arXiv subjects

Xuejie Liu

Publications and source records attributed to Xuejie Liu.

At least 19 recordsLinked to original sources

arXiv2026

Investigation of fully heavy tetraquark within chiral quark model

In the framework of the Chiral quark model (ChQM), we investigate the fully charmed and fully bottomed tetraquark with $J^{PC}=2^{++}$ including two structures: $Q\bar{Q}-Q\bar{Q}$ and $QQ-\bar{Q}\bar{Q}$. The bound-state calculation shows that there is no bound state in either $cc\bar{c}\bar{c}$ or $bb\bar{b}\bar{b}$ systems. However, by using the real-scaling method, some resonance states are obtained. For the $cc\bar{c}\bar{c}$ system, when the channel-coupling includes only three $S$-wave channels, two resonant states are obtained: one with a mass around $7002$ MeV and decay width near $54$ MeV, and another with a mass around $7227$ MeV and a decay width near $66$ MeV. The former can be regarded as a candidate for the $X(6900)$, and the latter can be considered as a candidate for the $X(7200)$. Upon adding the $χ_{c0}χ_{c2}$, $χ_{c1}χ_{c1}$, $χ_{c1}χ_{c2}$, $χ_{c2}χ_{c2}$ channels, both resonant states still remain. For the $bb\bar{b}\bar{b}$ system, only one resonant state is obtained, regardless of whether the four channels composition of the excited mesons are included or excluded. The mass and width of this resonant state are around $19743$ MeV and $67$ MeV, respectively. We suggest that future experiments search for the possible resonance state in the invariant mass spectrum of $ΥΥ$ or $ΥΥ(2S)$.

hep-ph↗

arXiv2026

Agentic AI for ISAC: Analysis, Framework, and Case Study

Integrated sensing and communication (ISAC) has emerged as a key development direction in the sixth-generation (6G) era, which provides essential support for the collaborative sensing and communication of future intelligent networks. However, as wireless environments become increasingly dynamic and complex, ISAC systems require more intelligent processing and more autonomous operation to maintain efficiency and adaptability. Meanwhile, agentic artificial intelligence (AI) offers a feasible solution to address these challenges by enabling continuous perception-reasoning-action loops in dynamic environments to support intelligent, autonomous, and efficient operation for ISAC systems. As such, we delve into the application value and prospects of agentic AI in ISAC systems in this work. Firstly, we provide a comprehensive review of agentic AI and ISAC systems to demonstrate their key characteristics. Secondly, we show several common optimization approaches for ISAC systems and highlight the significant advantages of generative artificial intelligence (GenAI)-based agentic AI. Thirdly, we propose a novel agentic ISAC framework and prensent a case study to verify its superiority in optimizing ISAC performance. Finally, we clarify future research directions for agentic AI-based ISAC systems.

cs.AI↗

arXiv2026

The Expressivity Boundary of Probabilistic Circuits: A Comparison with Large Language Models

Probabilistic Circuits (PCs) are deep generative models that support exact and efficient probabilistic inference. Yet in autoregressive language modeling, PCs still lag behind Transformer-based large language models (LLMs), suggesting an important expressivity gap. In this work, we compare PCs and LLMs under a unified autoregressive formulation. First, an output bottleneck: PCs parameterize predictions as convex combinations in probability space, which struggles to represent the sharp distributions typical of language; adopting a logit-space parameterization substantially narrows this gap. Second, a context-encoding bottleneck: we prove that structured-decomposable PCs can match Transformer separation rank on vtree-aligned partitions, but show, both theoretically and empirically, that this capacity is limited to partitions aligned with the fixed routing structure, leading to severe degradation when the data exhibits heterogeneous dependency topologies. We further prove that decomposable PCs are strictly more expressive than structured-decomposable ones, though effectively optimizing them remains an open challenge.

cs.LG↗

arXiv2026

Spectroscopy and femtoscopic correlation function of the $B\bar{D}$, $B=(N, Δ)$ system in quark delocalization color screening model

In this work, we systematically investigate the pentaquark systems with quark contents $qqqq\bar{c}$ with the analyzed total spin and parity quantum numbers of $J^{P}=\frac{1}{2}^{-}$, $J^{P}=\frac{3}{2}^{-}$ and $J^{P}=\frac{5}{2}^{-}$, in the I=0, I=1 and I=2 isospin channels. The effective potentials between baryon and meson clusters are given, and the possible bound states are also investigated. Also, the study of the scattering process of the open channels is performed to identify possible resonance states. Our estimations indicate that several possible bound states and narrow baryon-meson resonances are found from corresponding the calculation processes. Furthermore, to bridge the gap between theoretical predictions and experimental measurement, we also extract the low-energy scattering parameters and compute the femtoscopic correlation functions for the $N\bar{D}$ system using the CATS framework. The results demonstrate that the predicted $I=0$ bound state manifests as a significant enhancement at low momentum accompanied by a characteristic suppression. In contrast, the $I=1$ correlations remain relatively flat as the predicted resonances are kinematically distant from the threshold. The $I=2$ sector exhibits strong spin dependence, where the bound state signal in the $J=1/2^{-}$ channel is largely masked by repulsive components in spin-averaged observables. This cancellation effect suggests that future experimental searches at ALICE and LHCb may require spin-selective measurements to identify such states. These predictions provide crucial theoretical guidance for future experiments.

hep-ph↗

arXiv2026

Lookahead Path Likelihood Optimization for Diffusion LLMs

Diffusion Large Language Models (dLLMs) support arbitrary-order generation, yet their inference performance critically depends on the unmasking order. Existing strategies rely on heuristics that greedily optimize local confidence, offering limited guidance for identifying unmasking paths that are globally consistent and accurate. To bridge this gap, we introduce path log-likelihood (Path LL), a trajectory-conditioned objective that strongly correlates with downstream accuracy and enables principled selection of unmasking paths. To optimize Path LL at inference time, we propose POKE, an efficient value estimator that predicts the expected future Path LL of a partial decoding trajectory. We then integrate this lookahead signal into POKE-SMC, a Sequential Monte Carlo-based search framework for dynamically identifying optimal unmasking paths. Extensive experiments across 6 reasoning tasks show that POKE-SMC consistently improves accuracy, achieving 2%--3% average gains over strong decoding-time scaling baselines at comparable inference overhead on LLaDA models and advancing the accuracy--compute Pareto frontier.

cs.LG↗

arXiv2025

Dynamical study of hidden-strange pentaquarks as analogs of the hidden-charm states

Motivated by the recent BESIII experiment~\cite{BESIII:2024muk} searching for hidden-strange exotic hadrons, we perform a systematic theoretical study of the hidden-strange pentaquark system within the framework of the quark delocalization color screening model (QDCSM) and the resonating group method (RGM). Our results demonstrate that the channel coupling effect plays a decisive role in the formation of bound and resonance states. It not only significantly enhances the short-range attraction but also induces essential attractive contributions from pion exchange. We predict three bound states with masses of $1759$ MeV, $2000$ MeV, and $2407$ MeV. Furthermore, we report the existence of a hidden-strange pentaquark resonance state, $ΞK^{\ast}$, with quantum numbers $I(J^{P})=0(1/2^{-})$. This resonance is identified in the $S$-wave scattering phase shifts of the $Λη_{s}$ and $Λϕ$ open channels, with a predicted mass in the range of $2204\text{--}2208$ MeV. By accounting for both the scattering width from channel coupling and the intrinsic decay width of the constituent $K^{\ast}$, the total decay width is estimated to be $55\text{--}63$ MeV. These theoretical predictions provide important guidance for future experimental searches for such exotic states at facilities like BESIII.

hep-ph↗

arXiv2025

Investigation of Resonances in the $Σ({1/2}^{-})$ System Based on the Chiral Quark Model

In this work, we investigate the resonance structures in the $Σ(1/2^-)$ system from both three-quark and five-quark perspectives within the framework of the chiral quark model. An accurate few-body computational approach, the Gaussian Expansion Method, is employed to construct the orbital wave functions of multiquark states. To reduce the model dependence on parameters, we fit two sets of parameters to check the stability of the results. The calculations show that our results remain stable despite changes in the parameters. In the three-quark calculations, two $Σ(1/2^-)$ states are obtained with energies around 1.8~GeV, which are good candidates for the experimentally observed $Σ(1750)$ and $Σ(1900)$. In the five-quark configuration, several stable resonance states are identified, including $Σπ$, $N \bar{K}$, and $N \bar{K}^{*}$. These resonance states survive the channel-coupling calculations under the complex-scaling framework and manifest as stable structures. Our results support the existence of a two-pole structure for the $Σ(1/2^-)$ system, predominantly composed of $Σπ$ and $N \bar{K}$ configurations, analogous to the well-known $Λ(1380)$-$Λ(1405)$ ($Σπ$-$N \bar{K}$) system. On the other hand, although the energy of the $N \bar{K}^{*}$ configuration is close to that of $Σ(1750)$ and $Σ(1900)$, the obtained width is not consistent with the experimental values. This suggests that the $N \bar{K}^{*}$ state needs to mix with three-quark components to better explain the experimental $Σ(1750)$ and $Σ(1900)$ states. According to our decay width calculations, the predicted two resonance states are primarily composed of $Σπ$ and $N \bar{K}$, with their main decay channel being $Λπ$.

hep-ph↗

arXiv2025

Generative Artificial Intelligence for Beamforming in Low-Altitude Economy

The growth of low-altitude economy (LAE) has driven a rising demand for efficient and secure communication. However, conventional beamforming optimization techniques struggle in the complex LAE environments. In this context, generative artificial intelligence (GenAI) methods provide a promising solution. In this article, we first introduce the core concepts of LAE and the roles of beamforming in advanced communication technologies for LAE. We then examine their interrelation, followed by an analysis of the limitations of conventional beamforming methods. Next, we provide an overview of how GenAI methods enhance the process of beamforming, with a focus on its applications in LAE. Furthermore, we present a case study using a generative diffusion model (GDM)-based algorithm to enhance the performance of aerial collaborative beamforming-enabled remote secure communications in LAE and simulation results verified the effectiveness of the proposed algorithms. Finally, promising research opportunities are identified.

cs.NI↗

arXiv2025

Energy Efficient Trajectory Control and Resource Allocation in Multi-UAV-assisted MEC via Deep Reinforcement Learning

Mobile edge computing (MEC) is a promising technique to improve the computational capacity of smart devices (SDs) in Internet of Things (IoT). However, the performance of MEC is restricted due to its fixed location and limited service scope. Hence, we investigate an unmanned aerial vehicle (UAV)-assisted MEC system, where multiple UAVs are dispatched and each UAV can simultaneously provide computing service for multiple SDs. To improve the performance of system, we formulated a UAV-based trajectory control and resource allocation multi-objective optimization problem (TCRAMOP) to simultaneously maximize the offloading number of UAVs and minimize total offloading delay and total energy consumption of UAVs by optimizing the flight paths of UAVs as well as the computing resource allocated to served SDs. Then, consider that the solution of TCRAMOP requires continuous decision-making and the system is dynamic, we propose an enhanced deep reinforcement learning (DRL) algorithm, namely, distributed proximal policy optimization with imitation learning (DPPOIL). This algorithm incorporates the generative adversarial imitation learning technique to improve the policy performance. Simulation results demonstrate the effectiveness of our proposed DPPOIL and prove that the learned strategy of DPPOIL is better compared with other baseline methods.

cs.NI↗

arXiv2025

$Υ(5S)$ in the unquenched quark model

The observation of the $Υ(10753)$ state by Belle II Collaboration has sparked significant interest in the theoretical understanding of such states within the context of hadron physics. Considering the similar mass and the decay with, as well as the same quantum numbers $J^{PC}=1^{--}$ with the $Υ(10860)$ state, which is referred to be the $Υ(5S)$ in PDG, in this work, we try to calculate the mass of the $Υ(5S)$ state. The model used to predict the high-energy spectrum of these states generally involves a constituent quark model, which can describe a variety of properties of hadrons containing heavy quarks. In the framework of the unquenched quark model, a coupled-channel calculation is employed to explore the effect of open-bottom meson-meson thresholds on the $Υ(10860)$ state. The hypothesis is that coupled-channel effects could be large enough to create new dynamically generated states, thus potentially explaining the nature of the $Υ(10860)$ state, as well as whether the $Υ(10860)$ and $Υ(10753)$ is the same state. The results indicate that unquenched effects play a crucial role in explaining the $Υ(10860)$ state, providing a plausible mechanism for its formation. Besides in our calculations, the $Υ(10860)$ and $Υ(10753)$ may be two different states.

hep-ph↗

arXiv2025

Tractable Transformers for Flexible Conditional Generation

Non-autoregressive (NAR) generative models are valuable because they can handle diverse conditional generation tasks in a more principled way than their autoregressive (AR) counterparts, which are constrained by sequential dependency requirements. Recent advancements in NAR models, such as diffusion language models, have demonstrated superior performance in unconditional generation compared to AR models (e.g., GPTs) of similar sizes. However, such improvements do not always lead to improved conditional generation performance. We show that a key reason for this gap is the difficulty in generalizing to conditional probability queries (i.e., the set of unknown variables) unseen during training. As a result, strong unconditional generation performance does not guarantee high-quality conditional generation. This paper proposes Tractable Transformers (Tracformer), a Transformer-based generative model that is more robust to different conditional generation tasks. Unlike existing models that rely solely on global contextual features derived from full inputs, Tracformers incorporate a sparse Transformer encoder to capture both local and global contextual information. This information is routed through a decoder for conditional generation. Empirical results demonstrate that Tracformers achieve state-of-the-art conditional generation performance on text modeling compared to recent diffusion and AR model baselines.

cs.CL↗

arXiv2025

Plug-and-Play Context Feature Reuse for Efficient Masked Generation

Masked generative models (MGMs) have emerged as a powerful framework for image synthesis, combining parallel decoding with strong bidirectional context modeling. However, generating high-quality samples typically requires many iterative decoding steps, resulting in high inference costs. A straightforward way to speed up generation is by decoding more tokens in each step, thereby reducing the total number of steps. However, when many tokens are decoded simultaneously, the model can only estimate the univariate marginal distributions independently, failing to capture the dependency among them. As a result, reducing the number of steps significantly compromises generation fidelity. In this work, we introduce ReCAP (Reused Context-Aware Prediction), a plug-and-play module that accelerates inference in MGMs by constructing low-cost steps via reusing feature embeddings from previously decoded context tokens. ReCAP interleaves standard full evaluations with lightweight steps that cache and reuse context features, substantially reducing computation while preserving the benefits of fine-grained, iterative generation. We demonstrate its effectiveness on top of three representative MGMs (MaskGIT, MAGE, and MAR), including both discrete and continuous token spaces and covering diverse architectural designs. In particular, on ImageNet256 class-conditional generation, ReCAP achieves up to 2.4x faster inference than the base model with minimal performance drop, and consistently delivers better efficiency-fidelity trade-offs under various generation settings.

cs.CV↗

arXiv2025

Exploring the spectroscopic features of double-strangeness tetraquark states

Since the discovery of the $T_{cc}$ double-charm tetaquark by the LHCb collaboration, the field of the theoretical research on heavy quarks has advanced rapidly, with increasing interest in exploring the light quark sector. In this study, the quark model is employed to systematically analyze the double-strange tetraquark system. Both the meson-meson configuration and diquark-antidiquark configuration are considered. The interactions between hadron pairs under various quantum numbers, as well as the possibilities of bound states and resonances, are evaluated. The results indicate the presence of two bound states, $ \bar{K}^{\ast }\bar{K}$ and $\bar{K}^{\ast }\bar{K}^{\ast}$, with quantum number $I(J^{P})=0(1^{+})$ in single-channel estimations. Additionally, by considering the channel coupling between the two configurations, a bound state with quantum numbers $I(J^{P})=0(1^{+})$ and a mass of approximately $1310$ MeV is obtained. Moreover, through the application of Resonance Ground Method, a resonance state is identified in the $I(J^{P})=0(1^{+})$ $\ssqq$ system, with an estimated mass of around 1783 MeV and a decay width of approximately 17 MeV.

hep-ph↗

arXiv2025

A study on the properties of hidden-charm pentaquarks with double strangeness

Motivated by the LHCb observations of $P_c$ and $P_{cs}$ states, we systematically investigate the hidden-charm double-strange pentaquark system ($nssc\bar{c}$) using the resonating group method within the quark delocalization color screening model (QDCSM). By dynamically incorporating channel coupling effects, five resonance states are identified with $J^P = 1/2^-$ and $3/2^-$. Their masses, widths, and dominant decay channels are predicted, providing critical guidance for future experimental searches.

hep-ph↗

arXiv2025

Study of the $c\bar{c}s\bar{s}$ system in the chiral quark model

Recently, a charmonium $X(3960)$ in $B$ decays in the $D_s^+D_s^-$ invariant-mass spectrum is discovered by the LHCb Collaboration with the quantum number $J^{PC}=0^{++}$. Motivated by the discovery, in this work, we systematically investigated the $c\bar{c}s\bar{s}$ tetraquark states with the quantum numbers $J^{PC}=0^{++}, 1^{++}, 1^{+-}, 2^{++}$ in the framework of the chiral quark model(CQM). In our calculations, we considered the meson-meson structure of the tetraquark states and the diquark-antidiquark structure, as well as the channel-coupling of all channels of these two configurations are considered in this work. For example, all color structures including color singlet, hidden color channel, and the mixing of them are also taken into account. The numerical results indicates that no bound states were found in our model. But there exist several resonant states by using the stabilization method, the real scaling method (RSM) so called. Among these states, the $0^{++}$ resonant state with mass 3927 MeV matches very well with the energy of the newly discovered exotic state $X(3960)$ reported by the LHCb collaboration. As a result, our calculations suggest that $X(3960)$ can be interpreted as a $c\bar{c}s\bar{s}$ tetraquark state with quantum number $J^{PC}=0^{++}$. Apart form that, we also find several resonance states with mass 4179 MeV, 4376 MeV with $0^{++}$. For $1^{++}$, there is likely one resonance state in the energy range of 4310$\sim$4336 MeV, along with two resonance states at the energy of 4395 MeV and 4687 MeV, respectively. Besides, two resonance states at 4300 MeV and 4355 MeV for $1^{+-}$, as well as one state at 4788 MeV for $2^{++}$, are found, which are likely to be new exotic states. More experimental data is needed to confirm the existence of these resonance states.

hep-ph↗

arXiv2025

A Tractable Inference Perspective of Offline RL

A popular paradigm for offline Reinforcement Learning (RL) tasks is to first fit the offline trajectories to a sequence model, and then prompt the model for actions that lead to high expected return. In addition to obtaining accurate sequence models, this paper highlights that tractability, the ability to exactly and efficiently answer various probabilistic queries, plays an important role in offline RL. Specifically, due to the fundamental stochasticity from the offline data-collection policies and the environment dynamics, highly non-trivial conditional/constrained generation is required to elicit rewarding actions. it is still possible to approximate such queries, we observe that such crude estimates significantly undermine the benefits brought by expressive sequence models. To overcome this problem, this paper proposes Trifle (Tractable Inference for Offline RL), which leverages modern Tractable Probabilistic Models (TPMs) to bridge the gap between good sequence models and high expected returns at evaluation time. Empirically, Trifle achieves the most state-of-the-art scores in 9 Gym-MuJoCo benchmarks against strong baselines. Further, owing to its tractability, Trifle significantly outperforms prior approaches in stochastic environments and safe RL tasks (e.g. with action constraints) with minimum algorithmic modifications.

cs.LG↗

arXiv2024

OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents

This paper presents OmniJARVIS, a novel Vision-Language-Action (VLA) model for open-world instruction-following agents in Minecraft. Compared to prior works that either emit textual goals to separate controllers or produce the control command directly, OmniJARVIS seeks a different path to ensure both strong reasoning and efficient decision-making capabilities via unified tokenization of multimodal interaction data. First, we introduce a self-supervised approach to learn a behavior encoder that produces discretized tokens for behavior trajectories $τ= \{o_0, a_0, \dots\}$ and an imitation learning policy decoder conditioned on these tokens. These additional behavior tokens will be augmented to the vocabulary of pretrained Multimodal Language Models. With this encoder, we then pack long-term multimodal interactions involving task instructions, memories, thoughts, observations, textual responses, behavior trajectories, etc into unified token sequences and model them with autoregressive transformers. Thanks to the semantically meaningful behavior tokens, the resulting VLA model, OmniJARVIS, can reason (by producing chain-of-thoughts), plan, answer questions, and act (by producing behavior tokens for the imitation learning policy decoder). OmniJARVIS demonstrates excellent performances on a comprehensive collection of atomic, programmatic, and open-ended tasks in open-world Minecraft. Our analysis further unveils the crucial design principles in interaction data formation, unified tokenization, and its scaling potentials. The dataset, models, and code will be released at https://craftjarvis.org/OmniJARVIS.

cs.LG↗

arXiv2024

Probing the nature of the anticharmed-strange pentaquark states: mass spectra, decays, and magnetic moments

Within the framework of the quark delocalization color screening model, a systematic investigation of the anticharmed-strange pentaquark system is performed using the resonance group method. The currently estimations predict three bound states with estimated masses to be 2886 MeV, 3039 MeV, and 3153 MeV, respectively. Additionally, three resonance states are identified in various scattering phase shifts processes. Among them, two resonance states $ΣD$ and $Σ^{\ast}D^{\ast}$ with quantum number $\frac{1}{2}(\frac{1}{2}^{-})$ are detected in channels $ND_{s}^{\ast}$ and $ND$, and $ΣD^{\ast}$ and $ΛD$, with masses and decay widths of ($M_{R}=3053\sim3055$ MeV, $T_{total}=13.0\sim13.4$ MeV) and ($M_{R}=3389\sim3390$ MeV, $T_{total}=10.4$ MeV), respectively. In the $ΛD^{\ast}$ and $ΣD^{\ast}$ channels, a resonance state with quantum number $\frac{1}{2}(\frac{3}{2}^{-})$ is discovered, with its mass and decay width being $3250\sim3252$ MeV and 4.4 MeV, respectively. These predicted pentaquark states have $\bar{c}snnn$ quark compositions, allowing them to be recognized as genuine pentaquark states. To validate these predictions, it is expected that upcoming experiments will further explore the predicted resonance and bound states in these possible decay channels.

hep-ph↗