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Source author record

Kai Zhu

Kai Zhu appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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hep-exComputer VisionSocial and Information Networkshep-phastro-ph.GAcond-mat.mtrl-sciMachine Learningphysics.soc-phArtificial IntelligenceComputational Engineering, Finance, and Sciencecond-mat.supr-conData Structures and Algorithmshep-thInformation Theorymath.ITMultimediaNetworking and Internet Architecturephysics.app-phphysics.data-anphysics.ins-detphysics.opticsSystems and Control

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Published work

27 published item(s)

preprint2026arXiv

EditEmoTalk: Controllable Speech-Driven 3D Facial Animation with Continuous Expression Editing

Speech-driven 3D facial animation aims to generate realistic and expressive facial motions directly from audio. While recent methods achieve high-quality lip synchronization, they often rely on discrete emotion categories, limiting continuous and fine-grained emotional control. We present EditEmoTalk, a controllable speech-driven 3D facial animation framework with continuous emotion editing. The key idea is a boundary-aware semantic embedding that learns the normal directions of inter-emotion decision boundaries, enabling a continuous expression manifold for smooth emotion manipulation. Moreover, we introduce an emotional consistency loss that enforces semantic alignment between the generated motion dynamics and the target emotion embedding through a mapping network, ensuring faithful emotional expression. Extensive experiments demonstrate that EditEmoTalk achieves superior controllability, expressiveness, and generalization while maintaining accurate lip synchronization. Code and pretrained models will be released.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation

Video generation is rapidly evolving from single-shot synthesis to complex multi-shot audio-video (MSAV) narratives to meet real-world demands. However, evaluating such frontier models remains a fundamental challenge. Existing benchmarks are limited in scope and data diversity, and rely on rigid evaluation pipelines, preventing systematic and reliable assessment of modern MSAV models. To bridge these gaps, we introduce MSAVBench, the first comprehensive benchmark and adaptive hybrid evaluation framework for multi-shot audio-video generation. Our benchmark spans four key dimensions, video, audio, shot, and reference, covering diverse task settings, varying shot counts of up to 15, and challenging non-realistic scenarios. Our evaluation framework improves robustness through an adaptive self-correction mechanism for shot segmentation, instance-wise rubrics for subjective metrics, and tool-grounded evidence extraction for complex judgments. Furthermore, MSAVBench achieves high alignment with human judgments, reaching a Spearman rank correlation of 91.5%. Our systematic evaluation of 19 state-of-the-art closed- and open-source models shows that current systems still struggle with director-level control and fine-grained audio-visual synchronization, while modular or agentic generation pipelines offer a promising path toward narrowing the gap between open- and closed-source models. We will release the benchmark data and evaluation code to facilitate future research.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

A Data-driven dE/dx Simulation with Normalizing Flow

In high-energy physics, precise measurements rely on highly reliable detector simulations. Traditionally, these simulations involve incorporating experiment data to model detector responses and fine-tuning them. However, due to the complexity of the experiment data, tuning the simulation can be challenging. One crucial aspect for charged particle identification is the measurement of energy deposition per unit length (referred to as dE/dx). This paper proposes a data-driven dE/dx simulation method using the Normalizing Flow technique, which can learn the dE/dx distribution directly from experiment data. By employing this method, not only can the need for manual tuning of the dE/dx simulation be eliminated, but also high-precision simulation can be achieved.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

FAMLP: A Frequency-Aware MLP-Like Architecture For Domain Generalization

MLP-like models built entirely upon multi-layer perceptrons have recently been revisited, exhibiting the comparable performance with transformers. It is one of most promising architectures due to the excellent trade-off between network capability and efficiency in the large-scale recognition tasks. However, its generalization performance to heterogeneous tasks is inferior to other architectures (e.g., CNNs and transformers) due to the extensive retention of domain information. To address this problem, we propose a novel frequency-aware MLP architecture, in which the domain-specific features are filtered out in the transformed frequency domain, augmenting the invariant descriptor for label prediction. Specifically, we design an adaptive Fourier filter layer, in which a learnable frequency filter is utilized to adjust the amplitude distribution by optimizing both the real and imaginary parts. A low-rank enhancement module is further proposed to rectify the filtered features by adding the low-frequency components from SVD decomposition. Finally, a momentum update strategy is utilized to stabilize the optimization to fluctuation of model parameters and inputs by the output distillation with weighted historical states. To our best knowledge, we are the first to propose a MLP-like backbone for domain generalization. Extensive experiments on three benchmarks demonstrate significant generalization performance, outperforming the state-of-the-art methods by a margin of 3%, 4% and 9%, respectively.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Selecting the physical solution via $η$-$η'$ mixing

Based on $η$-$η'$ mixing analysis, we propose a novel method to extract the physical solutions for the hadronic properties of the $Y(4230)$ resonance from the experimental data. Experimentally, multiple solutions have been reported in the decays of $Y(4230) \to ηJ/ψ$ and $Y(4230) \to η' J/ψ$. Utilizing our method, we determine a unique solution for the process $Y(4230) \to η' J/ψ$. Likewise, two solutions for the process $Y(4230) \to ηJ/ψ$ are preferred among the originally reported three solutions under the assumption that $Y(4230)$ dose not take an $s\bar{s}$ component.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning

Non-exemplar class-incremental learning is to recognize both the old and new classes when old class samples cannot be saved. It is a challenging task since representation optimization and feature retention can only be achieved under supervision from new classes. To address this problem, we propose a novel self-sustaining representation expansion scheme. Our scheme consists of a structure reorganization strategy that fuses main-branch expansion and side-branch updating to maintain the old features, and a main-branch distillation scheme to transfer the invariant knowledge. Furthermore, a prototype selection mechanism is proposed to enhance the discrimination between the old and new classes by selectively incorporating new samples into the distillation process. Extensive experiments on three benchmarks demonstrate significant incremental performance, outperforming the state-of-the-art methods by a margin of 3%, 3% and 6%, respectively.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Tensor amplitudes for partial wave analysis of $ψ\toΔ\barΔ$ within helicity frame

We have derived the tensor amplitudes for partial wave analysis of $ψ\toΔ\barΔ$, $Δ\to p π$ within the helicity frame, as well as the amplitudes for the other decay sequences with same final states. These formulae are practical for the experiments measuring $ψ$ decaying into $p \bar{p}π^+ π^-$ final states, such as BESIII with its recently collected huge $J/ψ$ and $ψ(2S)$ data samples.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

An Adaptive Interpolation Scheme for Wideband Frequency Sweep in Electromagnetic Simulations

An adaptive interpolation scheme is proposed to accurately calculate the wideband responses in electromagnetic simulations. In the proposed scheme, the sampling points are first carefully divided into several groups based on their responses to avoid the Runge phenomenon and the error fluctuations, and then different interpolation strategies are used to calculate the responses in the whole frequency band. If the relative error does not satisfy the predefined threshold in a specific frequency band, it will be refined until the error criteria is met. The detailed error analysis is also presented to verify the accuracy of the interpolation scheme. At last, two numerical examples including the antenna radiation and the filter simulation are carried out to validate its accuracy and efficiency.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Systematic errors induced by the elliptical power-law model in galaxy-galaxy strong lens modeling

The elliptical power-law (EPL) model of the mass in a galaxy is widely used in strong gravitational lensing analyses. However, the distribution of mass in real galaxies is more complex. We quantify the biases due to this model mismatch by simulating and then analysing mock {\it Hubble Space Telescope} imaging of lenses with mass distributions inferred from SDSS-MaNGA stellar dynamics data. We find accurate recovery of source galaxy morphology, except for a slight tendency to infer sources to be more compact than their true size. The Einstein radius of the lens is also robustly recovered with 0.1% accuracy, as is the global density slope, with 2.5% relative systematic error, compared to the 3.4% intrinsic dispersion. However, asymmetry in real lenses also leads to a spurious fitted `external shear' with typical strength, $γ_{\rm ext}=0.015$. Furthermore, time delays inferred from lens modelling without measurements of stellar dynamics are typically underestimated by $\sim$5%. Using such measurements from a sub-sample of 37 lenses would bias measurements of the Hubble constant $H_0$ by $\sim$9%. Although this work is based on a particular set of MaNGA galaxies, and the specific value of the detected biases may change for another set of strong lenses, our results strongly suggest the next generation cosmography needs to use more complex lens mass models.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Amplitudes separation and strong-electromagnetic relative phase in the $ψ(2S)$ decays into baryons

The strong, electromagnetic and mixed strong-electromagnetic amplitudes of the $ψ(2S)$ decays into baryon-anti-baryon pairs have been obtained by exploiting all available data sets in the framework of an effective Lagrangian model. We observed that at the $ψ(2S)$ mass the QCD regime is not completely perturbative, as can be inferred by the relative strength of the strong and the mixed strong-electromagnetic amplitudes. Recently a similar conclusion has been reached also for the $J/ψ$ decays. The relative phase between the strong and the electromagnetic amplitudes is $φ= (58\pm 8)^\circ$, to be compared with $φ= (73\pm 8)^\circ$ obtained for the $J/ψ$. On the other hand, in the case of the $ψ(2S)$ meson, different values of the ratio between strong and mixed strong-electromagnetic amplitudes are phenomenologically required, while for the $J/ψ$ meson only one ratio was enough to describe the data. Finally, we also observed a peculiar behavior of the mixed strong-electromagnetic amplitudes of the decays $ψ(2S)\toΣ^+ \overline Σ^-$ and $ψ(2S)\toΣ^- \overline Σ^+$.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

An analysis of carrier dynamics in methylammonium lead triiodide perovskite solar cells using cross-correlation noise spectroscopy

Using cross-correlation current noise spectroscopy, we have investigated carrier dynamics in methylammonium lead triiodide solar cells. This method provides a space selectivity for devices with planar multi-layered structure, effectively amplifying current noise contributions coming from the most resistive element of the stack. In the studied solar cells, we observe near full-scale shot noise, indicating the dominance of noise generation by a single source, likely the interface between the perovskite and the spiro-OMeTAD hole-transport layer. We argue that the strong 1/f noise term has contributions both from the perovskite layer and interfaces. It displays non-ideal dependence on photocurrent, $S \propto I^{1.4}$ (instead of usual $S \propto I^2$ ), which is likely due to current-induced halide migration. Finally, we observe generation-recombination noise. The relaxation time of this process grows linearly with photocurrent, which allows to attribute this contribution to bimolecular recombination in the perovskite bulk absorption layer. Extrapolating our results, we estimate that at the standard 1 sun illumination the electron-hole recombination time is 5 microseconds.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Lessons on Star-forming Ultra-diffuse Galaxies from The Stacked Spectra of Sloan Digital Sky Survey

We investigate the on-average properties for 28 star-forming ultra-diffuse galaxies (UDGs) located in low-density environments, by stacking their spectra from the Sloan Digital Sky Survey. These relatively-isolated UDGs, with stellar masses of $\log_{10}(M_*/M_{\odot})\sim 8.57\pm0.29$, have the on-average total-stellar-metallicity [M/H]$\sim -0.82\pm0.14$, iron-metallicity [Fe/H]$\sim -1.00\pm0.16$, stellar age $t_*\sim5.2\pm0.5$ Gyr, $α$-enhancement [$α$/Fe]$\sim 0.24\pm0.10$, and oxygen abundance 12+log(O/H)$\sim 8.16\pm0.06$, as well as central stellar velocity dispersion $54\pm12$ km/s. On the star-formation rate versus stellar mass diagram, these UDGs are located lower than the extrapolated star-forming main sequence from the massive spirals, but roughly follow the main sequence of low-surface-brightness dwarf galaxies. We find that these star-forming UDGs are not particularly metal-poor or metal-rich for their stellar masses, as compared with the metallicity-mass relations of the nearby typical dwarfs. With the UDG data of this work and previous studies, we also find a coarse correlation between [Fe/H] and magnesium-element enhancement [Mg/Fe] for UDGs: [Mg/Fe]$\simeq-0.43(\pm0.26)$[Fe/H]$-0.14(\pm0.40)$.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

One-Shot Texture Retrieval with Global Context Metric

In this paper, we tackle one-shot texture retrieval: given an example of a new reference texture, detect and segment all the pixels of the same texture category within an arbitrary image. To address this problem, we present an OS-TR network to encode both reference and query image, leading to achieve texture segmentation towards the reference category. Unlike the existing texture encoding methods that integrate CNN with orderless pooling, we propose a directionality-aware module to capture the texture variations at each direction, resulting in spatially invariant representation. To segment new categories given only few examples, we incorporate a self-gating mechanism into relation network to exploit global context information for adjusting per-channel modulation weights of local relation features. Extensive experiments on benchmark texture datasets and real scenarios demonstrate the above-par segmentation performance and robust generalization across domains of our proposed method.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Catch'Em All: Locating Multiple Diffusion Sources in Networks with Partial Observations

This paper studies the problem of locating multiple diffusion sources in networks with partial observations. We propose a new source localization algorithm, named Optimal-Jordan-Cover (OJC). The algorithm first extracts a subgraph using a candidate selection algorithm that selects source candidates based on the number of observed infected nodes in their neighborhoods. Then, in the extracted subgraph, OJC finds a set of nodes that "cover" all observed infected nodes with the minimum radius. The set of nodes is called the Jordan cover, and is regarded as the set of diffusion sources. Considering the heterogeneous susceptible-infected-recovered (SIR) diffusion in the Erdos-Renyi (ER) random graph, we prove that OJC can locate all sources with probability one asymptotically with partial observations. OJC is a polynomial-time algorithm in terms of network size. However, the computational complexity increases exponentially in $m,$ the number of sources. We further propose a low-complexity heuristic based on the K-Means for approximating the Jordan cover, named Approximate-Jordan-Cover (AJC). Simulations on random graphs and real networks demonstrate that both AJC and OJC significantly outperform other heuristic algorithms.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Simultaneous band gap narrowing and carrier lifetime prolongation of organic-inorganic trihalide perovskites

The organic-inorganic hybrid lead trihalide perovskites have been emerging as the most attractive photovoltaic material. As regulated by Shockley-Queisser theory, a formidable materials science challenge for the next level improvement requires further band gap narrowing for broader absorption in solar spectrum, while retaining or even synergistically prolonging the carrier lifetime, a critical factor responsible for attaining the near-band gap photovoltage. Herein, by applying controllable hydrostatic pressure we have achieved unprecedented simultaneous enhancement in both band gap narrowing and carrier lifetime prolongation (up to 70~100% increase) under mild pressures at ~0.3 GPa. The pressure-induced modulation on pure hybrid perovskites without introducing any adverse chemical or thermal effect clearly demonstrates the importance of band edges on the photon-electron interaction and maps a pioneering route towards a further boost in their photovoltaic performance.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Combining upper limits with a Bayesian approach

We discuss how to determine and combine upper limits based on observed events and estimated backgrounds with a Bayesian method, when insignificant signals are observed in independent measurements. In addition to some general features deduced from the analytical formulae, systematic numerical results are obtained by a C$++$ program (CULBA) for low-count experiments, which can be used as a reference to combine two upper limits.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Distributed Rate and Power Control in Vehicular Networks

The focus of this paper is on the rate and power control algorithms in Dedicated Short Range Communication (DSRC) for vehicular networks. We first propose a utility maximization framework by leveraging the well-developed network congestion control, and formulate two subproblems, one on rate control with fixed transmit powers and the other on power control with fixed rates. Distributed rate control and power control algorithms are developed to solve these two subproblems, respectively, and are proved to be asymptotically optimal. Joint rate and power control can be done by using the two algorithms in an alternating fashion. The performance enhancement of our algorithms compared with a recent rate control algorithm, called EMBARC, is evaluated by using the network simulator ns2.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Source Localization in Networks: Trees and Beyond

Information diffusion in networks can be used to model many real-world phenomena, including rumor spreading on online social networks, epidemics in human beings, and malware on the Internet. Informally speaking, the source localization problem is to identify a node in the network that provides the best explanation of the observed diffusion. Despite significant efforts and successes over last few years, theoretical guarantees of source localization algorithms were established only for tree networks due to the complexity of the problem. This paper presents a new source localization algorithm, called the Short-Fat Tree (SFT) algorithm. Loosely speaking, the algorithm selects the node such that the breadth-first search (BFS) tree from the node has the minimum depth but the maximum number of leaf nodes. Performance guarantees of SFT under the independent cascade (IC) model are established for both tree networks and the Erdos-Renyi (ER) random graph. On tree networks, SFT is the maximum a posterior (MAP) estimator. On the ER random graph, the following fundamental limits have been obtained: $(i)$ when the infection duration $<\frac{2}{3}t_u,$ SFT identifies the source with probability one asymptotically, where $t_u=\left\lceil\frac{\log n}{\log μ}\right\rceil+2$ and $μ$ is the average node degree, $(ii)$ when the infection duration $>t_u,$ the probability of identifying the source approaches zero asymptotically under any algorithm; and $(iii)$ when infection duration $<t_u,$ the BFS tree starting from the source is a fat tree. Numerical experiments on tree networks, the ER random graphs and real world networks with different evaluation metrics show that the SFT algorithm outperforms existing algorithms.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Unconventional interfacial superconductivity in epitaxial Bi/Ni heterostructures

Superconductivity (SC) is one of the most intriguing physical phenomena in nature. Nucleation of SC has long been considered highly unfavorable if not impossible near ferromagnetism, in low dimensionality and, above all, out of non-superconductor. Here we report observation of SC with TC near 4 K in Ni/Bi bilayers that defies all known paradigms of superconductivity, where neither ferromagnetic Ni film nor rhombohedra Bi film is superconducting in isolation. This highly unusual SC is independent of the growth order (Ni/Bi or Bi/Ni), but highly sensitive to the constituent layer thicknesses. Most importantly, the SC, distinctively non-s pairing, is triggered from, but does not occur at, the Bi/Ni interface. Using point contact Andreev reflection, we show evidences that the unique SC, naturally compatible with magnetism, is triplet p-wave pairing. This new revelation may lead to unconventional avenues to explore novel SC for applications in superconducting spintronics.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

Collaborative Filtering with Information-Rich and Information-Sparse Entities

In this paper, we consider a popular model for collaborative filtering in recommender systems where some users of a website rate some items, such as movies, and the goal is to recover the ratings of some or all of the unrated items of each user. In particular, we consider both the clustering model, where only users (or items) are clustered, and the co-clustering model, where both users and items are clustered, and further, we assume that some users rate many items (information-rich users) and some users rate only a few items (information-sparse users). When users (or items) are clustered, our algorithm can recover the rating matrix with $ω(MK \log M)$ noisy entries while $MK$ entries are necessary, where $K$ is the number of clusters and $M$ is the number of items. In the case of co-clustering, we prove that $K^2$ entries are necessary for recovering the rating matrix, and our algorithm achieves this lower bound within a logarithmic factor when $K$ is sufficiently large. We compare our algorithms with a well-known algorithms called alternating minimization (AM), and a similarity score-based algorithm known as the popularity-among-friends (PAF) algorithm by applying all three to the MovieLens and Netflix data sets. Our co-clustering algorithm and AM have similar overall error rates when recovering the rating matrix, both of which are lower than the error rate under PAF. But more importantly, the error rate of our co-clustering algorithm is significantly lower than AM and PAF in the scenarios of interest in recommender systems: when recommending a few items to each user or when recommending items to users who only rated a few items (these users are the majority of the total user population). The performance difference increases even more when noise is added to the datasets.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

Jointly Clustering Rows and Columns of Binary Matrices: Algorithms and Trade-offs

In standard clustering problems, data points are represented by vectors, and by stacking them together, one forms a data matrix with row or column cluster structure. In this paper, we consider a class of binary matrices, arising in many applications, which exhibit both row and column cluster structure, and our goal is to exactly recover the underlying row and column clusters by observing only a small fraction of noisy entries. We first derive a lower bound on the minimum number of observations needed for exact cluster recovery. Then, we propose three algorithms with different running time and compare the number of observations needed by them for successful cluster recovery. Our analytical results show smooth time-data trade-offs: one can gradually reduce the computational complexity when increasingly more observations are available.

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preprint2014arXiv

Locating Contagion Sources in Networks with Partial Timestamps

This paper studies the problem of identifying the contagion source when partial timestamps of a contagion process are available. We formulate the source localization problem as a ranking problem on graphs, where infected nodes are ranked according to their likelihood of being the source. Two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed in this paper. Experimental evaluations with synthetic and real-world data show that our algorithms significantly improve the ranking accuracy compared with four existing algorithms.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

A Robust Information Source Estimator with Sparse Observations

In this paper, we consider the problem of locating the information source with sparse observations. We assume that a piece of information spreads in a network following a heterogeneous susceptible-infected-recovered (SIR) model and that a small subset of infected nodes are reported, from which we need to find the source of the information. We adopt the sample path based estimator developed in [1], and prove that on infinite trees, the sample path based estimator is a Jordan infection center with respect to the set of observed infected nodes. In other words, the sample path based estimator minimizes the maximum distance to observed infected nodes. We further prove that the distance between the estimator and the actual source is upper bounded by a constant independent of the number of infected nodes with a high probability on infinite trees. Our simulations on tree networks and real world networks show that the sample path based estimator is closer to the actual source than several other algorithms.

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preprint2013arXiv

Information Source Detection in the SIR Model: A Sample Path Based Approach

This paper studies the problem of detecting the information source in a network in which the spread of information follows the popular Susceptible-Infected-Recovered (SIR) model. We assume all nodes in the network are in the susceptible state initially except the information source which is in the infected state. Susceptible nodes may then be infected by infected nodes, and infected nodes may recover and will not be infected again after recovery. Given a snapshot of the network, from which we know all infected nodes but cannot distinguish susceptible nodes and recovered nodes, the problem is to find the information source based on the snapshot and the network topology. We develop a sample path based approach where the estimator of the information source is chosen to be the root node associated with the sample path that most likely leads to the observed snapshot. We prove for infinite-trees, the estimator is a node that minimizes the maximum distance to the infected nodes. A reverse-infection algorithm is proposed to find such an estimator in general graphs. We prove that for $g$-regular trees such that $gq>1,$ where $g$ is the node degree and $q$ is the infection probability, the estimator is within a constant distance from the actual source with a high probability, independent of the number of infected nodes and the time the snapshot is taken. Our simulation results show that for tree networks, the estimator produced by the reverse-infection algorithm is closer to the actual source than the one identified by the closeness centrality heuristic. We then further evaluate the performance of the reverse infection algorithm on several real world networks.

0 citations0 reviewsNo code linkedOpen access