arXiv subjects

Yang Su

Publications and source records attributed to Yang Su.

At least 55 records · Page 3Linked to original sources

arXiv2025

Large-field CO(1-0) observations toward the Galactic historical supernova remnants: shocked molecular clouds toward the Crab Nebula

Using the PMO 13.7m telescope, we present large-field and high-sensitivity CO(1-0) line observations toward the Crab Nebula, in order to better understand the interstellar gas environment of this well-known historical supernova remnant. The CO observations show molecular clouds toward the Crab Nebula at a velocity range from about 0 to 16 km/s. After checking the CO spectra, we find shocked signatures in the clouds extending at a velocity of roughly [5, 11] km/s. These shocked molecular clouds, with an angular distance of about 0.4-0.5 degree toward the Crab Nebula, are located at the shell of a bubble discovered in the GALFA-HI (and HI4PI) images at the same velocity range. The dimension of the bubble is roughly 2.3$\times$2.6 degree and the expansion velocity is about 5 km/s. The kinetic energy referred from the shocked molecular clouds (roughly 3.5$\times$10$^{51}$ erg), together with the HI bubble, support the picture that the Crab Nebula belongs to a typical core-collapse supernova remnant. Nevertheless, due to the large uncertainty in the distance measurement, further observations are needed to verify the physical association between the shocked molecular clouds and the Crab Nebula.

astro-ph.GA↗

arXiv2025

Finesse: An Agile Design Framework for Pairing-based Cryptography via Software/Hardware Co-Design

Pairing-based cryptography (PBC) is crucial in modern cryptographic applications. With the rapid advancement of adversarial research and the growing diversity of application requirements, PBC accelerators need regular updates in algorithms, parameter configurations, and hardware design. However, traditional design methodologies face significant challenges, including prolonged design cycles, difficulties in balancing performance and flexibility, and insufficient support for potential architectural exploration. To address these challenges, we introduce Finesse, an agile design framework based on co-design methodology. Finesse leverages a co-optimization cycle driven by a specialized compiler and a multi-granularity hardware simulator, enabling both optimized performance metrics and effective design space exploration. Furthermore, Finesse adopts a modular design flow to significantly shorten design cycles, while its versatile abstraction ensures flexibility across various curve families and hardware architectures. Finesse offers flexibility, efficiency, and rapid prototyping, comparing with previous frameworks. With compilation times reduced to minutes, Finesse enables faster iteration cycles and streamlined hardware-software co-design. Experiments on popular curves demonstrate its effectiveness, achieving $34\times$ improvement in throughput and $6.2\times$ increase in area efficiency compared to previous flexible frameworks, while outperforming state-of-the-art non-flexible ASIC designs with a $3\times$ gain in throughput and $3.2\times$ improvement in area efficiency.

cs.AR↗

arXiv2025

Observatory Science with eXTP

Scheduled for launch in 2030, the enhanced X-ray Timing and Polarization (eXTP) telescope is a Chinese space-based mission aimed at studying extreme conditions and phenomena in astrophysics. eXTP will feature three main payloads: Spectroscopy Focusing Arrays (SFAs), Polarimetry Focusing Arrays (PFAs), and a Wide-field Camera (W2C). This white paper outlines observatory science, incorporating key scientific advances and instrumental changes since the publication of the previous white paper [1]. We will discuss perspectives of eXTP on the research domains of flare stars, supernova remnants, pulsar wind nebulae, cataclysmic variables, X-ray binaries, ultraluminous X-ray sources, AGN, and pulsar-based positioning and timekeeping.

astro-ph.IM↗

arXiv2025

SDiFL: Stable Diffusion-Driven Framework for Image Forgery Localization

Driven by the new generation of multi-modal large models, such as Stable Diffusion (SD), image manipulation technologies have advanced rapidly, posing significant challenges to image forensics. However, existing image forgery localization methods, which heavily rely on labor-intensive and costly annotated data, are struggling to keep pace with these emerging image manipulation technologies. To address these challenges, we are the first to integrate both image generation and powerful perceptual capabilities of SD into an image forensic framework, enabling more efficient and accurate forgery localization. First, we theoretically show that the multi-modal architecture of SD can be conditioned on forgery-related information, enabling the model to inherently output forgery localization results. Then, building on this foundation, we specifically leverage the multimodal framework of Stable DiffusionV3 (SD3) to enhance forgery localization performance.We leverage the multi-modal processing capabilities of SD3 in the latent space by treating image forgery residuals -- high-frequency signals extracted using specific highpass filters -- as an explicit modality. This modality is fused into the latent space during training to enhance forgery localization performance. Notably, our method fully preserves the latent features extracted by SD3, thereby retaining the rich semantic information of the input image. Experimental results show that our framework achieves up to 12% improvements in performance on widely used benchmarking datasets compared to current state-of-the-art image forgery localization models. Encouragingly, the model demonstrates strong performance on forensic tasks involving real-world document forgery images and natural scene forging images, even when such data were entirely unseen during training.

cs.CV↗

arXiv2025

CU-JADE: A Method for Traversing Extinction Jumps along the Line of Sight

Although interstellar dust extinction serves as a powerful distance estimator, the solar system's location within the Galactic plane complicates distance determinations, especially for molecular clouds (MCs) at varying distances along the line of sight (LoS). The presence of complex extinction patterns along the LoS introduces degeneracies, resulting in less accurate distance measurements to overlapping MCs in crowded regions of the Galactic plane. In this study, we develop the CUSUM-based Jump-point Analysis for Distance Estimation (CU-JADE), a novel method designed to help mitigate these observational challenges. The key strengths of CU-JADE include: (1) sensitivity to detect abrupt jumps in Distance-$A_λ$ ($D$-$A$) datasets, (2) minimal systematic errors as demonstrated on both mock and observed data, and (3) the ability to combine CUSUM analysis with multiwavelength data to improve the completeness of distance measurements for nearby gas structures, even for extinction values as low as $ΔA_{V} \gtrsim 0.15$ mag. By combining CO survey data with a large sample of stars characterized by high-precision parallaxes and extinctions, we uncovered the multilayered molecular gas distribution in the high-latitude Cepheus region. We also determined accurate distances to MCs beyond the Cygnus Rift by analyzing the intricate structure of gas and extinction within the Galactic plane. Additionally, we constructed a full-sky 3D extinction map extending to 4 kpc, which provides critical insights into dense interstellar medium components dominated by molecular hydrogen. These results advance our understanding of the spatial distribution and physical properties of MCs across the Milky Way.

astro-ph.GA↗

arXiv2025

Molecular Gas Distribution toward the Inner and Outer Galaxy Revealed by MWISP -- the Galactic Longitude 45°--60°and 120°--130°

Molecular clouds (MCs) are cradles of star and planet formation, thereby playing an important role in the evolution of galaxies. Based on the unbiased Milky Way Imaging Scroll Painting (MWISP) survey data of $^{12}$CO, $^{13}$CO, and C$^{18}$O (J=1--0) line emission in two regions toward the inner and outer Galaxy, i.e. the G50 ($44.75°\le l \le 60.25°$) and G120 ($119.75°\le l \le 130.25°$) regions, the distribution of molecular gas is studied. Both regions have Galactic latitudes of $|b| \le 5.25°$. A catalog containing 24724 MCs is constructed from the data. In our proximity, several molecular structures with large angular scales and small velocity dispersions are discovered, resembling curtains of mist. Beyond the nearby molecular gas, a clear aggregation of MCs along coherent structures in the Galactic plane is visible, sketching spiral arm structures. Nevertheless, the aggregation of MCs is also detected in the inter-arm region between the Perseus and Outer arms in the G50 region. The Galactic molecular disk in this inter-arm region is found to be thinner than that in the adjacent spiral arm region. In addition, the thickness of the Galactic molecular disk examined here is found to be correlated with the warp of it, indicating their homologous origins. The molecular disk has a typical thickness of ~220 pc in the inner Galaxy. Moreover, the dispersion of the MC systemic velocity decreases with increasing galactocentric radius, resulting in lower kinematic distance uncertainties at larger radii. However, the Perseus arm segment in the G120 region exhibits a relatively large cloud-to-cloud velocity dispersion and split components in its MC velocity distribution.

astro-ph.GA↗

arXiv2025

Intense Hard X-ray Emissions in C-class Flares: A Statistical Study with ASO-S/HXI Data

In the standard model of solar eruptive events, coronal mass ejections (CMEs) and flares are associated with each other through magnetic reconnection initiated by erupting flux ropes. Observations also reveal an increasing association ratio between flares and CMEs with flare intensity. However, the fundamental relationship between flares and CMEs, and that between thermal and nonthermal processes, remains unknown. Here we investigate energetic C-class flares (ECFs) -- Geostationary Operational Environmental Satellite (GOES) C-class flares with hard X-ray (HXR) emissions above 30 keV -- using observations from Advanced Space-based Solar Observatory/Hard X-ray Imager (HXI), Solar Dynamic Observatory, and GOES. Among 1331 C-class flares detected by HXI, 127 ECFs (9.5%) were identified for statistical analysis of their properties and associations with CMEs and other flare-related features. Our statistical results reveal that ECFs have relatively shorter durations and harder spectra (the mean electron power-law index is 4.65), with no significant correlation between soft X-ray flux and nonthermal parameters (e.g., HXR peak flux). Among the 127 events, 53 (42%) were associated with type III bursts, 38 (30%) with jets, at least 13 (~11%) with 360 nm brightenings, and only 5 (~4%) with CMEs. Crucially, all five CME events were narrow CMEs associated with jets. The surprising correlation between these ECFs and CMEs suggests that noneruptive or confined magnetic field configurations in these flares may favor electron acceleration, resulting in harder X-ray spectra.We discuss the potential formation mechanisms and efficient electron acceleration processes in these atypical flares, providing valuable insights into nonstandard flare behavior.

astro-ph.SR↗

arXiv2025

Responses of a Coronal Hole to a Fast Flare-Driven Coronal Wave

Coronal waves, significant solar phenomena, act as diagnostic tools for scientists studying solar atmosphere properties. Here, we present a novel observation detailing how a coronal wave event, associated with an X5.0 class flare, influenced the properties of an adjacent coronal hole through interaction. The coronal wave was observed in both extreme ultraviolet observations from the Atmospheric Imaging Assembly aboard the Solar Dynamics Observatory and Lyman-alpha observations from the Solar Disk Imager aboard the Advanced Space-based Solar Observatory. Utilizing the method of differential emission measure, we found that as the coronal wave passed through, the adjacent coronal hole experienced an increase in temperature from 1.31 to 1.43 MK and a rise in density from $\sim$1.62$\times10^{8}$ to 1.76$\times10^{8}$ cm$^{-3}$ within the rising period of $\sim$7 minutes. Subsequently, after the wave passed, the entire coronal hole transitioned to a new state with a slight temperature increase and a 14$\%$ decrease in density, with more pronounced changes observed at the coronal hole's boundary. Taking into account the impacts of radiative loss and heat conduction, the coronal wave was estimated to provide an average energy of 2.2$\times10^{8}$ erg cm$^{-2}$ to the coronal hole during the short rising period. This study highlights the identification of the coronal wave in both extreme ultraviolet and Lyman-alpha observations, shedding light on the significant energy input, particularly within the coronal hole. These findings provide new insights into better understanding kinematics of fast coronal waves, energy transfer processes open versus closed magnetic topologies, and the possible acceleration of solar winds.

astro-ph.SR↗

arXiv2025

HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization

Federated fine-tuning of pre-trained Large Language Models (LLMs) enables task-specific adaptation across diverse datasets while preserving privacy. However, challenges such as high computational and memory demands, heterogeneous client resources, bandwidth constraints, and ineffective global aggregation hinder its efficiency. To address these issues, we propose HAFLQ (Heterogeneous Adaptive Federated Low-Rank Adaptation Fine-tuned LLM with Quantization), a novel framework for efficient and scalable federated fine-tuning of LLMs in heterogeneous environments. To reduce memory and computation demands, we propose a salience-driven adaptive LLM quantization framework that evaluates the importance of transformer blocks using a salience metric and applies adaptive block-wise quantization accordingly. To handle heterogeneous computational capabilities, we propose an importance-based parameter truncation and freezing scheme. To address communication bottlenecks, we propose an importance-aware bandwidth-adaptive quantization method, which dynamically adjusts parameter precision based on importance and bandwidth constraints. To improve global model aggregation, we propose an adaptive rank-1 matrix-level aggregation strategy, which prevents information dilution and accelerates convergence by aggregating only updated rank-1 matrices from clients. Experimental results on the text classification task demonstrate that HAFLQ reduces memory usage by 31%, lowers communication cost by 49%, improves accuracy by 50%, and achieves faster convergence compared to the baseline method.

cs.LG↗

arXiv2025

Qwen3 Technical Report

In this work, we present Qwen3, the latest version of the Qwen model family. Qwen3 comprises a series of large language models (LLMs) designed to advance performance, efficiency, and multilingual capabilities. The Qwen3 series includes models of both dense and Mixture-of-Expert (MoE) architectures, with parameter scales ranging from 0.6 to 235 billion. A key innovation in Qwen3 is the integration of thinking mode (for complex, multi-step reasoning) and non-thinking mode (for rapid, context-driven responses) into a unified framework. This eliminates the need to switch between different models--such as chat-optimized models (e.g., GPT-4o) and dedicated reasoning models (e.g., QwQ-32B)--and enables dynamic mode switching based on user queries or chat templates. Meanwhile, Qwen3 introduces a thinking budget mechanism, allowing users to allocate computational resources adaptively during inference, thereby balancing latency and performance based on task complexity. Moreover, by leveraging the knowledge from the flagship models, we significantly reduce the computational resources required to build smaller-scale models, while ensuring their highly competitive performance. Empirical evaluations demonstrate that Qwen3 achieves state-of-the-art results across diverse benchmarks, including tasks in code generation, mathematical reasoning, agent tasks, etc., competitive against larger MoE models and proprietary models. Compared to its predecessor Qwen2.5, Qwen3 expands multilingual support from 29 to 119 languages and dialects, enhancing global accessibility through improved cross-lingual understanding and generation capabilities. To facilitate reproducibility and community-driven research and development, all Qwen3 models are publicly accessible under Apache 2.0.

cs.CL↗

arXiv2025

PWC-MoE: Privacy-Aware Wireless Collaborative Mixture of Experts

Large language models (LLMs) hosted on cloud servers alleviate the computational and storage burdens on local devices but raise privacy concerns due to sensitive data transmission and require substantial communication bandwidth, which is challenging in constrained environments. In contrast, small language models (SLMs) running locally enhance privacy but suffer from limited performance on complex tasks. To balance computational cost, performance, and privacy protection under bandwidth constraints, we propose a privacy-aware wireless collaborative mixture of experts (PWC-MoE) framework. Specifically, PWC-MoE employs a sparse privacy-aware gating network to dynamically route sensitive tokens to privacy experts located on local clients, while non-sensitive tokens are routed to non-privacy experts located at the remote base station. To achieve computational efficiency, the gating network ensures that each token is dynamically routed to and processed by only one expert. To enhance scalability and prevent overloading of specific experts, we introduce a group-wise load-balancing mechanism for the gating network that evenly distributes sensitive tokens among privacy experts and non-sensitive tokens among non-privacy experts. To adapt to bandwidth constraints while preserving model performance, we propose a bandwidth-adaptive and importance-aware token offloading scheme. This scheme incorporates an importance predictor to evaluate the importance scores of non-sensitive tokens, prioritizing the most important tokens for transmission to the base station based on their predicted importance and the available bandwidth. Experiments demonstrate that the PWC-MoE framework effectively preserves privacy and maintains high performance even in bandwidth-constrained environments, offering a practical solution for deploying LLMs in privacy-sensitive and bandwidth-limited scenarios.

cs.LG↗

arXiv2025

Gas Transfer Between the Inner 3-kpc Disk and the Galactic Central Molecular Zone

We uncovered a more tilted molecular gas structure with highly negative velocities located near the dust lane. Our observations also show that the approaching gas flows from the overshoot process are captured by the bar gravitational and then flows towards the Galactic central molecular zone (CMZ) through the bar channel. The recycling gas from the overshoot effect, in conjunction with freshly accreted gas from the inner 3-kpc disk, accumulates significantly near R_GC~1/2R_bar and R_GC~2/3R_bar regions by adopting a bar length of ~3.2--3.4kpc. Importantly, within these regions, there are frequent collisions and substantial angular momentum exchanges between gas flows with different trajectories. In this scenario, the DISSIPATION processes arising from interactions between colliding flows, together with the varying torques induced by the nonaxisymmetric bar, effectively transfer the angular momentum of viscous gas outward, thereby driving the molecular gas to settle into the CMZ within ~3 orbital periods. A long-term gas inflow with an average rate of >1.1Msun/yr, coupled with intense transient accretion events that exceed the average rate by several times due to the overshoot effect, significantly regulates the gas distribution, physical properties, and dynamical evolution of the CMZ. These findings provide robust observational evidence for elucidating the intricate dynamics of molecular gas flows towards the CMZ. Our results show that gas dynamics has a significant impact on the secular evolution of both the Milky Way and the extragalactic gas-rich galaxies.

astro-ph.GA↗

arXiv2025

Multiple generation star formation in Cepheus Flare

We present an analysis of the young stellar moving group ASCC 127 using Gaia DR3 data, significantly expanding its membership to 3,971 stars -- double the number identified in previous studies. Using kinematic and distance criteria, ASCC 127 is divided into five subgroups (Groups 1-5) with ages spanning from 15 to 32 Myr. Groups 1-5 are spatially linked to the Cepheus Flare star-forming region, revealing potential evidence of four sequential star formation episodes at approximately 32 Myr, 20 Myr, 15 Myr, and 7 Myr. Through dust and gas mapping, we identify a spatial cavity extending several tens of parsecs, which may have resulted from feedback processes such as supernovae associated with earlier generations of stars in the region. This structure, along with the larger Loop III feature, indicates that feedback from massive stars likely influenced the interstellar medium (ISM). By integrating young stellar populations with ISM studies, we provide a detailed picture of the feedback-driven star formation history in the Cepheus Flare region.

astro-ph.SR↗

arXiv2025

Unveiling Spatiotemporal Properties of the Quasi-periodic Pulsations in the Balmer Continuum at 3600 Å in an X-class Solar White-light Flare

Quasi-periodic pulsations (QPPs) in the Balmer continuum of solar white-light flares (WLFs) are rarely reported, and accurately pinpointing the spatial source of flaring QPPs remains a significant challenge. We present spatiotemporal characteristics of QPPs of an X2.8 two-ribbon solar WLF (SOL2023-12-14T17:02), which was well observed by the White-light Solar Telescope (WST) aboard the Advanced Space-based Solar Observatory, with high-cadence imaging (1--2 s) in the Balmer continuum at 3600 Å. Combined with additional multi-instrument data, we find that the enhancement of the WLF in both Balmer and Paschen continua shows strong spatiotemporal correlation with hard X-ray (HXR) emissions. Notably, the pulses in the WST Balmer continuum exhibited a near-zero time lag with most HXR pulses, whereas soft X-ray and extreme ultraviolet emissions showed a lag of 2--3 s. Interestingly, quasi-harmonic QPPs with periods of $\sim$11 s and $\sim$20 s were observed in multiple wavelengths in the rising phase of the white-light continuum. Furthermore, we employed Fourier transform to spatially locate the QPPs around 11 and 20 s, revealing that they primarily originated from the east flare ribbon, which exhibited the most substantial continuum enhancement. More interestingly, we find that the west ribbon contributed significantly to the 11-second QPP but had a weaker contribution to the 20-second QPP. Moreover, the occurrence of quasi-harmonic QPPs is temporally coincident with the rapid elongation and separation motions of flare ribbons. Possible mechanisms for the quasi-harmonic QPPs have been discussed. These observations provide valuable insights into QPP modeling for solar and stellar flares.

astro-ph.SR↗

arXiv2025

Fourier shape parametrization in covariant density functional theory for nuclear fission

We implement the Fourier shape parametrization within the point-coupling covariant density functional theory to construct the collective space, potential energy surface (PES), and mass tensor, which serve as inputs for the time-dependent generator coordinate method to simulate the fission dynamics. Taking $^{226}$Th as a benchmark, we demonstrate the superiority of Fourier shape parametrization over conventional spherical harmonic parametrization: it significantly enhances the convergence of higher-order collective shape parameters by efficiently characterizing extreme nuclear deformations. Consequently, the new framework generates more reasonable elongated configurations, particularly for the scission configurations, and significantly improves the description of charge distribution near the symmetric fission peak. Moreover, the Fourier shape parametrization provides a smooth and well-defined three-dimensional (3D) PES with minimal correlations between degrees of freedom, enabling high-precision 3D dynamical simulations of fission.

nucl-th↗

arXiv2025

Gaze-Guided Robotic Vascular Ultrasound Leveraging Human Intention Estimation

Medical ultrasound has been widely used to examine vascular structure in modern clinical practice. However, traditional ultrasound examination often faces challenges related to inter- and intra-operator variation. The robotic ultrasound system (RUSS) appears as a potential solution for such challenges because of its superiority in stability and reproducibility. Given the complex anatomy of human vasculature, multiple vessels often appear in ultrasound images, or a single vessel bifurcates into branches, complicating the examination process. To tackle this challenge, this work presents a gaze-guided RUSS for vascular applications. A gaze tracker captures the eye movements of the operator. The extracted gaze signal guides the RUSS to follow the correct vessel when it bifurcates. Additionally, a gaze-guided segmentation network is proposed to enhance segmentation robustness by exploiting gaze information. However, gaze signals are often noisy, requiring interpretation to accurately discern the operator's true intentions. To this end, this study proposes a stabilization module to process raw gaze data. The inferred attention heatmap is utilized as a region proposal to aid segmentation and serve as a trigger signal when the operator needs to adjust the scanning target, such as when a bifurcation appears. To ensure appropriate contact between the probe and surface during scanning, an automatic ultrasound confidence-based orientation correction method is developed. In experiments, we demonstrated the efficiency of the proposed gaze-guided segmentation pipeline by comparing it with other methods. Besides, the performance of the proposed gaze-guided RUSS was also validated as a whole on a realistic arm phantom with an uneven surface.

cs.RO↗

arXiv2025

Examining Turbulence in Galactic Molecular Clouds -- I: A Statistical Analysis of Velocity Structures

We present a systematic analysis of the velocity structure functions (VSFs) of 167 molecular clouds with angular sizes greater than $\sim$176 arcmin$^2$ in three sectors of the Galactic mid-plane. We calculated the 1st- to 3rd-order VSFs and found that 60\% of the VSFs exhibit power-law distributions. The relative power-law exponents are consistent with predictions from intermittent turbulence models. Column density weighting reduces the proportion of power-law VSFs and steepens the VSF slopes, implying a reduction of turbulent energy in high-density regions. All clouds show small-scale intermittency, with slightly stronger intermittency in those molecular clouds showing none power-law VSFs. Negative VSF exponents that may indicate gravitational collapse are not observed in our sample. The scaling exponents of the observed VSFs do not correlate with the virial parameters of the molecular clouds. These two observations suggest that gravity-dominated scales in molecular clouds still need further investigation. Consistent VSF scaling exponents for the molecular clouds with significant power-law VSFs suggest large-scale external driving of turbulence in these molecular clouds. However, the driving mechanisms are likely not universal, as the power-law scaling coefficients in our results show relatively large scatter. The fact that nearly 40\% of the VSFs deviate to some extent from power-law distributions suggests that the influence of local environments on the internal turbulence of molecular clouds may not be negligible.

astro-ph.GA↗

arXiv2025

Federated Fine-Tuning of LLMs: Framework Comparison and Research Directions

Federated learning (FL) provides a privacy-preserving solution for fine-tuning pre-trained large language models (LLMs) using distributed private datasets, enabling task-specific adaptation while preserving data privacy. However, fine-tuning the extensive parameters in LLMs is particularly challenging in resource-constrained federated scenarios due to the significant communication and computational costs. To gain a deeper understanding of how these challenges can be addressed, this article conducts a comparative analysis three advanced federated LLM (FedLLM) frameworks that integrate knowledge distillation (KD) and split learning (SL) to mitigate these issues: 1) FedLLMs, where clients upload model parameters or gradients to enable straightforward and effective fine-tuning; 2) KD-FedLLMs, which leverage KD for efficient knowledge sharing via logits; and 3) Split-FedLLMs, which split the LLMs into two parts, with one part executed on the client and the other one on the server, to balance the computational load. Each framework is evaluated based on key performance metrics, including model accuracy, communication overhead, and client-side computational load, offering insights into their effectiveness for various federated fine-tuning scenarios. Through this analysis, we identify framework-specific optimization opportunities to enhance the efficiency of FedLLMs and discuss broader research directions, highlighting open opportunities to better adapt FedLLMs for real-world applications. A use case is presented to demonstrate the performance comparison of these three frameworks under varying configurations and settings.

cs.LG↗