arXiv subjects

Xiang Liu

Publications and source records attributed to Xiang Liu.

At least 91 records · Page 5Linked to original sources

arXiv2026

Electromagnetic characteristics as probes into the inner structures of the predicted $Ξ_c^{(',)}D^{()}_s$ molecular states

In this work, we conduct a systematic investigation of the electromagnetic properties, specifically the magnetic moments and the M1 radiative decay behavior, of the predicted $Ξ_c^{(',*)}D^{(*)}_s$-type double-charm hidden-strangeness molecular pentaquarks. The study is carried out within the framework of the constituent quark model to evaluate these electromagnetic observables, and our analysis incorporates three distinct scenarios: single-channel analysis, $S$-$D$ wave mixing analysis, and coupled-channel analysis. The calculated magnetic moments reveal characteristic patterns that reflect their underlying constituent configurations and provide sensitive probes for their quantum number assignments. Furthermore, we identify several M1 radiative decay channels with sizable widths that may offer promising signatures for future experimental detection. These M1 transitions also act as sensitive probes into their inner structures, displaying distinctive features that help differentiate between their constituent configurations and quantum number assignments. We anticipate that this study will stimulate experimental interest in exploring the electromagnetic properties of the $Ξ_c^{(',*)}D^{(*)}_s$ molecular states, thereby advancing our structural understanding of these exotic hadronic states.

hep-ph↗

arXiv2026

Assessing the validity of the Born-Oppenheimer approximation in potential models for doubly heavy hadrons

The Born-Oppenheimer approximation is widely used to investigate the properties of hydrogen-like systems and doubly heavy hadrons. However, the extent to which this approximation captures the features of such systems within potential models remains an open question. In this work, we adopt the results obtained with the Gaussian expansion method as a benchmark to assess the validity of the Born-Oppenheimer approximation within potential models for hadronic systems. We also investigate the dependence of the Born-Oppenheimer approximation results on the choice of trial wave functions. A comprehensive study of the Born-Oppenheimer approximation is carried out by performing calculations using Slater-type functions and Gaussian-type functions as trial wave functions, and by comparing the resulting predictions with those obtained from the Gaussian expansion method. We find that the calculations performed within the Born-Oppenheimer approximation are close to those obtained with the Gaussian expansion method when the heavy-quark mass is relatively small. However, as the heavy-quark mass increases, calculations employing Slater-type functions yield larger values than those from the Gaussian expansion method, whereas those using Gaussian-type functions lead to smaller ones. The use of Slater-type functions generally leads to an enhanced binding energy. The underestimation observed in Born-Oppenheimer approximation calculations with Gaussian-type functions primarily stems from the neglect of non-adiabatic corrections. This comparative study provides deeper insight into the structure of doubly heavy hadrons and helps clarify the applicability and limitations of the Born-Oppenheimer treatment within potential models.

hep-ph↗

arXiv2026

Colloquium: Hadron Production in Open-charm Meson Pair at $e^+e^-$ Collider

The standard model of particle physics is a well-established theoretical framework, yet several unresolved issues remain that warrant further experimental and theoretical exploration. In the realm of quark physics, these issues include understanding the nature of quark confinement and elucidating the mechanism linking quarks and gluons to strongly interacting particles within the standard model theory, which may offer insights into the underlying physics mechanisms. These issues inquiries can be addressed through the study of hadrons produced at $e^+e^-$ collisions and decaying to open-charm meson pairs utilizing the capabilities of {\it BABAR}, Belle, BESIII, and CLEO-c experiments, which have yielded valuable insights into nonstandard hadrons in recent decades. This Colloquium examines the contributions of $e^+e^-$ colliders from the {\it BABAR}, Belle, BESIII, and CLEO-c experiments to such studies in the past two decades and discusses future prospects for $e^+e^-$ collider experiments.

hep-ex↗

arXiv2026

How Does Alignment Enhance LLMs' Multilingual Capabilities? A Language Neurons Perspective

Multilingual Alignment is an effective and representative paradigm to enhance LLMs' multilingual capabilities, which transfers the capabilities from the high-resource languages to the low-resource languages. Meanwhile, some research on language-specific neurons provides a new perspective to analyze and understand LLMs' mechanisms. However, we find that there are many neurons that are shared by multiple but not all languages and cannot be correctly classified. In this work, we propose a ternary classification methodology that categorizes neurons into three types, including language-specific neurons, language-related neurons, and general neurons. And we propose a corresponding identification algorithm to distinguish these different types of neurons. Furthermore, based on the distributional characteristics of different types of neurons, we divide the LLMs' internal process for multilingual inference into four parts: (1) multilingual understanding, (2) shared semantic space reasoning, (3) multilingual output space transformation, and (4) vocabulary space outputting. Additionally, we systematically analyze the models before and after alignment with a focus on different types of neurons. We also analyze the phenomenon of "Spontaneous Multilingual Alignment". Overall, our work conducts a comprehensive investigation based on different types of neurons, providing empirical results and valuable insights to better understand multilingual alignment and multilingual capabilities of LLMs.

cs.CL↗

arXiv2026

Enhanced Structured Lasso Pruning with Class-wise Information

Modern applications require lightweight neural network models. Most existing neural network pruning methods focus on removing unimportant filters; however, these may result in the loss of statistical information after pruning due to failing to consider the class-wise information. In this paper, we employ the structured lasso from the perspective of utilizing precise class-wise information for model pruning with the help of Information Bottleneck theory, which guides us to ensure the retention of statistical information before and after pruning. With these techniques, we propose two novel adaptive network pruning schemes in parallel: sparse graph-structured lasso pruning with Information Bottleneck (sGLP-IB) and sparse tree-guided lasso pruning with Information Bottleneck (sTLP-IB). The key component is that we prune the model filters utilizing sGLP-IB and sTLP-IB with more precise structured class-wise relatedness. Compared to multiple state-of-the-art methods, our approaches achieve the best performance across three datasets and six model structures on extensive experiments. For example, with the VGG16 model based on the CIFAR-10 dataset, we can reduce the parameters by 85%, decrease the FLOPs by 61%, and maintain an accuracy of 94.10% (0.14% better than the original). For large-scale ImageNet, we can reduce the parameters by 55% while keeping the accuracy at 76.12% (only drop 0.03%) using the ResNet architecture. In summary, we succeed in reducing the model size and computational resource usage while maintaining the effectiveness of accuracy.

cs.CV↗

arXiv2026

SSR: Speculative Parallel Scaling Reasoning in Test-time

Large language models (LLMs) have achieved impressive results on multi-step mathematical reasoning, yet at the cost of high computational overhead. This challenge is particularly acute for test-time scaling methods such as parallel decoding, which increase answer diversity but scale poorly in efficiency. To address this efficiency-accuracy trade-off, we propose SSR (Speculative Parallel Scaling Reasoning), a training-free framework that leverages a key insight: by introducing speculative decoding at the step level, we can accelerate reasoning without sacrificing correctness. SSR integrates two components: a Selective Parallel Module (SPM) that identifies a small set of promising reasoning strategies via model-internal scoring, and Step-level Speculative Decoding (SSD), which enables efficient draft-target collaboration for fine-grained reasoning acceleration. Experiments on three mathematical benchmarks-AIME 2024, MATH-500, and LiveMathBench - demonstrate that SSR achieves strong gains over baselines. For instance, on LiveMathBench, SSR improves pass@1 accuracy by 13.84% while reducing computation to 80.5% of the baseline FLOPs. On MATH-500, SSR reduces compute to only 30% with no loss in accuracy.

cs.LG↗

arXiv2026

Chain-of-Trajectories: Unlocking the Intrinsic Generative Optimality of Diffusion Models via Graph-Theoretic Planning

Diffusion models operate in a reflexive System 1 mode, constrained by a fixed, content-agnostic sampling schedule. This rigidity arises from the curse of state dimensionality, where the combinatorial explosion of possible states in the high-dimensional noise manifold renders explicit trajectory planning intractable and leads to systematic computational misallocation. To address this, we introduce Chain-of-Trajectories (CoTj), a train-free framework enabling System 2 deliberative planning. Central to CoTj is Diffusion DNA, a low-dimensional signature that quantifies per-stage denoising difficulty and serves as a proxy for the high-dimensional state space, allowing us to reformulate sampling as graph planning on a directed acyclic graph. Through a Predict-Plan-Execute paradigm, CoTj dynamically allocates computational effort to the most challenging generative phases. Experiments across multiple generative models demonstrate that CoTj discovers context-aware trajectories, improving output quality and stability while reducing redundant computation. This work establishes a new foundation for resource-aware, planning-based diffusion modeling. The code is available at https://github.com/UnicomAI/CoTj.

cs.LG↗

arXiv2026

Are Dilemmas and Conflicts in LLM Alignment Solvable? A View from Priority Graph

As Large Language Models (LLMs) become more powerful and autonomous, they increasingly face conflicts and dilemmas in many scenarios. We first summarize and taxonomize these diverse conflicts. Then, we model the LLM's preferences to make different choices as a priority graph, where instructions and values are nodes, and the edges represent context-specific priorities determined by the model's output distribution. This graph reveals that a unified stable LLM alignment is very challenging, because the graph is neither static nor necessarily consistent in different contexts. Besides, it also reveals a potential vulnerability: priority hacking, where adversaries can craft deceptive contexts to manipulate the graph and bypass safety alignments. To counter this, we propose a runtime verification mechanism, enabling LLMs to query external sources to ground their context and resist manipulation. While this approach enhances robustness, we also acknowledge that many ethical and value dilemmas are philosophically irreducible, posing a long-term, open challenge for the future of AI alignment.

cs.AI↗

arXiv2026

Discovering an Unquenched Dynamics Mechanism for Charmonium Scattering

In this work, we propose an unquenched mechanism for charmonium scattering that utilizes the internal structure of charmonium. By capturing light flavor quarks and anti-quarks from the vacuum, charm and anti-charm quarks form virtual charmed mesons, which mediate an effective one-boson exchange process. This approach accurately reproduces the di-$J/ψ$ invariant mass spectrum observed by CMS and LHCb, demonstrating its validity. Our mechanism offers a comprehensive framework for understanding charmonium scattering and is applicable to the scattering problems involving all fully heavy hadrons, an area of increasing interest.

hep-ph↗

arXiv2026

Production of high-spin $ω_J/ρ_J$ ($J=2,3,4,5$) mesons in $π^{-}p$ reactions

In this work, we perform a comprehensive investigation of the production of high-spin $ω_J$ and $ρ_J$ mesons ($J=2,3,4,5$) in $π^- p$ reactions using an effective Lagrangian approach. By constructing the relevant $t$-channel processes and calibrating the model with a single adjustable parameter fitted to existing data, we successfully reproduce the measured total and differential cross sections for the $J=3$ states $ω_3(1670)$ and $ρ_3(1690)$. Within the same framework, we predict the production cross sections for their lower- and higher-spin partners: $ω_2(1975)$, $ρ_2(1940)$, $ω_4(2250)$, $ρ_4(2230)$, $ω_5(2350)$, and $ρ_5(2350)$. Our results show that these states exhibit measurable cross sections with characteristically forward-peaked angular distributions, underscoring their strong potential for observation in future $πp$ meson-beam experiments.

hep-ph↗

arXiv2026

ImageEdit-R1: Boosting Multi-Agent Image Editing via Reinforcement Learning

With the rapid advancement of commercial multi-modal models, image editing has garnered significant attention due to its widespread applicability in daily life. Despite impressive progress, existing image editing systems, particularly closed-source or proprietary models, often struggle with complex, indirect, or multi-step user instructions. These limitations hinder their ability to perform nuanced, context-aware edits that align with human intent. In this work, we propose ImageEdit-R1, a multi-agent framework for intelligent image editing that leverages reinforcement learning to coordinate high-level decision-making across a set of specialized, pretrained vision-language and generative agents. Each agent is responsible for distinct capabilities--such as understanding user intent, identifying regions of interest, selecting appropriate editing actions, and synthesizing visual content--while reinforcement learning governs their collaboration to ensure coherent and goal-directed behavior. Unlike existing approaches that rely on monolithic models or hand-crafted pipelines, our method treats image editing as a sequential decision-making problem, enabling dynamic and context-aware editing strategies. Experimental results demonstrate that ImageEdit-R1 consistently outperforms both individual closed-source diffusion models and alternative multi-agent framework baselines across multiple image editing datasets.

cs.CV↗

arXiv2026

Beyond Geometry: Artistic Disparity Synthesis for Immersive 2D-to-3D

Current 2D-to-3D conversion methods achieve geometric accuracy but are artistically deficient, failing to replicate the immersive and emotionally resonant experience of professional 3D cinema. This is because geometric reconstruction paradigms mistake deliberate artistic intent, such as strategic zero-plane shifts for pop-out effects and local depth sculpting, for data noise or ambiguity. This paper argues for a new paradigm: Artistic Disparity Synthesis, shifting the goal from physically accurate disparity estimation to artistically coherent disparity synthesis. We propose Art3D, a preliminary framework exploring this paradigm. Art3D uses a dual-path architecture to decouple global depth parameters (macro-intent) from local artistic effects (visual brushstrokes) and learns from professional 3D film data via indirect supervision. We also introduce a preliminary evaluation method to quantify cinematic alignment. Experiments show our approach demonstrates potential in replicating key local out-of-screen effects and aligning with the global depth styles of cinematic 3D content, laying the groundwork for a new class of artistically-driven conversion tools.

cs.CV↗

arXiv2026

X-Ray Intraday Variability of the Blazar OJ 287 Observed with XMM-Newton

We present X-ray intraday variability, cross-correlated variability, and power spectrum density analysis of the binary black hole blazar candidate OJ 287. The X-ray pointed observations of the source were carried out on eight occasions by the EPIC-pn camera on board the XMM-Newton satellite from November 2005 to November 2022. These good time intervals range between 3.6 hours and 24.1 hours. Three energy bands -- 0.2-2 keV (soft), 2-10 keV (hard), and 0.2-10 keV (total) -- have been used to estimate variability. Low amplitude variations are observed in 4, 5, and 6 light curves in soft, hard, and total energy bands, respectively. Only two observation IDs has shown variation in the all energy bands. The discrete correlation function of the light curves in soft and hard energy bands peaks at zero lag, suggesting that the emission in both bands was cospatial and came from the same population of leptons. Red noise dominates the power spectral densities of variable light curves. According to our flux and spectrum investigations, both particle acceleration and synchrotron cooling mechanisms contribute significantly to the emission from this blazar.

astro-ph.HE↗

arXiv2026

Prospects for observing the missing $2D$ and $1F$ charmonium states around 4 GeV

Our understanding of high-lying states within the charmonium family remains incomplete, particularly in light of recent observations of charmonium states at energies around 4 GeV. In this study, we investigate the spectroscopic properties of several high-lying charmonia, focusing on the $2D$ and $1F$ states. A mass spectrum analysis is conducted, incorporating the unquenched effects. We then present a detailed study of the strong decay properties, including partial decay widths for two-body strong decays permitted by the Okubo-Zweig-Iizuka (OZI) rule. Additionally, we explore the primary radiative decay channels associated with these states. Finally, we discuss the radiative transitions of the $2D$ and $1F$ states via $e^+e^-$ annihilation. Theoretical predictions provided here aim to guide future experimental searches for high-lying charmonium states at facilities such as BESIII, Belle II, LHCb, and the future STCF.

hep-ph↗

arXiv2026

Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod

Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentralized serving. This report presents xDeepServe, the production serving system behind Huawei Cloud's MaaS offering on CloudMatrix384, a 48-server SuperPod with 384 Ascend 910C chips connected by a high-bandwidth UB fabric and global shared memory. It serves models including DeepSeek, Kimi, GLM, Qwen, and MiniMax, among others. xDeepServe is built around Transformerless, a disaggregated execution architecture that decomposes transformer inference into modular units -- attention, feedforward, and MoE -- and supports disaggregated Prefill-Decode and MoE-Attention deployments. To enable disaggregation, we develop XCCL, a memory-semantic communication layer providing microsecond-level point-to-point and scalable all-to-all primitives, and we extend FlowServe with decentralized DP groups and techniques to mitigate stragglers and synchronization variance. In a peak decoding configuration, xDeepServe reaches 2400 tokens/s per Ascend 910C chip at ~50ms time-per-output-token (TPOT).

cs.DC↗

arXiv2026

Janus-Q: End-to-End Event-Driven Trading via Hierarchical-Gated Reward Modeling

Financial market movements are often driven by discrete financial events conveyed through news, whose impacts are heterogeneous, abrupt, and difficult to capture under purely numerical prediction objectives. These limitations have motivated growing interest in using textual information as the primary source of trading signals in learning-based systems. Two key challenges hinder existing approaches: (1) the absence of large-scale, event-centric datasets that jointly model news semantics and statistically grounded market reactions, and (2) the misalignment between language model reasoning and financially valid trading behavior under dynamic market conditions. To address these challenges, we propose Janus-Q, an end-to-end event-driven trading framework that elevates financial news events from auxiliary signals to primary decision units. Janus-Q unifies event-centric data construction and model optimization under a two-stage paradigm. Stage I focuses on event-centric data construction, building a large-scale financial news event dataset comprising 62,400 articles annotated with 10 fine-grained event types, associated stocks, sentiment labels, and event-driven cumulative abnormal return (CAR). Stage II performs decision-oriented fine-tuning, combining supervised learning with reinforcement learning guided by a Hierarchical Gated Reward Model (HGRM), which explicitly captures trade-offs among multiple trading objectives. Extensive experiments demonstrate that Janus-Q achieves more consistent, interpretable, and profitable trading decisions than market indices and LLM baselines, improving the Sharpe Ratio by up to 102.0% while increasing direction accuracy by over 17.5% compared to the strongest competing strategies.

cs.CL↗

arXiv2026

SMMAN: quasi-Simultaneous Multi-wavelength Monitoring of gamma-ray-loud AGNs with the Nanshan 26-m radio telescope

Active Galactic Nuclei (AGNs) are characterized by strong temporal flux density variability across the electromagnetic spectrum, offering insights into the complex physical processes governing accretion and plasma outflows. To systematically investigate AGNs flux density variability in radio bands, a long-term program was initiated in late 2016: quasi-Simultaneous Multiwavelength Monitoring of gamma-ray-loud AGNs with the Nanshan 26-m radio telescope (SMMAN). This work presents the first data release of the SMMAN program, spanning over eight years from 2016 to 2024 with observations at 4.8 and 23.6 GHz. The SMMAN sample includes 131 northern ($δ>\sim0^{\circ}$) sources selected from the Fermi Large Area Telescope third source catalog. The characteristics of variability, spectral index, luminosity, and $γ$-ray loudness factor are examined for different AGN classes within the sample. Target sources exhibit stronger variability at 23.6 GHz compared to 4.8 GHz, with BL Lac objects being more variable than flat-spectrum radio quasars (FSRQs). BL Lacs generally have flatter radio spectra, while FSRQs, blazar candidates of uncertain type (BCUs), and radio galaxies (RDGs) span a wider range from flat to steep. FSRQs are more radio-luminous than BL Lacs and other classes, with BCUs intermediate and RDGs generally fainter. FSRQs and BL Lacs have higher $γ$-ray loudness factors than RDGs, while BCUs have intermediate values. The SMMAN dataset, incorporated with other historical and ongoing monitoring programs, will provide a unique opportunity to investigate the evolution of spectral energy distributions, search for quasi-periodic oscillations, and analyze supermassive black hole binary systems.

astro-ph.GA↗

arXiv2026

Producing $Λ(1405)$ and $Λ(1520)$ in $π^-p$ reaction to explore their inner structures

In this work, the production mechanisms of the hyperon resonances $Λ(1405)$ and $Λ(1520)$ in the $π^- p$ scattering are investigated within an effective Lagrangian approach incorporating Regge trajectories. By including contributions from $t$-channel $K^*$ and $u$-channel $Σ$ exchanges, we perform global fits to the total and differential cross sections for $π^{-} p \rightarrow KΛ(1405)$ and $π^{-} p \rightarrow KΛ(1520)$. The results show good agreement with available experimental data. For the total cross section of $Λ(1405)$ production, the $u$-channel contribution is dominant, whereas the $t$-channel contribution plays the primary role in $Λ(1520)$ production. Furthermore, the differential cross sections of the two processes exhibit distinctly different shapes, reflecting their distinct underlying reaction mechanisms. An analysis based on the constituent counting rule indicates that $Λ(1520)$ is consistent with a conventional three-quark configuration, while $Λ(1405)$ shows a clear deviation, suggesting a more exotic structure. Owing to the large branching ratio of $Λ^* \to πΣ$, the Dalitz process $π^{-} p \rightarrow K Λ^{*} \rightarrow K πΣ$ is also calculated. Our results demonstrate that reconstructing $Λ^*$ via the $KπΣ$ final state is experimentally feasible. This study provides important theoretical insights into the production dynamics of these hyperon resonances, and suggests future high-precision measurements of the $t$-distribution at large momentum transfer at facilities such as AMBER, J-PARC, HIKE, and HIAF, which can further clarify their reaction mechanisms and structural properties.

nucl-th↗