arXiv subjects

Shuo Cao

Publications and source records attributed to Shuo Cao.

At least 19 recordsLinked to original sources

arXiv2026

Qwen-Image-PE: Learning Visual Design for Text-to-Image Prompt Enhancement

Learning visual design is essential for prompt enhancement (PE) to turn underspecified user requests into coherent visual specifications for text-to-image (T2I) generation. Existing methods preserve user intent and improve overall visual appeal, with less explicit emphasis on fine-grained design dimensions. To address this gap, we introduce Qwen-Image-PE, which learns visual design through two-stage training. Supervised fine-tuning with Caption-Based Reverse Distillation (CRD) uses dense captions of well-designed images as design supervision. Reinforcement learning with Groupwise Design Reward (GDR) jointly compares all candidate images for the same request to refine lighting, composition, layout, and detail. On Qwen-Image-Bench with Qwen-Image-2.1, Qwen-Image-PE-397B improves over original requests by 7.81 points, while Qwen-Image-PE-9B outperforms all evaluated PE baselines. Further evaluations show gains in visual design, aesthetics, image quality, and human preference. We find that PE scales along three axes: training data, model size, and information density, with sufficient information density as a prerequisite for effective enhancement. Moreover, we demonstrate that Qwen-Image-PE generalizes to four additional T2I backbones, even surpassing native prompt enhancers on HunyuanImage-2.1 and FLUX 3 Image Klein. We release Qwen-Image-PE-9B at https://huggingface.co/Qwen/Qwen-Image-2.1-PE-T2I.

cs.CV↗

arXiv2026

No Strong Evidence for Plasma Lensing in FRB 20240114A

FRB 20240114A is an extremely active repeating fast radio burst for which plasma lensing has been proposed to explain its burst-rate variations, spectral evolution, and apparently ``carbon-copy'' burst pairs. Using FAST data and publicly available Parkes observations, we test this interpretation with the predictions of a one-dimensional Gaussian plasma-lens model. Although the burst-rate enhancements may be fitted separately for Parkes and FAST, the corresponding magnification peaks and demagnification troughs between the two datasets are offset from each other, inconsistent with plasma lensing predictions. The enhancement peaks also do not show consistent periodicity, disfavoring a binary plasma lensing origin. The burst bandwidths are not systematically narrower during the proposed lensing interval than in other episodes. Most importantly, the burst energy distribution, which shows an intrinsic turnover peak at low energies, shows no significant shift of the turnover during the magnification interval, providing a model-independent test to the plasma-lensing interpretation. All these suggest that there is no strong evidence in favor of a plasma lensing interpretation to the source. Rather, all the burst property variations are consistent with being caused by the intrinsic variations of the FRB central engine.

astro-ph.HE↗

arXiv2026

Probing generalized equation of state for dark energy with latest cosmological probes

Baryon acoustic oscillation (BAO) measurements from DESI DR2 have strengthened indications of a time-evolving dark energy. In this paper, we investigate observational constraints on the generalized equation of state (GEoS) for dark energy, $w(a) = w_0 - w_β(a^β- 1)/β$, with latest data from UV and X-ray observations of high-redshift quasars, DESI DR2 BAO, Cosmic Microwave Background (CMB) data (including lensing) from Planck and the Atacama Cosmology Telescope (ACT), and Pantheon+ Type Ia Supernovae (SNe Ia). The full Quasar+BAO+CMB+SNe Ia data combination yields stringent constraints on the EoS parameters of $w_0=-0.840^{+0.057}_{-0.084}$, $w_β=-0.90^{+0.88}_{-0.23}$, and $β=2.2^{+2.4}_{-5.2}$. Specially, the $β$ parameter, which describe a broad range of dark energy evolution, is in perfect agreement with the Chevallier--Polarski--Linder model ($β=1$) -- the most widely used two-parameter parametrizations of dynamical dark energy. We also compare GEoS with other dynamical dark-energy parametrizations including CPL, Barboza--Alcaniz (BA) and Jassal--Bagla--Padmanabhan (JBP), and report three key findings. Firstly, we find compelling evidence for dynamical dark energy: all four EoS parametrizations yield lower information criterion (IC) values than $Λ$CDM for the full data combination, indicating a preference for EoS parametrizations under the Akaike information criterion (AIC) and the variance-based deviance information criterion (DIC). Secondly, although the unified phenomenological framework GEoS performs better than JBP, the current data do not strongly discriminate among different EoS parametrizations. Thirdly, the EoS trajectories of GEoS, CPL, and BA exhibit qualitatively similar transitions from the phantom regime at higher redshifts to the quintessence regime at late times, while the JBP parametrization exhibits a nonmonotonic evolution.

physics.gen-ph↗

arXiv2026

Revisiting self-interacting dark matter with DESI DR2 baryon acoustic oscillation observations

We revisit self-interacting dark matter (SIDM), originally proposed to resolve small-scale CDM problems and drive late-time cosmic acceleration. Using latest DESI BAO, Pantheon+/DESY5 type Ia supernova, and cosmic chronometer Hubble data, we constrain three representative SIDM scenarios including creation and annihilation. We focus on the annihilation of dark matter particles in model SIDM1; our findings indicate the effective annihilation cross section is $\log_{10}(κC_1)=-4.32$ (with an upper limit of $\log_{10}(κC_1)=-3.90$). For the SIDM2 model, the SIDM fluid behaves similarly to a dark energy component with a mildly dynamical equation of state ($w_{\rm{SIDM}}=-0.82 \pm 0.04$). We also quantitatively discuss the dark matter self-interactions in a more general SIDM model (SIDM3), which reveals a strong correlation between the annihilation cross section and equation of state of dark matter. For the three SIDM models, the measured Hubble constant agrees with that derived from the recent Planck 2018 results; both are inconsistent with the results of the SH0ES collaboration, who report a significantly higher $H_0$ value. The Bayesian evidence indicates that SIDM2 and SIDM3 are more supported by the available observational data than the concordance standard $Λ$CDM. Furthermore, the cosmological constraints on the effective annihilation parameter can be translated into bounds on the velocity-averaged annihilation cross section and the self-interaction cross section per unit mass. While low-redshift data alone imply a relatively large cross section, the inclusion of cosmic microwave background distance priors significantly tightens the constraint at cluster-scale velocities, highlighting the necessity of a velocity-dependent cross section to reconcile cosmological and astrophysical observations.

physics.gen-ph↗

arXiv2026

Testing General Relativity with Binary Lens Microlensing Events

Einstein's General Relativity (GR), which has been precisely tested on galaxy and solar system scales, is still poorly constrained in extremely weak gravitational fields (with dimensionless Newtonian potentials of $Φ\sim 10^{-8}$). In this Letter, we propose a new method to probe such a weak-field regime of gravity and measure the spatial curvature generated per unit mass. Specifically, binary microlensing events provide a laboratory to measure the parameterized post-Newtonian (PPN) parameter ($γ$), by combining the lensing mass ($M_{\rm lens}^{\rm GR}$) inferred from microlensing with the dynamical mass ($M_{\rm dyn}$) determined from interferometric astrometry. Astrometric tracking of binary lenses was previously hindered by their faintness and minuscule angular separations (typically a few milliarcseconds). This limitation has been alleviated by the deployment of GRAVITY+, which pushes the instrument's sensitivity and astrometric precision to unprecedented heights. Based on astrometric simulations of the binary microlensing event ASASSN-22av, we directly estimate $γ$ at the precision of ~23%. Such test of GR in the extremely weak-field regime can be further improved to much higher precision (~3%), based on more binary microlensing events with precise determination of the dynamical/lens mass.

gr-qc↗

arXiv2026

Revisiting the Hubble Tension with DESI DR2 Baryon Acoustic Oscillation Observations and Machine Learning Methods

One of the key unresolved questions in modern cosmology is the Hubble tension, which arises from the inconsistency between determinations of the Hubble constant ($H_0$) based on nearby observations and those predicted by early-Universe data under the standard $Λ$CDM paradigm. Recent advances have identified the new Dark Energy Spectroscopic Instrument (DESI) survey as a promising observational tool for probing late-time cosmology. In this paper, we use the latest DESI DR2 baryon acoustic oscillation (BAO) measurements, combined with nonparametrically reconstructed Type Ia supernovae and cosmic chronometer data, to constrain the Hubble constant using three complementary machine learning methodologies: Gaussian process regression (GPR), artificial neural networks (ANNs), and long short-term memory (LSTM) networks. We perform individual and joint constraints on $H_0$ at the effective redshifts of DESI DR2 tracers, yielding $H_0 = 61.8 \pm 5.3\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ (GPR), $66.3 \pm 5.2\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ (ANN), and $68.7 \pm 6.0\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ (LSTM). Our results exhibit excellent agreement with the recent Planck measurements within $1σ$, which highlight the potential of data-driven, model-independent methods to address the Hubble tension. Finally, we further test the sensitivity of our results to potential systematics in the DESI data, emphasizing the importance of understanding systematic uncertainties in BAO surveys.

physics.gen-ph↗

arXiv2026

Predictions on the abundance of primordial black holes: results from the SMILE VLBI milli-lensing sample

Primordial black holes (PBHs) formed in the early universe represent a well-motivated dark matter candidate. However, their abundance in the intermediate-to-high mass range ($10^6$-$10^9\,M_\odot$) remains relatively less constrained. In this mass regime, the corresponding Einstein radii on the milliarcsecond scale make Very Long Baseline Interferometry (VLBI) the most direct observational probe via milli-lensing of compact radio sources. In this paper, we present predictions for the abundance of PBH dark matter ($f_{\rm PBH}$) using the large SMILE sample of $\sim 5000$ flat-spectrum compact radio sources. Under the optimistic observational conditions (with an angular resolution of $1.5\,\mathrm{mas}$, a maximum image separation of $100\,\mathrm{mas}$, and a maximum detectable flux ratio of $40$), assuming that no milli-lensing events are confirmed, we obtain the projected 95% upper limit of $f_{\rm PBH}\lesssim0.12%$ in the intermediate-to-high mass range, which would be approximately an order of magnitude tighter than previous VLBI milli-lensing limits. Broader lognormal mass functions yield correspondingly weaker projected limits. Generalising the optical depth to account for magnification bias and finite-core resolvability changes these projected limits by only about $5$%. Moreover, we show that the predicted limits are highly sensitive to a small number of confirmed events, i.e., even one confirmed milli-lensing event would relax the projected upper limit to $0.20$%, highlighting the critical importance of robust candidate confirmation in the SMILE sample. Finally, under the optimistic baryonic accretion scenario, the PBH mass growth changes the projected limits by $\lesssim 1$% within the VLBI-sensitive mass range, confirming the robustness of our results.

astro-ph.CO↗

arXiv2026

ProcArena: A Multi-Scenario Benchmark for LLMs on Direct and Interactive PL/SQL Development from Natural Language

Large language models (LLMs) have shown strong potential for translating natural-language (NL) requirements into PL/SQL programs, attracting increasing attention from the database community. However, existing NL-to-PL/SQL efforts primarily focus on directly generating PL/SQL from complete NL requirements. In practice, PL/SQL development involves diverse scenarios, such as from-scratch development, code modification, debugging, and optimization, and may require either direct generation or multi-turn interaction. Yet, no comprehensive benchmark evaluates multi-scenario, direct and interactive, and multi-dialect NL-to-PL/SQL development. In this paper, we present ProcArena, an execution-based benchmark covering both Direct and Interactive modes. ProcArena comprises 3,998 executable tasks over 157 databases, spanning nine development subscenarios in PostgreSQL and Oracle. We construct challenging Direct tasks through Iterative Logic Enhancement and scenario-specific adapters, and derive paired Interactive tasks through Knowledge Integration and Requirement Perturbation while preserving executable targets. We further design a controlled Solver-User Simulator protocol that allows models to clarify user intent and inspect the database environment without exposing hidden execution feedback. Evaluating seven language models, we find that the best average scores are only 62.2% and 57.8% in Direct and Interactive, respectively, demonstrating that realistic NL-to-PL/SQL development remains challenging, particularly in interactive settings.

cs.CL↗

arXiv2026

Accelerating Masked Image Generation by Learning Controlled Latent Dynamics

Masked Image Generation Models (MIGMs) have achieved great success, yet their efficiency is hampered by the multiple steps of bi-directional attention. In fact, there exists notable redundancy in their computation: when sampling discrete tokens, the rich semantics contained in the continuous features are lost. Some existing works attempt to cache the features to approximate future features. However, they exhibit considerable approximation error under aggressive acceleration settings. We attribute this to their limited expressivity and the failure to account for sampling information. To fill this gap, we propose learning a lightweight model that incorporates both previous features and sampled tokens, and regresses the average velocity field of feature evolution. The model has moderate complexity that suffices to capture the subtle dynamics while keeping lightweight compared to the original base model. We apply our method to two representative MIGMs and tasks. In particular, on the state-of-the-art Lumina-DiMOO, it achieves over 4x acceleration of text-to-image generation while maintaining quality, significantly pushing the Pareto frontier of masked image generation. The code and model weights are available at https://github.com/Kaiwen-Zhu/MIGM-Shortcut.

cs.CV↗

arXiv2026

Anisotropic Tensile Strength and Fracture Mechanism of $θ$-TaN: A Machine-Learning Potential Molecular Dynamics Study

theta-phase tantalum nitride (theta-TaN) combines metallic conductivity with exceptionally high thermal conductivity, making it a potential material for device thermal management and interconnect applications. However, its tensile strength and fracture behavior remain unclear. Here, we investigate the anisotropic tensile response and fracture mechanism of theta-TaN using neuroevolution-potential molecular dynamics simulations. Size-convergence tests show that a 20 nm long model is sufficient for reliable prediction, and the mechanical parameters vary by less than 3.5% over the strain-rate range of 10^7 to 10^9 s^-1. The results reveal strong tensile anisotropy. The c-axis direction ([0001]) shows a higher strength of 80.10 GPa and modulus of 748.63 GPa, but a lower fracture strain of 15.02%. In contrast, the a-axis direction ([2-1-10]) shows a lower strength of 56.87 GPa and modulus of 570.74 GPa, but a higher fracture strain of 17.71%. From 300 to 900 K, the mechanical properties decrease nearly linearly, while more than 73% of the 300 K strength is retained at 900 K. Fracture occurs without observable dislocation activity and is governed by cleavage-plane selection: {10-10} prismatic planes under a-axis tension and the (0001) basal plane under c-axis tension. Atomic displacement analysis shows that local separation and microvoid formation precede macroscopic crack growth, indicating a brittle fracture process driven by local bond-network instability. These results provide atomic-scale mechanical data for assessing the reliability of theta-TaN in thermal management applications.

cond-mat.mtrl-sci↗

arXiv2026

See2Think: Do Multimodal Models Really Use Intermediate Visual States?

Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether they truly rely on these visual states. Existing benchmarks are limited both by task collections with narrow coverage or partially text-solvable samples and by evaluations that emphasize final answers without diagnosing how intermediate visual states are generated, rendered, and used. We introduce See2Think, a unified evaluation framework comprising See2ThinkBench and Visual Action-of-Thought (VAoT). See2ThinkBench contains 1,200 open-ended, visually dependent problems across 12 task categories spanning 2D structured, 3D scene, and real-world reasoning. VAoT records textual thoughts, visual actions, rendered states, and subsequent reasoning under four controlled inference settings. Evaluating representative proprietary and open-source multimodal models, we find that visual reasoning is strongly model- and environment-dependent, with no single setting consistently dominating across tasks. Process analysis further shows that models usually select relevant visual operations, while faithful rendering remains the clearest bottleneck and high feedback uptake does not necessarily translate into accuracy gains. Under task-relevant corrupted feedback, models exhibit behavioral dependence on visual states, with accuracy dropping by over 10 percentage points in controlled interventions.

cs.CV↗

arXiv2026

Extragalactic test of General Relativity with time-delay gravitational lenses

Strong gravitational lensing, a key prediction of General Relativity (GR), offers a unique environment for examining alternative modified gravity theories. In this Letter, we employ a model-independent approach to estimate the parameterized post-Newtonian parameter $γ_{\rm PPN}$ using the time-delay measurements from H0LiCOW strong lensing systems. To minimize potential biases from cosmological models in testing GR, we use Gaussian Process regression (GPR) to reconstruct angular diameter distances ($D_{\rm A}$) from the newest baryon acoustic oscillation (BAO) measurements, provided by the Dark Energy Spectroscopic Instrument (DESI) DR2 data. Based on the reconstructed angular diameter distances and four H0LiCOW lenses, we directly estimate the post-Newtonian parameter $γ_{\rm PPN}=0.93^{+0.16}_{-0.17}$ and the sound horizon scale $r_{\rm d}=136.36^{+5.14}_{-3.20}~{\rm Mpc}$. This is the first simultaneous measurement of $γ_{\rm PPN}$ and $r_{\rm d}$ without any assumptions about the contents of the universe or the theory of gravity. In the new framework of distance ratio $D_{Δt}/D_{\rm l}$ which avoids the bias introduced by $r_{\rm d}$, the $γ_{\rm PPN}$ constraint can be further improved to $γ_{\rm PPN}=0.89^{+0.19}_{-0.15}$. Our results provide a direct test of GR at the extragalactic scale, which is well consistent with the prediction of GR within $1σ$.

astro-ph.CO↗

arXiv2026

A Pilot Study of Mildly Recycled Pulsars: A Case Study of PSR J2338+4818

Mildly recycled pulsars are neutron stars partially spun up through relatively short mass-transfer phases, typically with massive carbon-oxygen (CO) or oxygen-neon-magnesium (ONeMg) white dwarf companions. PSR J2338+4818, a mildly recycled pulsar, was discovered with the Five-hundred-meter Aperture Spherical Telescope (FAST). As a pilot study on the formation and evolutionary pathways of mildly recycled pulsars, we present the updated timing solution for PSR J2338+4818 and examine its single pulses and scintillation properties. Aided by the sensitivity of FAST, the single pulses of PSR J2338+4818 were systematically studied. 27,228 single pulses with S/N > 7 have been detected in our observations. For the FAST ultra-wideband observation on MJD 61045, the receiver was still in the technical commissioning phase, and then only a preliminary single-pulse search was performed. Pulse nulling was examined using a Markov Chain Monte Carlo (MCMC) method, but no evidence for nulling was found. The possible long-term nulling reported by previous studies did not occur in any of our observations in either the 1.0 to 1.5 GHz band or the 300 to 600 MHz band. Interstellar scintillation is evident in our observations. The measured scintillation timescales and bandwidths range from 2.93 to 25.26 minutes and 1.68 to 27.41 MHz, respectively. In all observations, no clear scintillation arc was found in the secondary spectra of PSR J2338+4818.

astro-ph.HE↗

arXiv2026

StableI2I: Spotting Unintended Changes in Image-to-Image Transition

In most real-world image-to-image (I2I) scenarios, existing evaluations primarily focus on instruction following and the perceptual quality or aesthetics of the generated images. However, they largely fail to assess whether the output image preserves the semantic correspondence and spatial structure of the input image. To address this limitation, we propose StableI2I, a unified and dynamic evaluation framework that explicitly measures content fidelity and pre--post consistency across a wide range of I2I tasks without requiring reference images, including image editing and image restoration. In addition, we construct StableI2I-Bench, a benchmark designed to systematically evaluate the accuracy of MLLMs on such fidelity and consistency assessment tasks. Extensive experimental results demonstrate that StableI2I provides accurate, fine-grained, and interpretable evaluations of content fidelity and consistency, with strong correlations to human subjective judgments. Our framework serves as a practical and reliable evaluation tool for diagnosing content consistency and benchmarking model performance in real-world I2I systems.

cs.CV↗

arXiv2026

FAST Polarization Catalog of FRB 20240114A

Polarization measurements of fast radio bursts (FRBs) probe the magnetized plasma surrounding their central engines. FRB~20240114A is an exceptionally active repeating source, with 17,356 bursts detected between 2024 January 28 and 2025 May 30 by FAST, enabling time-resolved polarimetric studies. In this work, we present a polarimetric catalog of 6,131 bright bursts (with a signal-to-noise ratio S/N $\geq$ 20, 35.3% of the total sample), including arrival time (MJD$_{\text{topo}}$), dispersion measure (DM), burst width (W$_{\text{eff}}$), bandwidth, Faraday rotation measure (RM), linear and circular polarization degrees (DOL, DOC), and intrinsic polarization angle (PA$_0$). We detect a clear temporal evolution of RM: after an initial stable phase, it decreases linearly by $\sim$200 $\rm rad\ m^{-2}$ over 200 days, forming a bimodal distribution, whereas DM remains stable at 528.9 $\rm pc\ cm^{-3}$. The linear polarization fraction is generally high, with the 3$σ$ lower bound around 76%, while circular polarization is low, with 1,157 of 17,356 bursts (6.67%) having DOC $\geq$10%. We perform a power-law fit between $|\textrm{V}|$/I and $|\textrm{RM}|$, which yields an index of $-2.98 \pm 0.80$. It is found that the combined 2D distribution of L/I versus V/I remains stable, implying that the emission mechanism is largely invariant. Our PA$_0$ measurements show a broad, non-uniform distribution, implying a complex emission geometry. These results suggest that FRB~20240114A resides in a dynamically evolving magneto-ionic environment. This catalog provides a foundation for studies of repeating FRB progenitors and their environments.

astro-ph.HE↗

arXiv2026

dMLLM-TTS: Self-Verified and Efficient Test-Time Scaling for Diffusion Multi-Modal Large Language Models

Diffusion Multi-modal Large Language Models (dMLLMs) have recently emerged as a novel architecture unifying image generation and understanding. However, developing effective and efficient Test-Time Scaling (TTS) methods to unlock their full generative potential remains an underexplored challenge. To address this, we propose dMLLM-TTS, a novel framework operating on two complementary scaling axes: (1) trajectory exploration scaling to enhance the diversity of generated hypotheses, and (2) iterative refinement scaling for stable generation. Conventional TTS approaches typically perform linear search across these two dimensions, incurring substantial computational costs of O(NT) and requiring an external verifier for best-of-N selection. To overcome these limitations, we propose two innovations. First, we design an efficient hierarchical search algorithm with O(N+T) complexity that adaptively expands and prunes sampling trajectories. Second, we introduce a self-verified feedback mechanism that leverages the dMLLMs' intrinsic image understanding capabilities to assess text-image alignment, eliminating the need for external verifier. Extensive experiments on the GenEval benchmark across three representative dMLLMs (e.g., Lumina-DiMOO, MMaDA, Muddit) show that our framework substantially improves generation quality while achieving up to 6x greater efficiency than linear search. Project page: https://github.com/Alpha-VLLM/Lumina-DiMOO.

cs.CV↗

arXiv2026

Inflation driven by a bare cosmological constant and its graceful exit

Vacuum energy, a prediction of quantum field theory, manifests itself as a cosmological constant in general relativity. In this Letter, we propose a novel inflationary scenario driven by a bare cosmological constant $Λ$, which terminates naturally through a self-tuning mechanism. Within Fab-Four gravity, self-tuning destabilizes the de Sitter state and drives the system toward a stiff-fluid attractor, thereby yielding a graceful exit. We construct two explicit models in which the slow-roll parameter evolves exponentially or as a power law. We show that the latter model, derived from center-manifold dynamics, significantly relaxes the required tuning of initial conditions. Our results establish, for the first time, that bare-vacuum-energy inflation with natural termination constitutes a viable dynamical possibility.

gr-qc↗

arXiv2026

LinearSR: Unlocking Linear Attention for Stable and Efficient Image Super-Resolution

Generative models for Image Super-Resolution (SR) are increasingly powerful, yet their reliance on self-attention's quadratic complexity (O(N^2)) creates a major computational bottleneck. Linear Attention offers an O(N) solution, but its promise for photorealistic SR has remained largely untapped, historically hindered by a cascade of interrelated and previously unsolved challenges. This paper introduces LinearSR, a holistic framework that, for the first time, systematically overcomes these critical hurdles. Specifically, we resolve a fundamental, training instability that causes catastrophic model divergence using our novel "knee point"-based Early-Stopping Guided Fine-tuning (ESGF) strategy. Furthermore, we mitigate the classic perception-distortion trade-off with a dedicated SNR-based Mixture of Experts (MoE) architecture. Finally, we establish an effective and lightweight guidance paradigm, TAG, derived from our "precision-over-volume" principle. Our resulting LinearSR model simultaneously delivers state-of-the-art perceptual quality with exceptional efficiency. Its core diffusion forward pass (1-NFE) achieves SOTA-level speed, while its overall multi-step inference time remains highly competitive. This work provides the first robust methodology for applying Linear Attention in the photorealistic SR domain, establishing a foundational paradigm for future research in efficient generative super-resolution.

cs.CV↗