Searcharxiv⌕ Search

arXiv subjects

Jiajun Wang

Publications and source records attributed to Jiajun Wang.

At least 37 records · Page 2Linked to original sources
arXiv2025

AI vs. Human Paintings? Deciphering Public Interactions and Perceptions towards AI-Generated Paintings on TikTok

With the development of generative AI technology, a vast array of AI-generated paintings (AIGP) have gone viral on social media like TikTok. However, some negative news about AIGP has also emerged. For example, in 2022, numerous painters worldwide organized a large-scale anti-AI movement because of the infringement in generative AI model training. This event reflected a social issue that, with the development and application of generative AI, public feedback and feelings towards it may have been overlooked. Therefore, to investigate public interactions and perceptions towards AIGP on social media, we analyzed user engagement level and comment sentiment scores of AIGP using human painting videos as a baseline. In analyzing user engagement, we also considered the possible moderating effect of the aesthetic quality of Paintings. Utilizing topic modeling, we identified seven reasons, including hyperrealistic quality, ambivalent reactions, perceived theft of art, etc., leading to negative public perceptions of AIGP. Our work may provide instructive suggestions for future generative AI technology development and avoid potential crises in human-AI collaboration.

cs.HC↗
arXiv2025

Scattering theory of the nonlinear wave equations on lattices

In this paper, I will summarize the uniform decay estimates of the discrete wave equations (DW) established by the oscillatory integral theory in [Sch98, BCH23, BCH24], and combine the abstract framework of the scattering theory of the dispersive equations established in [Str81] to finally establish the scattering theory of the discrete nonlinear wave equations (DNLW), including the existence of the wave operators and the asymptotic completeness. In addition, I will establish the scattering theory again by the Strichartz estimate.

math.AP↗
arXiv2025

Meron Spin Textures in Momentum Space Spawning from Bound States in the Continuum

Topological spin textures, such as merons and skyrmions, have shown significance in both fundamental science and practical applications across diverse physical systems. The optical skyrmionic textures in real space have been extensively explored, but which in momentum space are still rarely studied. Here, we report the experimental generation of momentum-space meron spin textures via bound states in the continuum (BICs) in photonic crystal slabs. We show that under circularly polarized illumination, the momentum-space vortex topology of BICs can transform light with meron spin textures in momentum space. These merons exhibit polarity-switchable configurations controlled by incident light polarization. We theoretically and experimentally verify the generation of momentum-space merons and demonstrate their operational flexibility across a broad spectral range. Our results establish a connection between different momentum-space topologies and provide a robust and compact platform for generating topological spin textures.

physics.optics↗
arXiv2025

Shortest filling geodesics on hyperbolic surfaces

In this paper, we obtain the minimal length of a filling (multi-)geodesic on a genus $g$ hyperbolic surface in the moduli space of hyperbolic surfaces and show that it is realized by the geodesic whose complement is a right-angled regular $(8g-4)$-gon. A single geodesic realizing this minimum is provided.

math.GT↗
arXiv2025

A Day in Their Shoes: Using LLM-Based Perspective-Taking Interactive Fiction to Reduce Stigma Toward Dirty Work

Occupations referred to as "dirty work" often face entrenched social stigma, which adversely affects the mental health of workers in these fields and impedes occupational equity. In this study, we propose a novel Interactive Fiction (IF) framework powered by Large Language Models (LLMs) to encourage perspective-taking and reduce biases against these stigmatized yet essential roles. Through an experiment with participants (n = 100) across four such occupations, we observed a significant increase in participants' understanding of these occupations, as well as a high level of empathy and a strong sense of connection to individuals in these roles. Additionally, qualitative interviews with participants (n = 15) revealed that the LLM-based perspective-taking IF enhanced immersion, deepened emotional resonance and empathy toward "dirty work," and allowed participants to experience a sense of professional fulfillment in these occupations. However, participants also highlighted ongoing challenges, such as limited contextual details generated by the LLM and the unintentional reinforcement of existing stereotypes. Overall, our findings underscore that an LLM-based perspective-taking IF framework offers a promising and scalable strategy for mitigating stigma and promoting social equity in marginalized professions.

cs.HC↗
arXiv2025

Continuum limit of 3D fractional nonlinear Schrödinger equation

In this paper, we investigate the continuum limit theory of the fractional nonlinear Schrödinger equation in dimension 3. We show that the solution of discrete fractional nonlinear Schrödinger equation on hZ^3 will converge strongly in L^2 to the solution of fractional nonlinear Schrödinger equation on R^3, when h->0. The key is proving the uniform-in-h Strichartz estimate for discrete fractional nonlinear Schrödinger equation, by using the uniform estimate of oscillatory integral and Newton polyhedron techniques.

math.AP↗
arXiv2024

Multi-modal Evidential Fusion Network for Trustworthy PET/CT Tumor Segmentation

Accurate tumor segmentation in PET/CT images is crucial for computer-aided cancer diagnosis and treatment. The primary challenge lies in effectively integrating the complementary information from PET and CT images. In clinical settings, the quality of PET and CT images often varies significantly, leading to uncertainty in the modality information extracted by networks. To address this challenge, we propose a novel Multi-modal Evidential Fusion Network (MEFN), which consists of two core stages: Cross-Modal Feature Learning (CFL) and Multi-modal Trustworthy Fusion (MTF). The CFL stage aligns features across different modalities and learns more robust feature representations, thereby alleviating the negative effects of domain gap. The MTF stage utilizes mutual attention mechanisms and an uncertainty calibrator to fuse modality features based on modality uncertainty and then fuse the segmentation results under the guidance of Dempster-Shafer Theory. Besides, a new uncertainty perceptual loss is introduced to force the model focusing on uncertain features and hence improve its ability to extract trusted modality information. Extensive comparative experiments are conducted on two publicly available PET/CT datasets to evaluate the performance of our proposed method whose results demonstrate that our MEFN significantly outperforms state-of-the-art methods with improvements of 3.10% and 3.23% in DSC scores on the AutoPET dataset and the Hecktor dataset, respectively. More importantly, our model can provide radiologists with credible uncertainty of the segmentation results for their decision in accepting or rejecting the automatic segmentation results, which is particularly important for clinical applications. Our code will be available at https://github.com/QPaws/MEFN.

eess.IV↗
arXiv2024

Wireless Electronic-free Mechanical Metamaterial Implants

Despite significant advancements in wireless smart implants over the last two decades, current implantable devices still operate passively and require additional electronic modules for wireless transmission of the stored biological data. To address these challenges, we propose an innovative wireless force sensing paradigm for implantable systems through the integration of mechanical metamaterials and nano energy harvesting technologies. We demonstrate composite mechanical metamaterial implants capable of serving as all-in-one wireless force sensing units, incorporating functions for power generation, sensing and transmission with ultra-low power requirements. In this alternative communication approach, the electrical signals harvested by the implants from mechanical stimuli are utilized directly for the wireless transmission of the sensed data. We conduct experimental and theoretical studies to demonstrate the wireless detection of the generated strain-induced polarization electric field using electrodes. The feasibility of the proposed wireless force sensing approach is evaluated through a proof-of-concept orthopedic implant in the form of a total knee replacement. The findings indicate that the created wireless, electronic-free metamaterial implants with a power output as low as 0.1 picowatts enable direct, self-powered wireless communication during force sensing across air, simulated body fluid and animal tissue. We validate the functionality of the proposed implants through a series of experiments conducted on an ex vivo human cadaver knee specimen. Furthermore, the effect of electrode size and placement on the strength of the received signals is examined. Finally, we highlight the potential of our approach to create a diverse array of mechanically-tunable wireless force sensing implants without relying on any external power sources.

physics.med-ph↗
arXiv2024

Topological Singularities in Metasurface Scattering Matrices: From Nodal Lines to Exceptional Lines

Topological properties of photonic structures described by Hamiltonian matrices have been extensively studied in recent years. Photonic systems are often open systems, and their coupling with the environment is characterized by scattering matrices, which can exhibit topological features as well. In this work, we uncover that topological singularities can be manifested in the scattering matrices of two-dimensional periodic photonic systems with open boundaries in the third dimension, introducing a new topological approach to describe scattering. We elaborate the importance of symmetry and demonstrate that mirror symmetry gives rise to the formation of diabolic points and nodal lines in the three-dimensional frequency-momentum space, which transform into exceptional points and lines in the presence of material loss. These topological features in the eigenvalue structure of the scattering matrix manifest as vortex lines in the cross-polarization scattering phase, providing a direct link between the eigen-problem and observable scattering phenomena in the frequency-momentum space. We demonstrate these phenomena numerically and experimentally using a reflective non-local metasurface. These findings extend the concept of topological singularities to scattering matrices and pave the way for novel photonic devices and wavefront engineering techniques.

physics.optics↗
arXiv2024

Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation

Controllable text-to-image (T2I) diffusion models have shown impressive performance in generating high-quality visual content through the incorporation of various conditions. Current methods, however, exhibit limited performance when guided by skeleton human poses, especially in complex pose conditions such as side or rear perspectives of human figures. To address this issue, we present Stable-Pose, a novel adapter model that introduces a coarse-to-fine attention masking strategy into a vision Transformer (ViT) to gain accurate pose guidance for T2I models. Stable-Pose is designed to adeptly handle pose conditions within pre-trained Stable Diffusion, providing a refined and efficient way of aligning pose representation during image synthesis. We leverage the query-key self-attention mechanism of ViTs to explore the interconnections among different anatomical parts in human pose skeletons. Masked pose images are used to smoothly refine the attention maps based on target pose-related features in a hierarchical manner, transitioning from coarse to fine levels. Additionally, our loss function is formulated to allocate increased emphasis to the pose region, thereby augmenting the model's precision in capturing intricate pose details. We assessed the performance of Stable-Pose across five public datasets under a wide range of indoor and outdoor human pose scenarios. Stable-Pose achieved an AP score of 57.1 in the LAION-Human dataset, marking around 13% improvement over the established technique ControlNet. The project link and code is available at https://github.com/ai-med/StablePose.

cs.CV↗
arXiv2024

The well-posedness and scattering theory of nonlinear Schrödinger equations on lattice graphs

In this paper, we introduce a novel first-order derivative for functions on a lattice graph, which extends the discrete Laplacian and generalizes the theory of discrete PDEs on lattices. First, we establish the well-posedness of generalized discrete quasilinear Schrödinger equations and give a new proof of the global well-posedness of discrete semilinear Schrödinger equations. Then we provide explicit expressions of higher-order derivatives of the solution map and prove the analytic dependence between the solution and the initial data. At the end, we show the existence of the wave operator and prove the asymptotic completeness of the solutions with the small data.

math.AP↗
arXiv2024

Sportoonizer: Augmenting Sports Highlights' Narration and Visual Impact via Automatic Manga B-Roll Generation

Sports highlights are becoming increasingly popular on video-sharing platforms. Yet, crafting sport highlight videos is challenging, which requires producing engaging narratives from different angles, and conforming to different platform affordances with constantly changing audiences. Many content creators therefore create derivative work of the original sports video through manga styles to enhance its expressiveness. But manually creating and inserting tailored manga-style content can still be time-consuming. We introduce Sportoonizer, a system embedding the pipeline for automatic generation of manga-style animations for highlights in sports videos and insertion into original videos. It seamlessly merges dynamic manga sequences with live-action footage, enriching the visual tapestry and deepening narrative scope. By leveraging genAIs, Sportoonizer crafts compelling storylines encapsulating the intensity of sports moments and athletes' personal journeys. Our evaluation study demonstrates that integrating manga B-rolls significantly enhances viewer engagement, visual interest, and emotional connection towards athletes' stories in the viewing experience.

cs.HC↗
arXiv2024

KoroT-3E: A Personalized Musical Mnemonics Tool for Enhancing Memory Retention of Complex Computer Science Concepts

As the demand for computer science (CS) skills grows, mastering foundational concepts is crucial yet challenging for novice learners. To address this challenge, we present KoroT-3E, an AI-based system that creates personalized musical mnemonics to enhance both memory retention and understanding of concepts in CS. KoroT-3E enables users to transform complex concepts into memorable lyrics and compose melodies that suit their musical preferences. We conducted semi-structured interviews (n=12) to investigate why novice learners find it challenging to memorize and understand CS concepts. The findings, combined with constructivist learning theory, established our initial design, which was then refined following consultations with CS education experts. An empirical experiment(n=36) showed that those using KoroT-3E (n=18) significantly outperformed the control group (n=18), with improved memory efficiency, increased motivation, and a positive learning experience. These findings demonstrate the effectiveness of integrating multimodal generative AI into CS education to create personalized and interactive learning experiences.

cs.HC↗
arXiv2024

Inherent spin-orbit locking in topological bound state in the continuum lasing

Bound states in the continuum (BICs) are exotic optical topological singularities that defy the typical radiation within the continuum of radiative modes and carry topological polarization vortices in momentum space. Enabling ultrahigh quality factors, BICs have been applied in realizing lasing and Bose-Einstein condensation via micro-/nano- photonic structures, and their momentum-space vortex topologies have been exploited in passive systems, revealing novel spin-orbit photonic effects. However, as representative topological properties, the spin-orbit-related phenemona of BICs in active systems have not yet been explored. Here, we demonstrate the inherent spin-orbit locking in topological BIC lasing. Utilizing photonic crystal (PhC) slabs with square (C4v) and triangular (C6v) lattices, we achieve distinct spin-orbit locking combinations in topological BIC lasing of +1 and -2 topological charges. These BIC lasing profiles manifest as vortex and high-order anti-vortex polarization configurations, directly tied to the topological properties of BICs. Our experimental results directly reveal the spin-orbit locking phenomena through momentum-space spin-dependent self-interference patterns and real-space spin separations of the lasing emissions. This study not only highlights the inherent spin-orbit-locking behaviours of topological BIC lasing but also opens new possibilities for dynamically switchable orbital angular momentum (OAM) lasing by controlling photonic spin, presenting significant potential for advancements in topological photonic source applications.

physics.optics↗
arXiv2024

Spin-Orbit-Locking Chiral Bound States in the Continuum

Bound states in the continuum (BICs), which are confined optical modes exhibiting infinite quality factors and carrying topological polarization configurations in momentum space, have recently sparked significant interest across both fundamental and applied physics.} Here we show that breaking time-reversal symmetry by external magnetic field enables a new form of chiral BICs with spin-orbit locking. Applying a magnetic field to a magneto-optical photonic crystal slab lifts doubly degenerate BICs into a pair of chiral BICs carrying opposite pseudo-spins and orbital angular momenta. Multipole analysis verifies the non-zero angular momenta and reveals the spin-orbital-locking behaviors. In momentum space, we observe ultrahigh quality factors and near-circular polarization surrounding chiral BICs, enabling potential applications in spin-selective nanophotonics. Compared to conventional BICs, the magnetically-induced chiral BICs revealed here exhibit distinct properties and origins, significantly advancing the topological photonics of BICs by incorporating broken time-reversal symmetry.

physics.optics↗
arXiv2024

The well-posedness of generalized nonlinear wave equations on the lattice graph

In this paper, we introduce a novel first-order derivative for functions on a lattice graph, and establish its weak (1, 1) estimate as well as strong (p, p) estimate for p > 1 in weighted spaces. This derivative is designed to reconstruct the discrete Laplacian, enabling an extension of the theory of nonlinear wave equations, including quasilinear wave equations, to lattice graphs. We prove the local well-posedness of generalized quasilinear wave equations and the long-time well-posedness of these equations for small initial data. Furthermore, we prove the global well-posedness of defocusing semilinear wave equations for large initial data.

math.AP↗
arXiv2023

Realistic Volume Rendering with Environment-Synced Illumination in Mixed Reality

Interactive volume visualization using a mixed reality (MR) system helps provide users with an intuitive spatial perception of volumetric data. Due to sophisticated requirements of user interaction and vision when using MR head-mounted display (HMD) devices, the conflict between the realisticness and efficiency of direct volume rendering (DVR) is yet to be resolved. In this paper, a new MR visualization framework that supports interactive realistic DVR is proposed. An efficient illumination estimation method is used to identify the high dynamic range (HDR) environment illumination captured using a panorama camera. To improve the visual quality of Monte Carlo-based DVR, a new spatio-temporal denoising algorithm is designed. Based on a reprojection strategy, it makes full use of temporal coherence between adjacent frames and spatial coherence between the two screens of an HMD to optimize MR rendering quality. Several MR development modules are also developed for related devices to efficiently and stably display the DVR results in an MR HMD. Experimental results demonstrate that our framework can better support immersive and intuitive user perception during MR viewing than existing MR solutions.

cs.GR↗