arXiv subjects

Gang Wu

Publications and source records attributed to Gang Wu.

At least 19 recordsLinked to original sources

arXiv2026

Fluid Antenna Systems for ISAC Design: A Survey

Fluid antenna systems (FAS) introduce dynamic positional degrees of freedom (DoFs), extending the spatial domain from a static and discrete resource to a quasi-continuous and reconfigurable design space. This spatial flexibility provides an effective means of alleviating the geometric rigidity and functional conflicts that constrain integrated sensing and communication (ISAC) systems. Against this backdrop, we provide a comprehensive overview of FAS-enabled ISAC, tracing the evolution from theoretical performance limits to practical transceiver architectures. To illustrate the surveyed design evolution, we further propose the fluid antenna multi-mode modulation (FA-MM) framework as a representative case study of multidimensional physical-layer design for FAS-ISAC. Finally, several open challenges are discussed, with emphasis on predictive sensing, adaptive coordination, and secure spatial-state management in future FAS-ISAC systems.

eess.SP↗

arXiv2026

Integrated Sensing and Communication via Channel Knowledge Maps Built from Beam Feedback Coefficients

Channel knowledge maps (CKMs) support wireless localization by linking channel features to user locations. Detailed channel fingerprints, however, can require substantial storage. This paper proposes a CKM-based localization framework that uses beam feedback coefficients collected during communication. These coefficients serve as compact location fingerprints within the beam management process, without requiring full channel feedback or additional sensing measurements. Using a coarse position prior, the base station searches nearby CKM entries and refines the location estimate through local interpolation. We analyze the relationship between spatial fingerprint variation and localization accuracy, and evaluate the effect of feedback quantization. Simulations show favorable storage--accuracy trade-offs relative to dense and sparsified spectral fingerprinting in the tested multipath environments.

eess.SP↗

arXiv2026

Randomized Krylov Subspace Methods for Shifted Linear Systems

We propose several novel Krylov subspace algorithms termed shifted randomized GMRES (RandGMRES-Sh), shifted randomized FOM (RandFOM-Sh), shifted randomized GMRES with deflated restarting (RandGMRES-Sh-DR), and shifted randomized FOM with deflated restarting (RandFOM-Sh-DR), for solving shifted linear systems. These methods are designed to significantly reduce the computational overhead of orthogonal basis generation while preserving orthogonality under specific conditions. Besides, this unified framework makes it possible to solve all shifted linear systems at the same time by using a single shared basis. These new approaches combine multiple advanced techniques together effectively, such as randomized sketching, the control of collinear residual directions, and deflated restarting methods. Compared with the standard versions of traditional algorithms, the new algorithms show a steady but moderate improvement in convergence speed. Furthermore, we theoretically prove that although GMRES and sketched GMRES have different algorithmic solution steps, their iterates are all confined to and together span the same basic Krylov subspace. We also work out the theoretical relationship between the solutions produced by RandGMRES-Sh and RandFOM-Sh at the same iteration step before the first restart. Moreover, we strictly prove how the solutions of RandGMRES-Sh and RandFOM-Sh are related to those of their traditional versions, GMRES-Sh and FOM-Sh, respectively.

math.NA↗

arXiv2026

The ALMA-QUARKS Survey: Discovery of Superfine Dusty Fibrils inside Massive Star-forming Clumps

We report the discovery of more than 320 superfine dusty filamentary structures (fibrils) inside 121 massive star forming clumps that are located in widely different Galactic environments (Galactocentric distances of ~1.2 - 12.9 kpc). These fibrils are identified from the 1.3-mm continuum emission in the ALMA-QUARKS survey, which has a linear resolution of ~900 AU for a source at ~3 kpc. The typical width of these fibrils identified in clumps is found to be ~0.01 pc, which is about ten times narrower than that of dusty filaments in nearby clouds identified by the Herschel Space Observatory. The mass (M) versus length (l) relation for these fibrils follows M ~ l^2, similar to that of Galactic filaments identified in space (e.g., Herschel) and ground-based single-dish (e.g., APEX) surveys. However, these fibrils in the ALMA-QUARKS survey are significantly denser (N_{H_2} = 10^{23} - 10^{24} cm^{-2}) than the filaments found in previous Herschel surveys (N_{H_2} = 10^{20} - 10^{23} cm^{-2}). This work contributes a large sample of newly found superfine fibrils in massive clumps, following the identification of large 0.1 pc-wide filaments and associated internal velocity coherent molecular fibers in nearby molecular clouds, further emphasizing the crucial role played by filamentary structures in star formation at various physical scales.

astro-ph.GA↗

arXiv2026

Evolving Intelligent Complex Systems via Intellicise Networks: Architecture, Technologies, and Pathways

Future engineering infrastructures are evolving into large-scale, open, heterogeneous, and wirelessly interconnected complex systems. These systems present significant challenges in optimizing network resource utilization, managing high-dimensional information spaces, and accommodating diverse business requirements. Intellicise networks, characterized by Intent-driven operation, semantic-native capability, and distributed intelligence, offer a promising paradigm for enabling such intelligent complex systems. We provide a systematic exploration of future intelligent complex systems from the perspective of intellicise networks. Specifically, we propose a cross-domain intelligent communication network architecture based on intellicise networks, grounded in information theory, systems theory, game theory, and cybernetics. The architecture comprises a cross-layer organizational framework, multi-functional planes, and novel information flows. The cross-layer framework defines the vertical evolution from perception and cognition to decision, while the control, user, data, computation, intelligence, and security planes deliver horizontal intellicise capabilities. Moreover, data, knowledge, model, and task flows interconnect the various layers and planes, forming a closed-loop process that derives simplicity from high-level intelligene while concurrently pursuing enhanced. Building on this architecture, we review key enabling technologies, tracing their evolution from semantic extraction to intent understanding, from heterogeneous resource integration to self-configuration and self-optimization, from generative artificial intelligence (AI) to agentic AI, and from embodied AI to symbodied AI. Additionally, we present a case study on intellicise networks for embodied agent communications and discuss representative applications and services for intelligent complex systems.

eess.SP↗

arXiv2026

SkillMarker: A KGW-Based Watermarking Method for Agent Skill Ownership Verification

Agent skills encode operational procedures and domain expertise as reusable knowledge assets, yet their distribution in plaintext exposes them to unauthorized copying and leakage. However, practical mechanisms for skill ownership verification and leakage tracing remain underdeveloped. Watermark embedding before distribution offers a potential solution, but structured, compact skill instructions impose stringent requirements for factual and procedural accuracy. To address these challenges, we introduce SkillMarker, a KGW-based watermarking method that jointly targets functionality preservation and strong watermark embedding. SkillMarker unifies quality-constrained rewriting with signal-oriented candidate search. The former separates essential knowledge from flexible expression to preserve instruction fidelity; the latter explores alternative expressions to obtain a stronger watermark signal under preservation constraints. We release an open-source toolkit that integrates watermark embedding, quality auditing, and detection to support the protection of agent skills. SkillMarker targets ownership verification and leakage tracing in distributed skill ecosystems, where content may be copied in whole or in part, or incorporated into other skills. Across four datasets, SkillMarker negligibly affects downstream task performance on average. In our copy-paste tests, window-based detection consistently identifies copied passages containing as few as 1,536 consecutive tokens. Even after merging with one or three background skills, SkillMarker retains watermark detection rates of 72.2--77.8\%.

cs.CR↗

arXiv2026

ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding

For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task must be carried out-modification scope, workflow order, validation, tool use, and reporting. This capability, which we call engineering constraint following, remains largely invisible to current evaluations. We introduce ANCHOR (Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding), a benchmark built on naturalistic, multilingual repository tasks spanning eight language groups. ANCHOR combines (i) a hierarchical taxonomy of 10 categories and 78 leaf types distilled from real developer interactions, (ii) an automated pipeline that instantiates task-grounded atomic constraints and composes them into typed AND/THEN/PRIORITY relations, and (iii) a trajectory-grounded evaluation framework that checks both the code diff and the execution trajectory with rule-based and LLM judges. Across 19 agent configurations spanning 2 scaffolds and 10 foundation models on 358 tasks, the strongest measured system, Claude Opus 4.8 under Cline, reaches 70.1% atomic compliance and 63.7% relation compliance, while 19.0% of tasks pass every scored checklist item under the strict all-item FCCR criterion. A five-engineer audit of constraints from 50 instances reports 94% feasibility, 94% repository consistency, and 96% realism. In the primary paired set (14 configurations), the mean signed change in task completion after adding constraints is +0.7 percentage points; individual changes vary in both directions. These results distinguish functional success from constraint compliance, with failures concentrated in workflow ordering, tool-use discipline, and reporting, and substantial interactions between models and scaffolds.

cs.CL↗

arXiv2026

On Convergence Behavior of Randomized Kaczmarz-type Methods for Solving Doubly Noisy Linear Systems

In this paper, we consider the convergence of some popular Kaczmarz-type methods, including the randomized Kaczmarz (RK) method, the randomized extended Kaczmarz (REK) method, the randomized block Kaczmarz (RBK) method, and the randomized double block Kaczmarz (RDBK) method for doubly noisy linear system. To the best of our knowledge, this is the first work that considers and compares the convergence of the Kaczmarz-type methods for consistent linear systems, as well as that for inconsistent linear systems to solve double noisy linear system. We prove that these methods converge to a neighborhood of the smallest norm least squares solution of the underlying noiseless system. Specifically, RK and RBK that are designed for consistent linear systems, often outperform REK and RDBK that are designed for inconsistent linear systems, respectively, in terms of the convergence rate or the convergence horizon. Moreover, we establish the convergence of the more general sketch-and-project framework for the doubly noisy linear system. The analysis provides more comprehensive results without imposing any additional restrictions. Numerical experiments are performed to validate our theoretical results.

math.NA↗

arXiv2026

PTC-Decoder: Towards Intelligent SLMs on Offline Resource-Constrained Edge Devices

Deploying small language models (SLMs) on offline, resource-constrained edge devices such as remote sensing satellites presents a fundamental challenge: their limited reasoning capacity hinders reliable execution of multi-step agent tasks requiring complex tool orchestration. Existing plan-solve paradigms rely on prompt-based enforcement, which our experiments show SLMs almost entirely disregard: weak models fail to invoke the plan. We propose PTC-Decoder (Plan-Tool Constrained Decoder), a training-free, plug-and-play decoder framework that combines (1) a Plan-to-Act paradigm, which elevates planning to an atomic tool and forces its invocation at the first inference step, and (2) TC-Decoder, a deterministic finite automaton that imposes token-level hard constraints on tool names while preserving freedom over parameter generation, thereby retaining SLM reasoning capability. Evaluated on 200 real remote-sensing satellite tasks across 7 SLMs, PTC-Decoder yields a statistically significant mean overall score gain of +1.21 (p<0.01), 95% CI [+1.13, +1.29]), with consistent improvements across models and other datasets. An ablation study that removes TC-Decoder causes substantial performance degradation across all quality metrics without reducing computational cost, confirming TC-Decoder as the primary driver. PTC-Decoder thus offers a lightweight yet effective solution for improving step-level reliability, with final-answer accuracy remaining an open challenge. In essence, we enforce plan adherence by constraining the permissible output vocabulary during inference, without requiring retraining.

cs.AI↗

arXiv2026

FLARE: A Full-Lifecycle Dense Supervision Paradigm for Long-Horizon Coding Agents via Generative Reward Model

While test-time scaling enhances Large Language Model (LLM) agents in long-horizon software engineering (SWE), sparse binary rewards (Pass/Fail) create a severe credit assignment crisis and waste failed exploratory trajectories. Current trajectory optimization and scaling methods are costly and structurally limited, relying on heuristic state reuse without causal diagnosis or delayed scalar scoring without actionable online guidance. We propose FLARE (Full-Lifecycle Alignment and Reward Engine), a novel dense supervision paradigm driven by a lightweight Generative Reward Model (GRM). First, RADAR, an offline causal-aware diagnostic framework, extracts high-fidelity, hindsight-free supervision through causal-chain backtracking to distill a GRM providing real-time, step-level risk feedback. Second, FLARE uses this GRM to continuously optimize the agent across its entire lifecycle. During inference, FLARE acts as an Active Scaffold, autonomously intercepting high-risk generation steps for localized breakpoint re-execution, drastically reducing compute overhead. During post-training, the GRM's structured signals serve as process-supervised reranking scores for Supervised Fine-Tuning (SFT) and step-level dense rewards for Reinforcement Learning (RL), mitigating policy collapse in sparse environments. Extensive evaluations show that FLARE establishes a new Pareto frontier across the agent lifecycle: FLARE (N=1) outperforms Global Rollout (N=5) with a 5x reduction in token consumption. Extending FLARE to training overcomes the sparse reward problem in long-horizon interactive tasks, delivering relative performance gains of 19.13% in SFT through process-aware data curation and a consistent 9.19% improvement in RL.

cs.CL↗

arXiv2026

On space-time derivative estimates for the fractional Navier-Stokes equations

In this paper, we are concerned with space-time derivative estimates of solutions to the fractional Navier-Stokes equations. It is shown that $Λ^{nα}u^{(m)}_{t} \in L^{\frac{2(6α-5)}{4mα+2nα+4 α-5}}~~~~~~~(0,T; L^{2}(\mathbb{R}^{3}))$ and $ Λ^{n }u^{(m)}_{t} \in L^{\frac{2(6α-5)}{4mα+2n +4 α-5}}~~~~~(0,T; L^{2}(\mathbb{R}^{3}))$. This generalizes a priori bounds for the classical Navier-Stokes system by Duff in [7, Acta Math. 164, 1990] and Boutros and Gibbon's spatial derivative estimates in [1, Nonlinearity 37, 2024]. In addition, we derive that $ u \in L^{\frac{q}{q-3}}~~(0,T;L^{q} (\mathbb{R}^{3}))$ with $ 6\leq q\leq\infty $ and $Λ^{k}u \in L^{\frac{q}{ q(k+1)-3}}~~~(0,T;L^{q} (\mathbb{R}^{3})) $ with $k\geq1, 2\leq q\leq\infty $ in the standard Navier-Stokes equations.

math.AP↗

arXiv2026

On space-time derivative estimates for the magnetohydrodynamic equations

In this paper, we present the space-time derivative estimates of solutions to the MHD equations. It is a generalization of a priori bounds for the classical Navier-Stokes system by Duff in \cite[Acta Math. 164, 1990]{[Duff]} and gives an affirmative answer to a question proposed by Zheligovsky in \cite[Mathematics. 9, 2021]{[Zheligovsky]}. In addition, we show that $u, B \in L^{\f{q}{q-3}}(0,T;L^{q} (\mathbb{R}^{3}))$ with $6\leq q\leq\infty $ and $ D ^{k}u, D ^{k}B \in L^{\f{q}{ q(k+1)-3}}(0,T;L^{q} (\mathbb{R}^{3}))$ for $k\geq1, 2\leq q\leq\infty$ in this system.

math.AP↗

arXiv2026

MedGEN-Bench: A Contextually Entangled Benchmark for Open-ended Multimodal Medical Generation

Medical vision-language models (VLMs) are increasingly expected to support clinical workflows through diagnostic text and relevant medical images. However, current medical visual benchmarks have three recurring limitations: query-image misalignment from queries weakly grounded in specific image instances, closed-ended formats that narrow answer space and encourage shortcut-based prediction, and text-centric output paradigms that limit evaluation of image-generation and image-editing capabilities. We introduce MedGEN-Bench, a benchmark for open-ended multimodal medical generation. The evaluation snapshot reported in this manuscript comprises 6,422 image-text pairs reviewed by clinical experts and models, spanning 6 canonical imaging modalities, 15 clinical tasks, and 27 named subtasks. It includes 1,100 Visual Question Answering (VQA) pairs, 3,872 Image Editing pairs, and 1,450 Contextual Multimodal Generation pairs. MedGEN-Bench centers on contextual entanglement: dependence of an instruction's intended output on the particular image instance rather than on task wording alone. The benchmark operationalizes this concept through image-grounded instructions and extends evaluation to open-ended multimodal outputs. Its tiered evaluation protocol combines reproducible reference-based fidelity and similarity measures with a structured, checklist-guided assessment by a medical VLM judge. We evaluate 10 compositional frameworks, 2 dedicated image-editing models, 3 unified models, and 5 VLMs. The results show image-output tasks remain unsaturated. Contextual augmentation increases mean image-instruction similarity from 0.273 to 0.372, while a 1,000-case medical-expert audit shows moderate agreement between judge scores and clinician ratings. Source code and dataset are available at https://yangjj007.github.io/medgen.

cs.CV↗

arXiv2026

ALMA Reveals an Explosive Outflow Candidate in IRAS 16119--5048

We present a multiwavelength study of the massive star formation region IRAS 16119-5048 (I16119) using ALMA ATOMS Band 3 and QUARKS Band 6 observations, complemented by archival ATCA radio continuum and Spitzer mid-infrared data. The CO (2-1) emission reveals a system of high-velocity streamer-like structures around the central region. Using dendrogram analysis of velocity-channel maps followed by linking in position-position-velocity space, we identify 16 approximately radially distributed streamers whose projected trajectories converge toward a common central region. The kinetic energy of the outflows is at least an order of magnitude lower than those of most known explosive outflows, while their mass entrainment and momentum rates are high compared with typical protostellar outflows, suggesting that I16119 may represent a low-energy explosive outflow candidate. Dense-gas and photodissociation-region tracers reveal shell-like structures associated with the 8 $μ$m emission, indicating that feedback from the H II region may influence the streamer morphology. The 1.3 mm continuum resolves 27 dense cores along a fragmented filamentary structure. Their separations are consistent with thermal Jeans or cylindrical fragmentation, while the collect-and-collapse scenario is unsupported. The dense cores also show evidence of mass segregation, with the most massive cores concentrated near the inferred explosive centre. We suggest that I16119 is a plausible low-energy explosive outflow candidate, possibly triggered by dynamical interactions among centrally concentrated massive cores. However, the complex velocity structure and possible contamination from individual core-driven outflows prevent a definitive classification. More sensitive, higher angular-resolution observations are required to confirm the nature of the outflow.

astro-ph.GA↗

arXiv2026

ALOHA IRDCs Molecular Line Follow-up: I. Gas properties and kinematics

Infrared Dark Clouds are ideal sites for investigating the initial conditions of massive star and cluster formation. The A Lei Of the Habitat and Assembly of Infrared Dark Clouds (ALOHA IRDCs), a James Clerk Maxwell Telescope (JCMT) Large Program, has mapped nearby IRDCs with SCUBA-2. Complementary molecular line observations are needed to characterise the physical, kinematic, and chemical properties of the dense gas. We aim to determine the thermal, kinematic, and chemical properties of clumps identified in the ALOHA IRDCs, and to assess their evolutionary status and level of star-forming activity. We performed single-pointing K-band and W-band observations towards 56 ALOHA IRDCs clumps using the Effelsberg 100-m and Yebes 40-m telescopes, respectively. We derived NH3 kinetic temperatures using the hyperfine group ratio (HFGR) method and identified infall and shock signatures from HCO+, H13CO+, SiO, and HNCO profiles. Water masers and NH2D emission were used as complementary tracers of chemical evolution and star formation. The clumps exhibit kinetic temperatures of 15-29 K. We detect NH2D emission towards 18 sources, with NH2D centroid velocities consistent with NH3, indicating both species trace the same dense gas component. More than half of the clumps display blue-asymmetric HCO+ profiles, identifying them as infall candidates. Water masers are detected in 22 sources, with prominent velocity ranges and variability. Broad SiO emission (>~20 km/s) indicates strong shocks, while narrower extents (<~6km/s) likely trace large-scale interactions or low-velocity shocks. The widespread infall signatures, shock tracers, masers, and NH2D emission suggest that relatively quiescent, chemically young material can coexist with dynamically active gas affected by early protostellar feedback, providing insight into the coupled physical and chemical evolution of massive IRDC clumps.

astro-ph.GA↗

arXiv2026

The TOP-SCOPE Survey of Planck Galactic Cold Clumps: Molecular gas properties

We surveyed 2008 Planck Galactic Cold Clumps (PGCCs) in $^{12}\mathrm{CO}$ and $^{13}\mathrm{CO}$ $J=1$--0 lines using the Taeduk Radio Astronomy Observatory (TRAO) 14 m telescope's multi-beam receiver. We detected 2784 ($^{12}\mathrm{CO}$) and 2291 ($^{13}\mathrm{CO}$) velocity components, their closely correlated centroid velocities suggest that $^{12}$CO and $^{13}$CO generally trace kinematically associated gas. PGCCs have low excitation temperatures (mean $\sim$10 K), mean $^{13}\mathrm{CO}$ optical depth $\sim$0.5, and mean $^{13}\mathrm{CO}$-derived H$_2$ column density $4.3\times10^{21}$~cm$^{-2}$. Gas--dust correlations are moderate, with $N_{^{13}\mathrm{CO}}$ more tightly correlated with the dust-derived H$_2$ column density from the PGCC catalog than $I_{^{12}\mathrm{CO}}$. Colder PGCCs tend to have higher CO-to-H$_2$ conversion factor ($X_{\mathrm{CO}}$) and $[\mathrm{H_{2}}]/[^{13}\mathrm{CO}]$ ratio. $X_{\mathrm{CO}}$ increases clearly with the dust-derived H$_2$ column density, consistent with enhanced CO freeze-out in high-column-density gas. Supersonic non-thermal motions are widespread: the Mach number derived from $^{13}\mathrm{CO}$ has a mean of 4.3 and a median of 3.6, increasing slightly with dust-derived H$_2$ column density. Overall, PGCCs are cold but dynamically active, serving as a valuable laboratory for studying the initial conditions of star formation.

astro-ph.GA↗

arXiv2026

Spinning Straw into Gold: Relabeling LLM Agent Trajectories in Hindsight for Successful Demonstrations

Large language model agents operate in partially observable, long-horizon settings where obtaining supervision remains a major bottleneck. We address this by utilizing a source of supervision overlooked in existing post-training methods: unintended yet successful goals embedded within agent rollouts. Specifically, we introduce Hindsight Supervised Learning (HSL), where an auxiliary LLM reviews each completed trajectory and relabels it with all of the natural-language goals the agent actually achieved. HSL then pairs the trajectory with its relabeled goals and uses these pairs for additional fine-tuning. To mitigate suboptimality in the relabeled data, we propose two learning techniques for HSL, irrelevant-action masking and sample reweighting. Our experiments show that HSL is flexible and compatible with existing post-training pipelines. It improves both SFT and DPO, with larger gains on long-horizon tasks with more diverse goal spaces. Moreover, HSL is sample-efficient: on ALFWorld, it surpasses baselines trained on the full dataset while using only one quarter of the ground-truth demonstrations.

cs.CL↗

arXiv2026

Surface code logical operations on a superconducting quantum processor

Fault-tolerant quantum computation requires logical operations that manipulate encoded information while preserving quantum error-correction protection. In planar surface-code architectures, code deformation and lattice surgery provide a local, measurement-based route to such operations. Here we experimentally realize key elements of patch-based surface-code logical processing on a 107-qubit superconducting quantum processor. We first implement a reusable primitive layer comprising merge and split, patch expansion and shrinkage, and deformations mediated by domain walls and twist defects. We then compose these primitives to realize logical state routing, the logical controlled-NOT gate, and the single-qubit Hadamard and phase gates, which together form a Clifford-generating set. All operations are implemented on distance-three rotated surface-code patches with multi-round syndrome extraction and neural-network decoding, without post-selection. Our results advance superconducting surface-code experiments from protected logical memory to active, patch-based fault-tolerant logical operations.

quant-ph↗