arXiv subjects

Jie Wang

Publications and source records attributed to Jie Wang.

At least 253 records · Page 14Linked to original sources

arXiv2025

Surgical-LVLM: Learning to Adapt Large Vision-Language Model for Grounded Visual Question Answering in Robotic Surgery

Recent advancements in Surgical Visual Question Answering (Surgical-VQA) and related region grounding have shown great promise for robotic and medical applications, addressing the critical need for automated methods in personalized surgical mentorship. However, existing models primarily provide simple structured answers and struggle with complex scenarios due to their limited capability in recognizing long-range dependencies and aligning multimodal information. In this paper, we introduce Surgical-LVLM, a novel personalized large vision-language model tailored for complex surgical scenarios. Leveraging the pre-trained large vision-language model and specialized Visual Perception LoRA (VP-LoRA) blocks, our model excels in understanding complex visual-language tasks within surgical contexts. In addressing the visual grounding task, we propose the Token-Interaction (TIT) module, which strengthens the interaction between the grounding module and the language responses of the Large Visual Language Model (LVLM) after projecting them into the latent space. We demonstrate the effectiveness of Surgical-LVLM on several benchmarks, including EndoVis-17-VQLA, EndoVis-18-VQLA, and a newly introduced EndoVis Conversations dataset, which sets new performance standards. Our work contributes to advancing the field of automated surgical mentorship by providing a context-aware solution.

cs.CV↗

arXiv2025

Privacy Law Enforcement Under Centralized Governance: A Qualitative Analysis of Four Years' Special Privacy Rectification Campaigns

In recent years, major privacy laws like the GDPR have brought about positive changes. However, challenges remain in enforcing the laws, particularly due to under-resourced regulators facing a large number of potential privacy-violating software applications (apps) and the high costs of investigating them. Since 2019, China has launched a series of privacy enforcement campaigns known as Special Privacy Rectification Campaigns (SPRCs) to address widespread privacy violations in its mobile application (app) ecosystem. Unlike the enforcement of the GDPR, SPRCs are characterized by large-scale privacy reviews and strict sanctions, under the strong control of central authorities. In SPRCs, central government authorities issue administrative orders to mobilize various resources for market-wide privacy reviews of mobile apps. They enforce strict sanctions by requiring privacy-violating apps to rectify issues within a short timeframe or face removal from app stores. While there are a few reports on SPRCs, the effectiveness and potential problems of this campaign-style privacy enforcement approach remain unclear to the community. In this study, we conducted 18 semi-structured interviews with app-related engineers involved in SPRCs to better understand the campaign-style privacy enforcement. Based on the interviews, we reported our findings on a variety of aspects of SPRCs, such as the processes that app engineers regularly follow to achieve privacy compliance in SPRCs, the challenges they encounter, the solutions they adopt to address these challenges, and the impacts of SPRCs, etc. We found that app engineers face a series of challenges in achieving privacy compliance in their apps...

cs.HC↗

arXiv2025

Formation of the dark-matter deficient S0 galaxy NGC 4111 under the tidal interactions

We present the high-sensitivity and large-scale atomic hydrogen (HI) observations towards lenticular (S0) galaxy NGC 4111 using the Five-hundred-meter Aperture Spherical Radio Telescope (FAST). The column density map shows that NGC4111 and seven other different types of galaxies share a huge HI gas complex. The data also suggest that NGC 4111 is interacting with seven galaxies. Moreover, we identified a rotating gas disk associated with NGC 4111 from the HI complex. Still, the HI disk rotation direction has deviated from its stellar disk about 34.2$^{\circ}$, indicating that the NGC 4111 galaxy is undergoing a transition from a spiral galaxy to an S0 galaxy by the tidal interactions. The obtained dark matter-to-stellar mass ratio of NGC4111 is 3.1$\pm$0.7, which is lower than the average value of the Local Universe, implying that the interactions may strip its dark matter. Our results suggest that in a galaxy group environment, tidal interactions have a significant effect on galaxy features.

astro-ph.GA↗

arXiv2025

Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming

Leveraging machine learning (ML) to predict an initial solution for mixed-integer linear programming (MILP) has gained considerable popularity in recent years. These methods predict a solution and fix a subset of variables to reduce the problem dimension. Then, they solve the reduced problem to obtain the final solutions. However, directly fixing variable values can lead to low-quality solutions or even infeasible reduced problems if the predicted solution is not accurate enough. To address this challenge, we propose an Alternating prediction-correction neural solving framework (Apollo-MILP) that can identify and select accurate and reliable predicted values to fix. In each iteration, Apollo-MILP conducts a prediction step for the unfixed variables, followed by a correction step to obtain an improved solution (called reference solution) through a trust-region search. By incorporating the predicted and reference solutions, we introduce a novel Uncertainty-based Error upper BOund (UEBO) to evaluate the uncertainty of the predicted values and fix those with high confidence. A notable feature of Apollo-MILP is the superior ability for problem reduction while preserving optimality, leading to high-quality final solutions. Experiments on commonly used benchmarks demonstrate that our proposed Apollo-MILP significantly outperforms other ML-based approaches in terms of solution quality, achieving over a 50% reduction in the solution gap.

cs.LG↗

arXiv2025

Air-stable lithiation engineering of $\mathrm{MoS}_{2}$ for direct-bandgap multilayers

Due to its sizable direct bandgap and strong light-matter interactions, the preparation of monolayer $\mathrm{MoS}_{2}$ has attracted significant attention and intensive research efforts. However, multilayer $\mathrm{MoS}_{2}$ is largely overlooked because of its optically inactive indirect bandgap caused by interlayer coupling. It is highly desirable to modulate and decrease the interlayer coupling so that each layer in multilayer $\mathrm{MoS}_{2}$ can exhibit a monolayer-like direct-gap behavior. Here, we demonstrate the nanoprobe fabrication of $\mathrm{Li}_{x}\mathrm{MoS}_{2}$-based multilayers exhibiting a direct bandgap and strong photoluminescence emission from tightly bound excitons and trions. The fabrication is facilitated by our newly developed Li-ion platform, featuring tip-induced Li intercalation, air stability and rewritability. Raman characterizations reveal that controlled Li intercalation effectively transforms multilayer $\mathrm{MoS}_{2}$ into the stack of multiple monolayers, leading to a 26-fold enhancement of photoluminescence, compared to a monolayer. This intercalation result is different from existing observations of transforming $\mathrm{MoS}_{2}$ multilayers into metallic phases.

cond-mat.mes-hall↗

arXiv2025

Accurate and Scalable Graph Neural Networks via Message Invariance

Message passing-based graph neural networks (GNNs) have achieved great success in many real-world applications. For a sampled mini-batch of target nodes, the message passing process is divided into two parts: message passing between nodes within the batch (MP-IB) and message passing from nodes outside the batch to those within it (MP-OB). However, MP-OB recursively relies on higher-order out-of-batch neighbors, leading to an exponentially growing computational cost with respect to the number of layers. Due to the neighbor explosion, the whole message passing stores most nodes and edges on the GPU such that many GNNs are infeasible to large-scale graphs. To address this challenge, we propose an accurate and fast mini-batch approach for large graph transductive learning, namely topological compensation (TOP), which obtains the outputs of the whole message passing solely through MP-IB, without the costly MP-OB. The major pillar of TOP is a novel concept of message invariance, which defines message-invariant transformations to convert costly MP-OB into fast MP-IB. This ensures that the modified MP-IB has the same output as the whole message passing. Experiments demonstrate that TOP is significantly faster than existing mini-batch methods by order of magnitude on vast graphs (millions of nodes and billions of edges) with limited accuracy degradation.

cs.LG↗

arXiv2025

FEASTS Combined with Interferometry (IV): Mapping HI Emission to a limit of $N_{\text{HI}}=10^{17.7} \text{cm}^{-2}$ in Seven Edge-on Galaxies

We present a statistical study of the neutral atomic hydrogen (HI) gas extending into the circumgalactic medium perpendicular to the disk for 7 edge-on galaxies with inclinations above $85^{\circ}$ from the FEASTS program with a $3σ$ ($20\,\text{km}\,\text{s}^{-1}$) column density ($N_{\text{HI}}$) depth of $5\times10^{17} \text{cm}^{-2}$. We develop two photometric methods to separate the extraplanar HI from the disk component, based on existing interferometric data and parametric modeling of the disk flux distribution respectively. With both methods, the FEASTS data exhibit clear extended wings beyond the disk along the minor axis. The extraplanar HI accounts for 5% to 20% of the total HI mass and extends to $20\text{-}50$ kpc at $N_{\text{HI}}=10^{18} \text{cm}^{-2}$. We find a tight positive correlation between vertical extensions of the extraplanar HI and total HI mass $M_\text{HI}$. The iso-density shape of HI at $N_{\text{HI}}=10^{18} \text{cm}^{-2}$ has an average axis ratio of $0.56\pm0.11$. The off-disk $N_{\text{HI}}$ profiles of these edge-on galaxies well represent the lower envelop of previous Lyman-$α$ absorption measurements at low-redshift. Our results suggest that at $N_{\text{HI}}=5\times10^{17} \text{cm}^{-2}$, the HI extends considerably further than the known thin and thick disks in the vertical direction, but still remains much flattener than a spherical distribution, consistent with theoretical expectations that outflow, circulation, and accretion should have different impacts in these two directions. We show the tension of our results with Illustris and TNG predictions, highlighting the constraining power of our results for future simulations.

astro-ph.GA↗

arXiv2025

Higher Landau-Level Analogs and Signatures of Non-Abelian States in Twisted Bilayer MoTe$_2$

Recent experimental discovery of fractional Chern insulators at zero magnetic field in moiré superlattices has sparked intense interests in bringing Landau level physics to flat Chern bands. In twisted MoTe$_2$ bilayers (tMoTe$_2$), recent theoretical and experimental studies have found three consecutive flat Chern bands at twist angle $\sim 2^\circ$. In this work, we investigate whether higher Landau level physics can be found in these consecutive Chern bands. At twist angles $2.00^\circ$ and $1.89^\circ$, we identify four consecutive $C = 1$ bands for the $K$ valley in tMoTe$_2$. By constructing Wannier functions directly from density functional theory (DFT) calculations, a six-orbital model is developed to describe the consecutive Chern bands, with the orbitals forming a honeycomb lattice. Exact diagonalization on top of Hartree-Fock calculations are carried out with the Wannier functions. Especially, when the second moiré miniband is half-filled, signatures of non-Abelian states are found. Our Wannier-based approach in modelling moiré superlattices is faithful to DFT wave functions and can serve as benchmarks for continuum models. The possibility of realizing non-Abelian anyons at zero magnetic field also opens up a new pathway for fault-tolerant quantum information processing.

cond-mat.str-el↗

arXiv2025

The FAST HI 21-cm absorption blind survey. II. -- Statistic Exploration for Associated and Intervening systems

We present an extragalactic HI 21-cm absorption lines catalog from a blind search at z $\leqslant$ 0.35, using drift-scan data collected in 1325.6 hours by the ongoing Commensal Radio Astronomy FasT Survey (CRAFTS) and FAST All Sky HI Survey (FASHI), which spans a sky area of 6072.0 deg$^{2}$ and covers 84533 radio sources with a flux density greater than 12 mJy. 14 previously identified HI absorbers and 20 newly discovered HI absorbers were detected, comprising 15 associated systems, 10 intervening systems, and 9 systems with undetermined classifications. Through spectral stacking, the mean peak optical path, mean velocity-integrated optical path, mean FWHM and mean HI column density are measured to be 0.47 and 0.30; 27.19 and 4.36 km s$^{-1}$; 42.61 and 9.33 km s$^{-1}$; 0.49 and 0.08 T$_{s} \times$ 10$^{20}$cm$^{-2}$K$^{-1}$, for the associated and intervening samples, respectively. Statistical analysis also reveals that associated systems tend to be hosted by red ($g-r>$0.7) galaxies at lower redshifts, whereas galaxies hosting intervening HI absorption are typically found at higher redshifts and are of a bluer ($g-r\leqslant$0.7) type. A noticeable difference is observed in the positions of foregrounds, backgrounds of intervening systems, and high-redshift and low-redshift associated systems on the WISE color-color diagram. All identified foreground sources in our sample have W1-W2 magnitudes below 0.8, suggesting no Active Galactic Nuclei (AGN). In contrast, backgrounds of intervening systems tend to have W1-W2 magnitudes above 0.8, indicating AGN presence. For associated absorption, most low-redshift ($z\leqslant$0.5) systems show W1-W2 values below 0.8, while higher-redshift associated absorption ($z>$0.5) displays a broader range of W1-W2 values.

astro-ph.GA↗

arXiv2025

New Calculations of the Turbulence-Turbulence Contribution to the Wind Noise Pressure Spectra within Homogeneous Anisotropic Turbulence

The turbulence-turbulence interaction and the turbulence-shear interaction are the sources of intrinsic pressure fluctuation for wind noise generated by atmospheric turbulence. In previous research [Yu et al., J. Acoust. Soc. Am. 129(2), 622-632 (2011)], it was shown that the measured turbulent fields outdoors can be realistically modeled with Kraichnan's mirror flow model [Kraichnan, J. Acoust. Soc. Am. 28(3), 378-390 (1956)]. This paper applies Kraichnan's mirror flow idea to develop theory for calculating the turbulence-turbulence interaction wind noise pressure spectra within homogeneous anisotropic turbulence. New calculations of the turbulence-turbulence contribution to the wind noise pressure spectra by incorporating turbulence anisotropy are performed and compared to the result using the same approach but with isotropic input and the result of the turbulence-turbulence interaction pressure spectrum for homogeneous isotropic turbulence using George et al.'s method [George et al., J. Fluid Mech. 148, 155-191 (1984)]. We also evaluated different contributions to the turbulence-turbulence interaction pressure spectra using our approach with both anisotropic and isotropic inputs. Our results indicate that the turbulence anisotropy has small effect on the turbulence-turbulence interaction pressure in source region, but changes the spectral slope in inertial region to about -5/3. The turbulence-turbulence interaction pressure spectrum incorporating turbulence anisotropy is not sensitive to height. The F33F33 term and the F11F11 term are the most dominant contributions to the anisotropic turbulence pressure spectra in the source region and inertial region, respectively.

physics.flu-dyn↗

arXiv2025

Molecular optomechanically-induced transparency

Molecular cavity optomechanics (COM), characterized by remarkably efficient optomechanical coupling enabled by a highly localized light field and ultra-small effective mode volume, holds significant promise for advancing applications in quantum science and technology. Here, we study optomechanically induced transparency and the associated group delay in a hybrid molecular COM system. We find that even with an extremely low optical quality factor, an obvious transparency window can appear, which is otherwise unattainable in a conventional COM system. Furthermore, by varying the ports of the probe light, the optomechanically induced transparency or absorption can be achieved, along with corresponding slowing or advancing of optical signals. These results indicate that our scheme provides a new method for adjusting the storage and retrieval of optical signals in such a molecular COM device.

physics.optics↗

arXiv2025

A refined lower bound theorem for $d$-polytopes with at most $2d$ vertices

In 1967, Grünbaum conjectured that the function $$ ϕ_k(d+s,d):=\binom{d+1}{k+1}+\binom{d}{k+1}-\binom{d+1-s}{k+1},\; \text{for $2\le s\le d$} $$ provides the minimum number of $k$-faces for a $d$-dimensional polytope (abbreviated as a $d$-polytope) with $d+s$ vertices. In 2021, Xue proved this conjecture for each $k\in[1\ldots d-2]$ and characterised the unique minimisers, each having $d+2$ facets. In this paper, we refine Xue's theorem by considering $d$-polytopes with $d+s$ vertices ($2\le s\le d$) and at least $d+3$ facets. If $s=2$, then there is precisely one minimiser for many values of $k$. For other values of $s$, the number of $k$-faces is at least $ϕ_k(d+s,d)+\binom{d-1}{k}-\binom{d+1-s}{k}$, which is met by precisely two polytopes in many cases, and up to five polytopes for certain values of $s$ and $k$. We also characterise the minimising polytopes.

math.CO↗

arXiv2025

Large Language Model driven Policy Exploration for Recommender Systems

Recent advancements in Recommender Systems (RS) have incorporated Reinforcement Learning (RL), framing the recommendation as a Markov Decision Process (MDP). However, offline RL policies trained on static user data are vulnerable to distribution shift when deployed in dynamic online environments. Additionally, excessive focus on exploiting short-term relevant items can hinder exploration, leading to suboptimal recommendations and negatively impacting long-term user gains. Online RL-based RS also face challenges in production deployment, due to the risks of exposing users to untrained or unstable policies. Large Language Models (LLMs) offer a promising solution to mimic user objectives and preferences for pre-training policies offline to enhance the initial recommendations in online settings. Effectively managing distribution shift and balancing exploration are crucial for improving RL-based RS, especially when leveraging LLM-based pre-training. To address these challenges, we propose an Interaction-Augmented Learned Policy (iALP) that utilizes user preferences distilled from an LLM. Our approach involves prompting the LLM with user states to extract item preferences, learning rewards based on feedback, and updating the RL policy using an actor-critic framework. Furthermore, to deploy iALP in an online scenario, we introduce an adaptive variant, A-iALP, that implements a simple fine-tuning strategy (A-iALP$_{ft}$), and an adaptive approach (A-iALP$_{ap}$) designed to mitigate issues with compromised policies and limited exploration. Experiments across three simulated environments demonstrate that A-iALP introduces substantial performance improvements

cs.IR↗

arXiv2025

Geometrical Responses of Generalized Landau Levels: Structure Factor and the Quantized Hall Viscosity

We present a new geometric characterization of generalized Landau levels (GLLs). The GLLs are a generalization of Landau levels to non-uniform Berry curvature, and are mathematically defined in terms of a holomorphic curve -- an ideal Kähler band -- and its associated unitary Frenet-Serret moving frame. Here, we find that GLLs are harmonic maps from the Brillouin zone to the complex projective space and they are critical points of the Dirichlet energy functional, as well as the static structure factor up to fourth order. We also find that filled GLLs exhibit quantized Hall viscosity, similar to the ordinary Landau levels. These results establish GLLs as a versatile generalization of Landau levels.

cond-mat.mes-hall↗

arXiv2025

Exact Parent Hamiltonians for All Landau Level States in a Half-flux Lattice

Realizing topological flat bands with tailored single-particle Hilbert spaces is a critical step toward exploring many-body phases, such as those featuring anyonic excitations. One prominent example is the Kapit-Mueller model, a variant of the Harper-Hofstadter model that stabilizes lattice analogs of the lowest Landau level states. The Kapit-Mueller model is constructed based on the Poisson summation rule, an exact lattice sum rule for coherent states. In this work, we consider higher Landau-level generalizations of the Poisson summation rule, from which we derive families of parent Hamiltonians on a half-flux lattice which have exact flat bands whose flatband wavefunctions are lattice version of higher Landau level states. Focusing on generic Bravais lattices with only translation and inversion symmetries, we discuss how these symmetries enforced gaplessness and singular points for odd Landau level series, and how to achieve fully gapped parent Hamiltonians by mixing even and odd series. Our model points to a large class of tight-binding models with suitable energetic and quantum geometries that are potentially useful for realizing non-Abelian fractionalized states when interactions are included. The model exhibits fast decay hopping amplitudes, making it potentially realizable with neutral atoms in optical lattices.

cond-mat.mes-hall↗

arXiv2025

Half a Million Binary Stars from the low resolution spectra of LAMOST

Binary stars are prevalent yet challenging to detect. We present a novel approach using convolutional neural networks (CNNs) to identify binary stars from low-resolution spectra obtained by the LAMOST survey. The CNN is trained on a dataset that distinguishes binaries from single main sequence stars based on their positions on the Hertzsprung-Russell diagram. Specifically, the training data labels stars with mass ratios between approximately 0.71 and 0.93 as intermediate mass ratio binaries, while excluding those beyond this range. The network achieves high accuracy with an area under the receiver operating characteristic curve of 0.949 on the test set. Its performance is further validated against known eclipsing binaries (97% detection rate) and binary stars identified by radial velocity variations (92% detection rate). Applying the trained CNN to a sample of one million main sequence stars from LAMOST DR10 and Gaia DR3 yields a catalog of 468,634 binary stars, which are mainly intermediate mass ratio binaries given the training data. This catalog includes 115 binary stars located beyond 10 kpc from the Sun and 128 cross-matched with known exoplanet hosts from the NASA Exoplanet Archive. This new catalog provides a valuable resource for future research on the properties, formation, and evolution of binary systems, particularly for statistically characterizing large populations.

astro-ph.SR↗

arXiv2024

Variable Selection for Kernel Two-Sample Tests

We consider the variable selection problem for two-sample tests, aiming to select the most informative variables to determine whether two collections of samples follow the same distribution. To address this, we propose a novel framework based on the kernel maximum mean discrepancy (MMD). Our approach seeks a subset of variables with a pre-specified size that maximizes the variance-regularized kernel MMD statistic. We focus on three commonly used types of kernels: linear, quadratic, and Gaussian. From a computational perspective, we derive mixed-integer programming formulations and propose exact and approximation algorithms with performance guarantees to solve these formulations. From a statistical viewpoint, we derive the rate of testing power of our framework under appropriate conditions. These results show that the sample size requirements for the three kernels depend crucially on the number of selected variables, rather than the data dimension. Experimental results on synthetic and real datasets demonstrate the superior performance of our method, compared to other variable selection frameworks, particularly in high-dimensional settings.

stat.ML↗

arXiv2024

Exploring Temporal Event Cues for Dense Video Captioning in Cyclic Co-learning

Dense video captioning aims to detect and describe all events in untrimmed videos. This paper presents a dense video captioning network called Multi-Concept Cyclic Learning (MCCL), which aims to: (1) detect multiple concepts at the frame level, using these concepts to enhance video features and provide temporal event cues; and (2) design cyclic co-learning between the generator and the localizer within the captioning network to promote semantic perception and event localization. Specifically, we perform weakly supervised concept detection for each frame, and the detected concept embeddings are integrated into the video features to provide event cues. Additionally, video-level concept contrastive learning is introduced to obtain more discriminative concept embeddings. In the captioning network, we establish a cyclic co-learning strategy where the generator guides the localizer for event localization through semantic matching, while the localizer enhances the generator's event semantic perception through location matching, making semantic perception and event localization mutually beneficial. MCCL achieves state-of-the-art performance on the ActivityNet Captions and YouCook2 datasets. Extensive experiments demonstrate its effectiveness and interpretability.

cs.CV↗