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Xiaoping Wang

Publications and source records attributed to Xiaoping Wang.

At least 55 records · Page 3Linked to original sources

A Dual-Stream Recurrence-Attention Network With Global-Local Awareness for Emotion Recognition in Textual Dialog

In real-world dialog systems, the ability to understand the user's emotions and interact anthropomorphically is of great significance. Emotion Recognition in Conversation (ERC) is one of the key ways to accomplish this goal and has attracted growing attention. How to model the context in a conversation is a central aspect and a major challenge of ERC tasks. Most existing approaches struggle to adequately incorporate both global and local contextual information, and their network structures are overly sophisticated. For this reason, we propose a simple and effective Dual-stream Recurrence-Attention Network (DualRAN), which is based on Recurrent Neural Network (RNN) and Multi-head ATtention network (MAT). DualRAN eschews the complex components of current methods and focuses on combining recurrence-based methods with attention-based ones. DualRAN is a dual-stream structure mainly consisting of local- and global-aware modules, modeling a conversation simultaneously from distinct perspectives. In addition, we develop two single-stream network variants for DualRAN, i.e., SingleRANv1 and SingleRANv2. According to the experimental findings, DualRAN boosts the weighted F1 scores by 1.43% and 0.64% on the IEMOCAP and MELD datasets, respectively, in comparison to the strongest baseline. On two other datasets (i.e., EmoryNLP and DailyDialog), our method also attains competitive results.

cs.CL↗

GA2MIF: Graph and Attention Based Two-Stage Multi-Source Information Fusion for Conversational Emotion Detection

Multimodal Emotion Recognition in Conversation (ERC) plays an influential role in the field of human-computer interaction and conversational robotics since it can motivate machines to provide empathetic services. Multimodal data modeling is an up-and-coming research area in recent years, which is inspired by human capability to integrate multiple senses. Several graph-based approaches claim to capture interactive information between modalities, but the heterogeneity of multimodal data makes these methods prohibit optimal solutions. In this work, we introduce a multimodal fusion approach named Graph and Attention based Two-stage Multi-source Information Fusion (GA2MIF) for emotion detection in conversation. Our proposed method circumvents the problem of taking heterogeneous graph as input to the model while eliminating complex redundant connections in the construction of graph. GA2MIF focuses on contextual modeling and cross-modal modeling through leveraging Multi-head Directed Graph ATtention networks (MDGATs) and Multi-head Pairwise Cross-modal ATtention networks (MPCATs), respectively. Extensive experiments on two public datasets (i.e., IEMOCAP and MELD) demonstrate that the proposed GA2MIF has the capacity to validly capture intra-modal long-range contextual information and inter-modal complementary information, as well as outperforms the prevalent State-Of-The-Art (SOTA) models by a remarkable margin.

cs.MM↗

GraphCFC: A Directed Graph Based Cross-Modal Feature Complementation Approach for Multimodal Conversational Emotion Recognition

Emotion Recognition in Conversation (ERC) plays a significant part in Human-Computer Interaction (HCI) systems since it can provide empathetic services. Multimodal ERC can mitigate the drawbacks of uni-modal approaches. Recently, Graph Neural Networks (GNNs) have been widely used in a variety of fields due to their superior performance in relation modeling. In multimodal ERC, GNNs are capable of extracting both long-distance contextual information and inter-modal interactive information. Unfortunately, since existing methods such as MMGCN directly fuse multiple modalities, redundant information may be generated and diverse information may be lost. In this work, we present a directed Graph based Cross-modal Feature Complementation (GraphCFC) module that can efficiently model contextual and interactive information. GraphCFC alleviates the problem of heterogeneity gap in multimodal fusion by utilizing multiple subspace extractors and Pair-wise Cross-modal Complementary (PairCC) strategy. We extract various types of edges from the constructed graph for encoding, thus enabling GNNs to extract crucial contextual and interactive information more accurately when performing message passing. Furthermore, we design a GNN structure called GAT-MLP, which can provide a new unified network framework for multimodal learning. The experimental results on two benchmark datasets show that our GraphCFC outperforms the state-of-the-art (SOTA) approaches.

cs.CL↗

Non-collinear 2k antiferromagnetism in the Zintl semiconductor Eu$_5$In$_2$Sb$_6$

Eu$_5$In$_2$Sb$_6$ is an orthorhombic non-symmorphic small band gap semiconductor with three distinct Eu$^{2+}$ sites and two low-temperature magnetic phase transitions. The material displays one of the greatest (negative) magnetoresistances of known stoichiometric antiferromagnets and belongs to a family of Zintl materials that may host an axion insulator. Using single crystal neutron diffraction, we show that the $T_{\mathrm{N1}}=14\mathrm{~K}$ second-order phase transition is associated with long-range antiferromagnetic order within the chemical unit cell $\left( k_1 = (000) \right)$. Upon cooling below $T_{\mathrm{N1}}$, the relative sublattice magnetizations of this structure vary until a second-order phase transition at $T_{\mathrm{N2}}=7\mathrm{~K}$ that doubles the unit cell along the $\hat{c}$ axis $\left( k_2 = \left(00\frac{1}{2}\right) \right)$. We show the anisotropic susceptibility and our magnetic neutron diffraction data are consistent with magnetic structures described by the $Γ_3$ irreducible representation with the staggered magnetization of the $k_1$ and $k_2$ components polarized along the $\hat{b}$ and $\hat{a}$ axis, respectively. As the $k_2$ component develops, the amplitude of the $k_1$ component is reduced, which indicates a 2k non-collinear magnetic structure. Density functional theory is used to calculate the energies of these magnetic structures and to show the $k_1$ phase is a metal so $T_{\mathrm{N1}}$ is a rare example of a unit-cell-preserving second-order phase transition from a paramagnetic semiconductor to an antiferromagnetic metal. DFT indicates the transition at $T_{\mathrm{N2}}$ to a doubled unit cell reduces the carrier density of the metal, which is consistent with resistivity data.

cond-mat.str-el↗

Structure transition and zigzag magnetic order in Ir/Rh-substituted honeycomb lattice RuCl3

We report magnetization and neutron diffraction studies on crystal and magnetic structures of Ir- and Rh-substituted honeycomb lattice $α$-RuCl$_3$. The iridium or rhodium atoms are distributed at the Ru site with little structural modification. Both systems undergo a room-temperature monoclinic $C2/m$ to low-temperature trigonal $R\bar{3}$ phase transformation with a large recoverable hysteresis. At low temperature, a zigzag spin order is observed with the same characteristic wavevector $(0,0.5,1)$ as in the parent $α$-RuCl$_3$. Detailed magnetic structure refinement reveals an ordered moment of $\rm 0.32(5) μ_B/Ru$ and a upper boundary of canting angle of $15(4)^\circ$ away from the basal plane at 5~K for the 10\% Ir-substituted $α$-RuCl$_3$, which is different from the 0.45-0.73~$\rm μ_B/Ru$ and $32^\circ$-$48^\circ$ canting angle reported in the parent compound $α$-RuCl$_3$. The observation of unchanged RuCl$_6$ local octahedral environment, reduced magnetic moment size and canting angle highlights the potential to study quantum spin liquid behavior through non-magnetic ion doping.

cond-mat.mtrl-sci↗

Watch the Speakers: A Hybrid Continuous Attribution Network for Emotion Recognition in Conversation With Emotion Disentanglement

Emotion Recognition in Conversation (ERC) has attracted widespread attention in the natural language processing field due to its enormous potential for practical applications. Existing ERC methods face challenges in achieving generalization to diverse scenarios due to insufficient modeling of context, ambiguous capture of dialogue relationships and overfitting in speaker modeling. In this work, we present a Hybrid Continuous Attributive Network (HCAN) to address these issues in the perspective of emotional continuation and emotional attribution. Specifically, HCAN adopts a hybrid recurrent and attention-based module to model global emotion continuity. Then a novel Emotional Attribution Encoding (EAE) is proposed to model intra- and inter-emotional attribution for each utterance. Moreover, aiming to enhance the robustness of the model in speaker modeling and improve its performance in different scenarios, A comprehensive loss function emotional cognitive loss $\mathcal{L}_{\rm EC}$ is proposed to alleviate emotional drift and overcome the overfitting of the model to speaker modeling. Our model achieves state-of-the-art performance on three datasets, demonstrating the superiority of our work. Another extensive comparative experiments and ablation studies on three benchmarks are conducted to provided evidence to support the efficacy of each module. Further exploration of generalization ability experiments shows the plug-and-play nature of the EAE module in our method.

cs.CL↗

Disorder-induced excitation continuum in a spin-1/2 cobaltate on a triangular lattice

A spin-1/2 triangular-lattice antiferromagnet is a prototypical frustrated quantum magnet, which exhibits remarkable quantum many-body effects that arise from the synergy between geometric spin frustration and quantum fluctuations. It can host quantum frustrated magnetic topological phenomena like quantum spin liquid (QSL) states, highlighted by the presence of fractionalized quasiparticles within a continuum of magnetic excitations. In this work, we use neutron scattering to study CoZnMo$_3$O$_8$, which has a triangular lattice of Jeff = 1/2 Co2+ ions with octahedral coordination. We found a wave-vector-dependent excitation continuum at low energy that disappears with increasing temperature. Although these excitations are reminiscent of a spin excitation continuum in a QSL state, their presence in CoZnMo$_3$O$_8$ originates from magnetic intersite disorder-induced dynamic spin states with peculiar excitations. Our results, therefore, give direct experimental evidence for the presence of a disorder-induced spin excitation continuum.

cond-mat.str-el↗

Interlayer donor-acceptor pair excitons in MoSe2/WSe2 moiré heterobilayer

Localized interlayer excitons (LIXs) in two-dimensional moiré superlattices exhibit sharp and dense emission peaks, making them promising as highly tunable single-photon sources. However, the fundamental nature of these LIXs is still elusive. Here, we show the donor-acceptor pair (DAP) mechanism as one of the origins of these excitonic peaks. Numerical simulation results of the DAP model agree with the experimental photoluminescence spectra of LIX in the moiré MoSe2/WSe2 heterobilayer. In particular, we find that the emission energy-lifetime correlation and the nonmonotonic power dependence of the lifetime agree well with the DAP IX model. Our results provide insight into the physical mechanism of LIX formation in moiré heterostructures and pave new directions for engineering interlayer exciton properties in moiré superlattices.

cond-mat.mes-hall↗

Superconductivity by alloying the topological insulator SnBi2Te4

Alloying indium into the topological insulator Sn1-xInxBi2Te4 induces bulk superconductivity with critical temperatures Tc up to 1.85 K and upper critical fields up to about 14 kOe. This is confirmed by electrical resistivity, heat capacity, and magnetic susceptibility measurements. The heat capacity shows a discontinuity at Tc and temperature dependence below Tc consistent with weak coupling BCS theory, and suggests a superconducting gap near 0.25 meV. The superconductivity is type-II and the topological surface states have been verified by photoemission. A simple picture suggests analogies with the isostructural magnetic topological insulator MnBi2Te4, in which a natural heterostructure hosts complementary properties on different sublattices, and motivates new interest in this large family of compounds. The existence of both topological surface states and superconductivity in Sn1-xInxBi2Te4 identifies these materials as promising candidates for the study of topological superconductivity.

cond-mat.supr-con↗

Spin waves and magnetic exchange Hamiltonian in CrSBr

CrSBr is an air-stable 2D van der Waals semiconducting magnet with great technological promise, but its atomic-scale magnetic interactions -- crucial information for high-frequency switching -- are poorly understood. We present an experimental study to determine the CrSBr magnetic exchange Hamiltonian and bulk magnon spectrum. We confirm the $A$-type antiferromagnetic order using single crystal neutron diffraction. We also measure the magnon dispersions using inelastic neutron scattering and rigorously fit the excitation modes to a spin wave model. The magnon spectrum is well described by an intra-plane ferromagnetic Heisenberg exchange model with seven nearest in-plane exchanges. This fitted exchange Hamiltonian enables theoretical predictions of CrSBr behavior: as one example, we use the fitted Hamiltonian to predict the presence of chiral magnon edge modes with a spin-orbit enhanced CrSBr heterostructure.

cond-mat.mtrl-sci↗

Multimodal Representations Learning Based on Mutual Information Maximization and Minimization and Identity Embedding for Multimodal Sentiment Analysis

Multimodal sentiment analysis (MSA) is a fundamental complex research problem due to the heterogeneity gap between different modalities and the ambiguity of human emotional expression. Although there have been many successful attempts to construct multimodal representations for MSA, there are still two challenges to be addressed: 1) A more robust multimodal representation needs to be constructed to bridge the heterogeneity gap and cope with the complex multimodal interactions, and 2) the contextual dynamics must be modeled effectively throughout the information flow. In this work, we propose a multimodal representation model based on Mutual information Maximization and Minimization and Identity Embedding (MMMIE). We combine mutual information maximization between modal pairs, and mutual information minimization between input data and corresponding features to mine the modal-invariant and task-related information. Furthermore, Identity Embedding is proposed to prompt the downstream network to perceive the contextual information. Experimental results on two public datasets demonstrate the effectiveness of the proposed model.

cs.LG↗

Anisotropic magnon damping by zero-temperature quantum fluctuations in ferromagnetic CrGeTe$_3$

Spin and lattice are two fundamental degrees of freedom in a solid, and their fluctuations about the equilibrium values in a magnetic ordered crystalline lattice form quasiparticles termed magnons (spin waves) and phonons (lattice waves), respectively. In most materials with strong spin-lattice coupling (SLC), the interaction of spin and lattice induces energy gaps in the spin wave dispersion at the nominal intersections of magnon and phonon modes. Here we use neutron scattering to show that in the two-dimensional (2D) van der Waals honeycomb lattice ferromagnetic CrGeTe3, spin waves propagating within the 2D plane exhibit an anomalous dispersion, damping, and break-down of quasiparticle conservation, while magnons along the c axis behave as expected for a local moment ferromagnet. These results indicate the presence of dynamical SLC arising from the zero-temperature quantum fluctuations in CrGeTe3, suggesting that the observed in-plane spin waves are mixed spin and lattice quasiparticles fundamentally different from pure magnons and phonons.

cond-mat.str-el↗

Electronic properties and phase transition in Kagome metal, Yb0.5Co3Ge3

The Kagome lattice is an important fundamental structure in condensed matter physics for investigating the interplay of electron correlation, topology, and frustrated magnetism. Recent work on Kagome metals in the AV3Sb5 (A = K, Rb, Cs) family, has shown a multitude of correlation-driven distortions, including symmetry breaking charge density waves and nematic superconductivity at low temperatures. Here we study the new Kagome metal Yb0.5Co3Ge3 and find a temperature-dependent kink in the resistivity that is highly similar to the AV3Sb5 behavior and is commensurate with an in-plane structural distortion of the Co Kagome lattice along with a doubling of the c-axis. The space group is found to lower from P6/mmm to P63/m below the transition temperature, breaking the in-plane mirror planes and C6 rotation, while gaining a screw axis along the c-direction. At very low temperatures, anisotropic negative magnetoresistance is observed, which may be related to anisotropic magnetism. This raises questions about the types of the distortions in Kagome nets and their resulting physical properties including superconductivity and magnetism.

cond-mat.str-el↗

The Role of the Third Dimension in Searching Majorana Fermions in $α$-RuCl$_3$ via Phonons

Understanding phonons in $α$-RuCl$_3$ is critical to analyze the controversy around the observation of the half-integer thermal quantum Hall effect. While many studies have focused on the magnetic excitations in $α$-RuCl$_3$, its vibrational excitation spectrum has remained relatively unexplored. We investigate the phonon structure of $α$-RuCl$_3$ via inelastic neutron scattering experiments and density functional theory calculations. Our results show excellent agreement between experiment and first principles calculations. After validating our theoretical model, we extrapolate the low energy phonon properties. We find that the phonons in $α$-RuCl$_3$ that either propagate or vibrate in the out-of-plane direction have significantly reduced velocities, and therefore have the potential to dominate the observability of the elusive half integer plateaus in the thermal Hall conductance. In addition, we use low-energy interlayer phonons to resolve the low temperature stacking structure of our large crystal of $α$-RuCl$_3$, which we find to be consistent with that of the $R\bar{3}$ space group, in agreement with neutron diffraction.

cond-mat.str-el↗

Neutron-diffraction and linear {Grüneisen} parameter studies of magnetism in NdFe$_2$Ga$_8$

We study the magnetism in NdFe$_2$Ga$_8$ by the neutron-diffraction and temperature-modulated linear {Grüneisen} parameter measurements. Previous thermodynamical measurements have demonstrated that there are two magnetic transitions at 10 and 14.5 K, respectively. Neutron-diffraction measurements confirm that the lower one is an antiferromagnetic (AFM) transition with a commensurate magnetic structure. Both the commensurate and the incommensurate (IC) magnetic peaks are found below the higher transition but their intensities only gradually increase with decreasing temperature. Below 10 K, the commensurate peak intensity increases quickly with decreasing temperature, signaling the AFM transition, while the IC peak intensity disappears below 5 K. The linear {Grüneisen} parameter along the $c$ axis, $Γ_c$, shows a hysteresis behavior that is different from the hysteresis behavior for the magnetization $M$. We give a discussion of the origin of the magnetism in NdFe$_2$Ga$_8$.

cond-mat.str-el↗

Tree-based Search Graph for Approximate Nearest Neighbor Search

Nearest neighbor search supports important applications in many domains, such as database, machine learning, computer vision. Since the computational cost for accurate search is too high, the community turned to the research of approximate nearest neighbor search (ANNS). Among them, graph-based algorithm is one of the most important branches. Research by Fu et al. shows that the algorithms based on Monotonic Search Network (MSNET), such as NSG and NSSG, have achieved the state-of-the-art search performance in efficiency. The MSNET is dedicated to achieving monotonic search with minimal out-degree of nodes to pursue high efficiency. However, the current MSNET designs did not optimize the probability of the monotonic search, and the lower bound of the probability is only 50%. If they fail in monotonic search stage, they have to suffer tremendous backtracking cost to achieve the required accuracy. This will cause performance problems in search efficiency. To address this problem, we propose (r,p)-MSNET, which achieves guaranteed probability on monotonic search. Due to the high building complexity of a strict (r,p)-MSNET, we propose TBSG, which is an approximation with low complexity. Experiment conducted on four million-scaled datasets show that TBSG outperforms existing state-of-the-art graph-based algorithms in search efficiency. Our code has been released on Github.

cs.IR↗

Site Mixing for Engineering Magnetic Topological Insulators

The van der Waals compound, MnBi$_2$Te$_4$, is the first intrinsic magnetic topological insulator, providing a materials platform for exploring exotic quantum phenomena such as the axion insulator state and the quantum anomalous Hall effect. However, intrinsic structural imperfections lead to bulk conductivity, and the roles of magnetic defects are still unknown. With higher concentrations of same types of magnetic defects, the isostructural compound MnSb$_2$Te$_4$ is a better model system for a systematic investigation of the connections among magnetic, topology and lattice defects. In this work, the impact of antisite defects on the magnetism and electronic structure is studied in MnSb$_2$Te$_4$. Mn-Sb site mixing leads to complex magnetic structures and tunes the interlayer magnetic coupling between antiferromagnetic and ferromagnetic. The detailed nonstoichiometry and site-mixing of MnSb$_2$Te$_4$ crystals depend on the growth parameters, which can lead to $\approx$40\% of Mn sites occupied by Sb and $\approx$15\% of Sb sites by Mn in as-grown crystals. Single crystal neutron diffraction and electron microscopy studies show nearly random distribution of the antisite defects. Band structure calculations suggest that the Mn-Sb site-mixing favors a FM interlayer coupling, consistent with experimental observation, but is detrimental to the band inversion required for a nontrivial topology. Our results suggest a long range magnetic order of Mn ions sitting on Bi sites in MnBi$_2$Te$_4$. The effects of site mixing should be considered in all layered heterostructures that consist of alternating magnetic and topological layers, including the entire family of MnTe(Bi$_2$Te$_3$)$_n$, its Sb analogs and their solid solution.

cond-mat.mtrl-sci↗

Canted antiferromagnetic order and spin dynamics in the honeycomb-lattice Tb2Ir3Ga9

Single crystal neutron diffraction, inelastic neutron scattering, bulk magnetization measurements, and first-principles calculations are used to investigate the magnetic properties of the honeycomb lattice $\rm Tb_2Ir_3Ga_9$. While the $R\ln2$ magnetic contribution to the low-temperature entropy indicates a $\rm J_{eff}=1/2$ moment for the lowest-energy crystal-field doublet, the Tb$^{3+}$ ions form a canted antiferromagnetic structure below 12.5 K. Due to the Dzyalloshinskii-Moriya interactions, the Tb moments in the $ab$ plane are slightly canted towards $b$ by $6^\circ$ with a canted moment of 1.22 $μ_{\rm B} $ per formula unit. A minimal $xxz$ spin Hamiltonian is used to simultaneously fit the spin-wave frequencies along the high symmetry directions and the field dependence of the magnetization along the three crystallographic axes. Long-range magnetic interactions for both in-plane and out-of-plane couplings up to the second nearest neighbors are needed to account for the observed static and dynamic properties. The $z$ component of the exchange interactions between Tb moments are larger than the $x$ and $y$ components. This compound also exhibits bond-dependent exchange with negligible nearest exchange coupling between moments parallel and perpendicular to the 4$f$ orbitals. Despite the $J_{\rm eff}=1/2$ moments, the spin Hamiltonian is denominated by a large in-plane anisotropy $K_z \sim -1$ meV. DFT calculations confirm the antiferromagnetic ground state and the substantial inter-plane coupling at larger Tb-Tb distances.

cond-mat.str-el↗