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Wenjun Li

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

ResearcherUnclaimed source record
Data Structures and Algorithmshep-phComputer Visioncond-mat.mes-hallcond-mat.mtrl-sciInformation Theorymath.IT

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Published work

9 published item(s)

preprint2026arXiv

HiSem: Hierarchical Semantic Disentangling for Remote Sensing Image Change Captioning

Remote sensing image change captioning (RSICC) aims to achieve high-level semantic understanding of genuine changes occurring between bi-temporal images. Despite notable progress, existing methods are fundamentally limited by a shared modeling assumption: changed and unchanged image pairs, which have intrinsically different semantic granularities, are processed under a unified modeling strategy. This modeling inconsistency leads to semantic entanglement between coarse-grained change existence judgment and fine-grained semantic understanding.To address the above limitation, we propose a novel hierarchical semantic disentangling network (HiSem) that explicitly disentangles semantic representations of different granularities. Specifically, we first introduce the Bidirectional Differential Attention Modulation (BDAM) module that leverages discrepancy-aware attention to enhance cross-temporal interactions, thereby amplifying true change signals while suppressing irrelevant variations. Building upon this, we design a Hierarchical Adaptive Semantic Disentanglement (HASD) module that performs adaptive routing at two hierarchical levels: a coarse-grained image-level routing mechanism distinguishes changed and unchanged image pairs, while a fine-grained token-level Mixture-of-Experts (MoE) block models diverse and heterogeneous change semantics for changed samples. Extensive experiments on two benchmark datasets demonstrate that HiSem outperfoms previous methods, achieving a significant improvement of +7.52\% BLEU-4 on the WHU-CDC dataset. More importantly, our approach provides a structured perspective for RSICC by explicitly aligning model design with the intrinsic semantic heterogeneity of bi-temporal scenes. The code will be available at https://github.com/Man-Wang-star/HiSem

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Improved Kernels and Algorithms for Claw and Diamond Free Edge Deletion Based on Refined Observations

In the {claw, diamond}-free edge deletion problem, we are given a graph $G$ and an integer $k>0$, the question is whether there are at most $k$ edges whose deletion results in a graph without claws and diamonds as induced graphs. Based on some refined observations, we propose a kernel of $O(k^3)$ vertices and $O(k^4)$ edges, significantly improving the previous kernel of $O(k^{12})$ vertices and $O(k^{24})$ edges. In addition, we derive an $O^*(3.792^k)$-time algorithm for the {claw, diamond}-free edge deletion problem.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Doubly cvharged vector leptons and the Higgs portal

Using a bottom up phenomenological approach we constructed a simple doubly charged vector lepton $E^{\pm\pm}$ model for the possible 750 GeV diphoton resonance $Φ$ at the LHC assuming it to be a scalar particle. Since no stable doubly charged leptons are seen, to facilitate their decays we complete the model by adding a charged SM electroweak scalar $S^\pm$. $Φ$ is a SM singlet and can be either an inert scalar or a Higgs field. In the inert case more than one vector lepton are required to account for the photon fusion production of the resonance if the model is to remain perturbative. For a Higgssed case $S^\pm$ can assist the production mechanism without using more than one such lepton. We also found that precision measurements constrain the couplings of $E^{\pm\pm}$ and $S^\pm$ to SM particles to be small. This raises the possibility that they can be fairly long lived and can give rise to displaced vertices if produced at the LHC.

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preprint2016arXiv

Further Kernelization of Proper Interval Vertex Deletion: New Observations and Refined Analysis

In the Proper Interval Vertex Deletion problem (PIVD for short), we are given a graph $G$ and an integer parameter $k>0$, and the question is whether there are at most $k$ vertices in $G$ whose removal results in a proper interval graph. It is known that the PIVD problem is fixed-parameter tractable and admits a polynomial but "unreasonably" large kernel of $O(k^{53})$ vertices. A natural question is whether the problem admits a polynomial kernel of "reasonable" size. In this paper, we answer this question by deriving an $O(k^7)$-vertex kernel for the PIVD problem. Our kernelization is based on several new observations and a refined analysis of the kernelization.

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preprint2015arXiv

Polarization-induced Zener Tunnel Diodes in GaN/InGaN/GaN Heterojunctions

By the insertion of thin InGaN layers into Nitrogen-polar GaN p-n junctions, polarization-induced Zener tunnel junctions are studied. The reverse-bias interband Zener tunneling current is found to be weakly temperature dependent, as opposed to the strongly temperature-dependent forward bias current. This indicates tunneling as the primary reverse-bias current transport mechanism. The Indium composition in the InGaN layer is systematically varied to demonstrate the increase in the interband tunneling current. Comparing the experimentally measured tunneling currents to a model helps identify the specific challenges in potentially taking such junctions towards nitride-based polarization-induced tunneling field-effect transistors.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

A $2k$-Vertex Kernel for Maximum Internal Spanning Tree

We consider the parameterized version of the maximum internal spanning tree problem, which, given an $n$-vertex graph and a parameter $k$, asks for a spanning tree with at least $k$ internal vertices. Fomin et al. [J. Comput. System Sci., 79:1-6] crafted a very ingenious reduction rule, and showed that a simple application of this rule is sufficient to yield a $3k$-vertex kernel. Here we propose a novel way to use the same reduction rule, resulting in an improved $2k$-vertex kernel. Our algorithm applies first a greedy procedure consisting of a sequence of local exchange operations, which ends with a local-optimal spanning tree, and then uses this special tree to find a reducible structure. As a corollary of our kernel, we obtain a deterministic algorithm for the problem running in time $4^k \cdot n^{O(1)}$.

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preprint2014arXiv

RPV SUSY effects in $τ^- \to e^-(μ^-) K\bar{K}$ Decays

In this paper, we investigate $τ^- \to e^-(μ^-) K\bar{K}(K\bar{K}=K ^+K^-,K^0\bar{K}^0)$ decays in the framework of the RPV SUSY model. We discuss the tree level contribution of the sparticles $\tildeν$ and $\tilde{u}$ to these decay branching ratios. In the two channels, the $\tildeν$-mediated channel is more sensitive to the parameter product $|λ^{'*}_{i22}λ_{i31(2)}|$ than the $\tilde{u}$-mediated channel to $|λ^{'*}_{1(2)j2}λ'_{3j2}|$. And the parameter product $|λ^{'*}_{i22}λ_{i31(2)}|$ is severely constrained to the order of ${\cal O}(10^{-5})$ by the experiment data with $m_{\tildeν}=100 GeV$, which is one order of magnitude more stringent than before. In the calculation of hadronic matrix elements, the resonant effects are large than those of non-resonant terms. Especially, the resonant contribution of scalar meson $f_{(980)}$ plays a dominate role in $\tildeν$-mediated channel.

0 citations0 reviewsNo code linkedOpen access
preprint2009arXiv

Location-Aided Fast Distributed Consensus in Wireless Networks

Existing works on distributed consensus explore linear iterations based on reversible Markov chains, which contribute to the slow convergence of the algorithms. It has been observed that by overcoming the diffusive behavior of reversible chains, certain nonreversible chains lifted from reversible ones mix substantially faster than the original chains. In this paper, we investigate the idea of accelerating distributed consensus via lifting Markov chains, and propose a class of Location-Aided Distributed Averaging (LADA) algorithms for wireless networks, where nodes' coarse location information is used to construct nonreversible chains that facilitate distributed computing and cooperative processing. First, two general pseudo-algorithms are presented to illustrate the notion of distributed averaging through chain-lifting. These pseudo-algorithms are then respectively instantiated through one LADA algorithm on grid networks, and one on general wireless networks. For a $k\times k$ grid network, the proposed LADA algorithm achieves an $ε$-averaging time of $O(k\log(ε^{-1}))$. Based on this algorithm, in a wireless network with transmission range $r$, an $ε$-averaging time of $O(r^{-1}\log(ε^{-1}))$ can be attained through a centralized algorithm. Subsequently, we present a fully-distributed LADA algorithm for wireless networks, which utilizes only the direction information of neighbors to construct nonreversible chains. It is shown that this distributed LADA algorithm achieves the same scaling law in averaging time as the centralized scheme. Finally, we propose a cluster-based LADA (C-LADA) algorithm, which, requiring no central coordination, provides the additional benefit of reduced message complexity compared with the distributed LADA algorithm.

0 citations0 reviewsNo code linkedOpen access