRB also depolarizes below radio frequencies around 1 to 3 GHz. We interpret these properties as due to change in the parallel component of the integrated magnetic field along the line-of-sight, including reversals. This could result from propagation through a turbulent, magnetized screen of plasma located between $10^{-5}$ to 100 parsecs of the FRB source. This is consistent with the bursts passing through the stellar wind of a binary companion of the FRB source.

astro-ph.HE↗
arXiv2023

FAST Observations of FRB 20220912A: Burst Properties and Polarization Characteristics

We report the observations of FRB 20220912A using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). We conducted 17 observations totaling 8.67 hours and detected a total of 1076 bursts with an event rate up to 390 hr$^{-1}$. The cumulative energy distribution can be well described using a broken power-law function with the lower and higher-energy slopes of $-0.38\pm0.02$ and $-2.07\pm0.07$, respectively. We also report the L band ($1-1.5$ GHz) spectral index of the synthetic spectrum of FRB~20220912A bursts, which is $-2.6\pm0.21$. The average rotation measure (RM) value of the bursts from FRB~20220912A is $-0.08\pm5.39\ \rm rad\,m^{-2}$, close to 0 $\rm rad\,m^{-2}$ and maintain relatively stable over two months. Most bursts have nearly 100\% linear polarization. About 45\% of the bursts have circular polarization with SNR $>$ 3, and the highest circular polarization degree can reach 70\%. Our observations suggest that FRB~20220912A is located in a relatively clean local environment with complex circular polarization characteristics. These various behaviors imply that the mechanism of circular polarization of FRBs likely originates from an intrinsic radiation mechanism, such as coherent curvature radiation or inverse Compton scattering inside the magnetosphere of the FRB engine source (e.g. a magnetar).

astro-ph.HE↗
arXiv2023

GRAN: Ghost Residual Attention Network for Single Image Super Resolution

Recently, many works have designed wider and deeper networks to achieve higher image super-resolution performance. Despite their outstanding performance, they still suffer from high computational resources, preventing them from directly applying to embedded devices. To reduce the computation resources and maintain performance, we propose a novel Ghost Residual Attention Network (GRAN) for efficient super-resolution. This paper introduces Ghost Residual Attention Block (GRAB) groups to overcome the drawbacks of the standard convolutional operation, i.e., redundancy of the intermediate feature. GRAB consists of the Ghost Module and Channel and Spatial Attention Module (CSAM) to alleviate the generation of redundant features. Specifically, Ghost Module can reveal information underlying intrinsic features by employing linear operations to replace the standard convolutions. Reducing redundant features by the Ghost Module, our model decreases memory and computing resource requirements in the network. The CSAM pays more comprehensive attention to where and what the feature extraction is, which is critical to recovering the image details. Experiments conducted on the benchmark datasets demonstrate the superior performance of our method in both qualitative and quantitative. Compared to the baseline models, we achieve higher performance with lower computational resources, whose parameters and FLOPs have decreased by more than ten times.

cs.CV↗
arXiv2023

SlimSeg: Slimmable Semantic Segmentation with Boundary Supervision

Accurate semantic segmentation models typically require significant computational resources, inhibiting their use in practical applications. Recent works rely on well-crafted lightweight models to achieve fast inference. However, these models cannot flexibly adapt to varying accuracy and efficiency requirements. In this paper, we propose a simple but effective slimmable semantic segmentation (SlimSeg) method, which can be executed at different capacities during inference depending on the desired accuracy-efficiency tradeoff. More specifically, we employ parametrized channel slimming by stepwise downward knowledge distillation during training. Motivated by the observation that the differences between segmentation results of each submodel are mainly near the semantic borders, we introduce an additional boundary guided semantic segmentation loss to further improve the performance of each submodel. We show that our proposed SlimSeg with various mainstream networks can produce flexible models that provide dynamic adjustment of computational cost and better performance than independent models. Extensive experiments on semantic segmentation benchmarks, Cityscapes and CamVid, demonstrate the generalization ability of our framework.

cs.CV↗