arXiv subjects

Jin Cui

Publications and source records attributed to Jin Cui.

28 records · Page 2Linked to original sources

arXiv2024

CaDRec: Contextualized and Debiased Recommender Model

Recommender models aimed at mining users' behavioral patterns have raised great attention as one of the essential applications in daily life. Recent work on graph neural networks (GNNs) or debiasing methods has attained remarkable gains. However, they still suffer from (1) over-smoothing node embeddings caused by recursive convolutions with GNNs, and (2) the skewed distribution of interactions due to popularity and user-individual biases. This paper proposes a contextualized and debiased recommender model (CaDRec). To overcome the over-smoothing issue, we explore a novel hypergraph convolution operator that can select effective neighbors during convolution by introducing both structural context and sequential context. To tackle the skewed distribution, we propose two strategies for disentangling interactions: (1) modeling individual biases to learn unbiased item embeddings, and (2) incorporating item popularity with positional encoding. Moreover, we mathematically show that the imbalance of the gradients to update item embeddings exacerbates the popularity bias, thus adopting regularization and weighting schemes as solutions. Extensive experiments on four datasets demonstrate the superiority of the CaDRec against state-of-the-art (SOTA) methods. Our source code and data are released at https://github.com/WangXFng/CaDRec.

cs.IR↗

arXiv2024

NFARec: A Negative Feedback-Aware Recommender Model

Graph neural network (GNN)-based models have been extensively studied for recommendations, as they can extract high-order collaborative signals accurately which is required for high-quality recommender systems. However, they neglect the valuable information gained through negative feedback in two aspects: (1) different users might hold opposite feedback on the same item, which hampers optimal information propagation in GNNs, and (2) even when an item vastly deviates from users' preferences, they might still choose it and provide a negative rating. In this paper, we propose a negative feedback-aware recommender model (NFARec) that maximizes the leverage of negative feedback. To transfer information to multi-hop neighbors along an optimal path effectively, NFARec adopts a feedback-aware correlation that guides hypergraph convolutions (HGCs) to learn users' structural representations. Moreover, NFARec incorporates an auxiliary task - predicting the feedback sentiment polarity (i.e., positive or negative) of the next interaction - based on the Transformer Hawkes Process. The task is beneficial for understanding users by learning the sentiment expressed in their previous sequential feedback patterns and predicting future interactions. Extensive experiments demonstrate that NFARec outperforms competitive baselines. Our source code and data are released at https://github.com/WangXFng/NFARec.

cs.IR↗

arXiv2024

Enhanced Coherence-Aware Network with Hierarchical Disentanglement for Aspect-Category Sentiment Analysis

Aspect-category-based sentiment analysis (ACSA), which aims to identify aspect categories and predict their sentiments has been intensively studied due to its wide range of NLP applications. Most approaches mainly utilize intrasentential features. However, a review often includes multiple different aspect categories, and some of them do not explicitly appear in the review. Even in a sentence, there is more than one aspect category with its sentiments, and they are entangled intra-sentence, which makes the model fail to discriminately preserve all sentiment characteristics. In this paper, we propose an enhanced coherence-aware network with hierarchical disentanglement (ECAN) for ACSA tasks. Specifically, we explore coherence modeling to capture the contexts across the whole review and to help the implicit aspect and sentiment identification. To address the issue of multiple aspect categories and sentiment entanglement, we propose a hierarchical disentanglement module to extract distinct categories and sentiment features. Extensive experimental and visualization results show that our ECAN effectively decouples multiple categories and sentiments entangled in the coherence representations and achieves state-of-the-art (SOTA) performance. Our codes and data are available online: \url{https://github.com/cuijin-23/ECAN}.

cs.CL↗

arXiv2024

High-Entropy Enhanced Negative Thermal Expansion Perfomance in Antiperovkites

The negative thermal expansion (NTE) materials, which can act as thermal-expansion compensators to counteract the positive thermal expansion, have great applications merit in precision engineering. However, the exploration of NTE behavior with a wide temperature range has reached its upper ceiling through traditional doping strategies due to composition limitations. The unique sluggish characteristic in phase transition and extended optimization space in recent high entropy systems has great potential to broaden the temperature range in electronic transitions-induced NTE materials. Mn-based anti-perovskites offer an ideal platform for the exploration of high entropy NTE material due to their abundant element selection and controllable NTE performance. In this paper, the high entropy strategy is first introduced to broaden the NTE temperature range by relaxing the abrupt phase transition in Mn-based anti-perovskite nitride. We propose an empirical screening method to synthesize the high-entropy anti-perovskite (HEAP). it is found that magnetic phase separation from anti-ferromagnetic CII to paramagnetic CI surviving in an ultra-wide temperature range of 5K<=T<=350K (Delta_T=345K), revealing a unique sluggish characteristic. Consequently, a remarkable NTE behavior (up to Delta_T=235K, 5K<=T<=240K) with a coefficient of thermal expansion of -4.7x10-6/K, has been obtained in HEAP. It is worth noting that the temperature range is two/three times wider than that of low-entropy systems. The sluggish characteristic has been further experimentally proved to come from disturbed phase transition dynamics due to distortion in atomic spacing and chemical environmental fluctuation observed by the spherical aberration-corrected electron microscope. Our demonstration provides a unique paradigm for broadening the temperature range of NTE materials induced by phase transition through entropy engineering.

cond-mat.mtrl-sci↗

arXiv2021

High-order linearly implicit structure-preserving exponential integrators for the nonlinear Schrödinger equation

A novel class of high-order linearly implicit energy-preserving integrating factor Runge-Kutta methods are proposed for the nonlinear Schrödinger equation. Based on the idea of the scalar auxiliary variable approach, the original equation is first reformulated into an equivalent form which satisfies a quadratic energy. The spatial derivatives of the system are then approximated with the standard Fourier pseudo-spectral method. Subsequently, we apply the extrapolation technique/prediction-correction strategy to the nonlinear terms of the semi-discretized system and a linearized energy-conserving system is obtained. A fully discrete scheme is gained by further using the integrating factor Runge-Kutta method to the resulting system. We show that, under certain circumstances for the coefficients of a Runge-Kutta method, the proposed scheme can produce numerical solutions along which the modified energy is precisely conserved, as is the case with the analytical solution and is extremely efficient in the sense that only linear equations with constant coefficients need to be solved at every time step. Numerical results are addressed to demonstrate the remarkable superiority of the proposed schemes in comparison with other existing structure-preserving schemes.

math.NA↗

arXiv2021

Arbitrary high-order linear structure-preserving schemes for the regularized long-wave equation

In this paper, a class of arbitrarily high-order linear momentum-preserving and energy-preserving schemes are proposed, respectively, for solving the regularized long-wave equation. For the momentum-preserving scheme, the key idea is based on the extrapolation/prediction-correction technique and the symplectic Runge-Kutta method in time, together with the standard Fourier pseudo-spectral method in space. We show that the scheme is linear, high-order, unconditionally stable and preserves the discrete momentum of the system. For the energy-preserving scheme, it is mainly based on the energy quadratization approach and the analogous linearized strategy used in the construction of the linear momentum-preserving scheme. The proposed scheme is linear, high-order and can preserve a discrete quadratic energy exactly. Numerical results are addressed to demonstrate the accuracy and efficiency of the proposed scheme.

math.NA↗

arXiv2020

Mass- and energy-preserving exponential Runge-Kutta methods for the nonlinear Schrödinger equation

In this paper, a family of arbitrarily high-order structure-preserving exponential Runge-Kutta methods are developed for the nonlinear Schrödinger equation by combining the scalar auxiliary variable approach with the exponential Runge-Kutta method. By introducing an auxiliary variable, we first transform the original model into an equivalent system which admits both mass and modified energy conservation laws. Then applying the Lawson method and the symplectic Runge-Kutta method in time, we derive a class of mass- and energy-preserving time-discrete schemes which are arbitrarily high-order in time. Numerical experiments are addressed to demonstrate the accuracy and effectiveness of the newly proposed schemes.

math.NA↗

arXiv2020

Arbitrarily high-order structure-preserving schemes for the Gross-Pitaevskii equation with angular momentum rotation in three dimensions

In this paper, we design a novel class of arbitrarily high-order structure-preserving numerical schemes for the time-dependent Gross-Pitaevskii equation with angular momentum rotation in three dimensions. Based on the idea of the scalar auxiliary variable approach which is proposed in the recent papers [J. Comput. Phys., 416 (2018) 353-407 and SIAM Rev., 61(2019) 474-506] for developing energy stable schemes for gradient flow systems, we firstly reformulate the Gross-Pitaevskii equation into an equivalent system with a modified energy conservation law. The reformulated system is then discretized by the Gauss collocation method in time and the standard Fourier pseudo-spectral method in space, respectively. We show that the proposed schemes can preserve the discrete mass and modified energy exactly. Numerical results are addressed to verify the efficiency and high-order accuracy of the proposed schemes.

math.NA↗

arXiv2019

A novel linearized and momentum-preserving Fourier pseudo-spectral scheme for the Rosenau-Korteweg de Vries equation

In this paper, we design a novel linearized and momentum-preserving Fourier pseudo-spectral scheme to solve the Rosenau-Korteweg de Vries equation. With the aid of a new semi-norm equivalence between the Fourier pseudo-spectral method and the finite difference method, a prior bound of the numerical solution in discrete $L^{\infty}$-norm is obtained from the discrete momentum conservation law. Subsequently, based on the energy method and the bound of the numerical solution, we show that, without any restriction on the mesh ratio, the scheme is convergent with order $O(N^{-s}+τ^2)$ in discrete $L^\infty$-norm, where $N$ is the number of collocation points used in the spectral method and $τ$ is the time step. Numerical results are addressed to confirm our theoretical analysis.

math.NA↗

arXiv2018

Dynamics of spin-orbit-coupled cold atomic gases in a Floquet lattice with an impurity

In this study, we have studied the quantum tunneling of a single spin-orbit-coupled atom held in a periodically modulated optical lattice with an impurity. At the pseudocollapse points of quasienergy bands, where the dynamical localization takes place globally, two types of local second-order tunneling processes appear beyond expectation between the two nearest-neighbor sites of the impurity with the spin unchanged and with impurity site population negligible all the time, when the impurity potential is far off-resonant with the driving field. Though tunneling behaviors of the two types seem to be the same, they are believed to involve two distinct mechanisms: one is related to spin-independent process, while the other is to spin-dependent tunneling process. The two types of second-order processes can be identified by means of resonant tunneling with or without spin-flipping by tuning the impurity potential to be in resonance with the driving field. In the Floquet picture, the second-order processes are manifested as subtle and fine avoided crossings of quasienergy spectrums near the pseudocollapse region. These results are confirmed analytically on the basis of effective three-site model and multiple-time-scale asymptotic perturbative method, and may be exploited for engineering the spin-dependent quantum transport in realistic experiments.

quant-ph↗