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Researcher profile

Qing Huang

Qing Huang contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
cond-mat.mtrl-scicond-mat.str-elArtificial IntelligenceComputer Visionmath-phmath.MPnlin.SISoftware EngineeringInformation Retrievalquant-ph

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Published work

18 published item(s)

preprint2026arXiv

GenShield: Unified Detection and Artifact Correction for AI-Generated Images

Diffusion-based image synthesis has made AI-generated images (AIGI) increasingly photorealistic, raising urgent concerns about authenticity in applications such as misinformation detection, digital forensics, and content moderation. Despite the substantial advances in AIGI detection, how to correct detected AI-generated images with visible artifacts and restore realistic appearance remains largely underexplored. Moreover, few existing work has established the connection between AIGI detection and artifact correction. To fill this gap, we propose GenShield, a unified autoregressive framework that jointly performs explainable AIGI detection and controllable artifact correction in a closed loop from diagnosis to restoration, revealing a mutually reinforcing relationship between these two tasks. We further introduce a Visual Chain-of-Thought based curriculum learning strategy that enables self-explained, multi-step ``diagnose-then-repair'' correction with an explicit stopping criterion. A high-quality dataset with large-scale ``artifact-restored'' pairs is also constructed alongside a unified evaluation pipeline. Extensive experiments on our correction benchmark and mainstream AIGI detection benchmarks demonstrate state-of-the-art performance and strong generalization of our method. The code is available at https://github.com/zhipeixu/GenShield.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains

Although precise recall is a core objective in Retrieval-Augmented Generation (RAG), a critical oversight persists in the field: improvements in retrieval performance do not consistently translate to commensurate gains in downstream reasoning. To diagnose this gap, we propose the Recall Conversion Rate (RCR), a novel evaluation metric to quantify the contribution of retrieval to reasoning accuracy. Our quantitative analysis of mainstream RAG methods reveals that as Recall@5 improves, the RCR exhibits a near-linear decay. We identify the neglect of retrieval quality in these methods as the underlying cause. In contrast, approaches that focus solely on quality optimization often suffer from inferior recall performance. Both categories lack a comprehensive understanding of retrieval quality optimization, resulting in a trade-off dilemma. To address these challenges, we propose comprehensive retrieval quality optimization criteria and introduce the NeocorRAG framework. This framework achieves holistic retrieval quality optimization by systematically mining and utilizing Evidence Chains. Specifically, NeocorRAG first employs an innovative activated search algorithm to obtain a refined candidate space. Then it ensures precise evidence chain generation through constrained decoding. Finally, the retrieved set of evidence chains guides the retrieval optimization process. Evaluated on benchmarks including HotpotQA, 2WikiMultiHopQA, MuSiQue, and NQ, NeocorRAG achieves SOTA performance on both 3B and 70B parameter models, while consuming less than 20% of tokens used by comparable methods. This study presents an efficient, training-free paradigm for RAG enhancement that effectively optimizes retrieval quality while maintaining high recall. Our code is released at https://github.com/BUPT-Reasoning-Lab/NeocorRAG.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

ReAlign: Generalizable Image Forgery Detection via Reasoning-Aligned Representation

The rise of AI-generated images (AIGIs) poses growing challenges for digital authenticity, prompting the need for efficient, generalizable image forgery detection systems. Existing methods, whether non-LLM-based or LLM-based, exhibit distinct advantages and limitations. While non-LLM-based models offer efficient low-level artifact detection, they often lack semantic understanding. Conversely, LLM-based methods provide strong semantic reasoning and explainability but are computationally intensive and less sensitive to subtle visual artifacts. Moreover, the true contribution of explanatory reasoning texts to forgery detection performance remains unclear. In this work, we investigate the intrinsic value and potential of LLM-generated reasoning texts, considering it a source of generalization and semantic-error sensitivity. Based on these findings, we propose ReAlign, a novel framework that distills high-quality reasoning texts generated by a GRPO-optimized LLM into a lightweight AIGI detector via contrastive learning. ReAlign effectively inherits the generalization ability and semantic sensitivity capability of reasoning textual representations, while remaining efficient and lightweight for deployment. Moreover, ReAlign adopts a tailored joint optimization strategy that integrates contrastive loss for image-text alignment and classification loss for accurate forgery discrimination. Experimental results on AIGCDetectBenchmark, AIGI-Holmes, and our newly constructed UltraSynth-10k demonstrate that ReAlign consistently outperforms existing state-of-the-art detectors in both accuracy and generalization, particularly when facing complex, high-fidelity forgeries from modern generative models.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

API Entity and Relation Joint Extraction from Text via Dynamic Prompt-tuned Language Model

Extraction of Application Programming Interfaces (APIs) and their semantic relations from unstructured text (e.g., Stack Overflow) is a fundamental work for software engineering tasks (e.g., API recommendation). However, existing approaches are rule-based and sequence-labeling based. They must manually enumerate the rules or label data for a wide range of sentence patterns, which involves a significant amount of labor overhead and is exacerbated by morphological and common-word ambiguity. In contrast to matching or labeling API entities and relations, this paper formulates heterogeneous API extraction and API relation extraction task as a sequence-to-sequence generation task, and proposes AERJE, an API entity-relation joint extraction model based on the large pre-trained language model. After training on a small number of ambiguous but correctly labeled data, AERJE builds a multi-task architecture that extracts API entities and relations from unstructured text using dynamic prompts. We systematically evaluate AERJE on a set of long and ambiguous sentences from Stack Overflow. The experimental results show that AERJE achieves high accuracy and discrimination ability in API entity-relation joint extraction, even with zero or few-shot fine-tuning.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Spinon continuum in the Heisenberg quantum chain compound Sr$_2$V$_3$O$_9$

Magnetic excitations in the spin chain candidate Sr$_2$V$_3$O$_9$ have been investigated by inelastic neutron scattering on a single crystal sample. A spinon continuum with a bandwidth of $\sim22$ meV is observed along the chain formed by alternating magnetic V$^{4+}$ and nonmagnetic V$^{5+}$ ions. Incipient magnetic Bragg peaks due to weak ferromagnetic interchain couplings emerge when approaching the magnetic transition at $T_N\sim 5.3$ K while the excitations remain gapless within the instrumental resolution. Comparisons to the Bethe ansatz, density matrix renormalization group (DMRG) calculations, and effective field theories confirm Sr$_2$V$_3$O$_9$ as a host of weakly coupled $S = 1/2$ chains dominated by antiferromagnetic intrachain interactions of $\sim7.1$(1) meV.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Anticollinear order and degeneracy lifting in square lattice antiferromagnet LaSrCrO4

We report the static and dynamic magnetic properties of LaSrCrO$_4$, a seemingly canonical spin-3/2 square-lattice antiferromagnet that exhibits frustration between magnetic layers -- owing to their AB stacking -- and offers a rare testbed to investigate accidental-degeneracy lifting in magnetism. Neutron diffraction experiments on single-crystal samples uncover a remarkable anticollinear magnetic order below $T_N$ = 170 K characterized by a Néel arrangement of the spins within each layer and an orthogonal arrangement between adjacent layers. To understand the origin of this unusual magnetic structure, we analyze the spin-wave excitation spectrum by means of inelastic neutron scattering and bulk measurements. A spectral gap of 0.5 meV, along with a spin-flop transition at 3.2\, T, reflect the energy scale associated with the degeneracy-lifting. A minimal model to explain these observations requires both a positive biquadratic interlayer exchange and dipolar interactions, both of which are on the order of 10$^{-4}$ meV, only a few parts per million of the dominant exchange interaction $J_1 \approx 11$ meV. These results provide direct evidence for the selection of a non-collinear magnetic structure by the combined effect of two distinct degeneracy lifting interactions.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Evidence for pressure induced unconventional quantum criticality in the coupled spin ladder antiferromagnet C$_9$H$_{18}$N$_2$CuBr$_4$

Quantum phase transitions in quantum matter occur at zero temperature between distinct ground states by tuning a nonthermal control parameter. Often, they can be accurately described within the Landau theory of phase transitions, similarly to conventional thermal phase transitions. However, this picture can break down under certain circumstances. Here, we present a comprehensive study of the effect of hydrostatic pressure on the magnetic structure and spin dynamics of the spin-1/2 ladder compound C$_9$H$_{18}$N$_2$CuBr$_4$. Single-crystal heat capacity and neutron diffraction measurements reveal that the N$\rm \acute{e}$el-ordered phase breaks down beyond a critical pressure of $P_{\rm c}$$\sim$1.0 GPa through a continuous quantum phase transition. Estimates of the critical exponents suggest that this transition may fall outside the traditional Landau paradigm. The inelastic neutron scattering spectra at 1.3 GPa are characterized by two well-separated gapped modes, including one continuum-like and another resolution-limited excitation in distinct scattering channels, which further indicates an exotic quantum-disordered phase above $P_{\rm c}$.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Investigation of the monopole magneto-chemical potential in spin ices using capacitive torque magnetometry

The single-ion anisotropy and magnetic interactions in spin-ice systems give rise to unusual non-collinear spin textures, such as Pauling states and magnetic monopoles. The effective spin correlation strength ($J_{eff}$) determines the relative energies of the different spin-ice states. With this work, we display the capability of capacitive torque magnetometry in characterizing the magneto-chemical potential associated with monopole formation. We build a magnetic phase diagram of Ho$_2$Ti$_2$O$_7$, and show that the magneto-chemical potential depends on the spin-sublattice ($α$ or $β$), i.e., the Pauling state, involved in the transition. Monte-Carlo simulations using the dipolar-spin-ice Hamiltonian support our findings of a sublattice-dependent magneto-chemical potential, but the model underestimates the $J_{eff}$ for the $β$-sublattice. Additional simulations, including next-nearest neighbor interactions ($J_2$), show that long-range exchange terms in the Hamiltonian are needed to describe the measurements. This demonstrates that torque magnetometry provides a sensitive test for $J_{eff}$ and the spin-spin interactions that contribute to it.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Prompt-tuned Code Language Model as a Neural Knowledge Base for Type Inference in Statically-Typed Partial Code

Partial code usually involves non-fully-qualified type names (non-FQNs) and undeclared receiving objects. Resolving the FQNs of these non-FQN types and undeclared receiving objects (referred to as type inference) is the prerequisite to effective search and reuse of partial code. Existing dictionary-lookup based methods build a symbolic knowledge base of API names and code contexts, which involve significant compilation overhead and are sensitive to unseen API names and code context variations. In this paper, we formulate type inference as a cloze-style fill-in-blank language task. Built on source code naturalness, our approach fine-tunes a code masked language model (MLM) as a neural knowledge base of code elements with a novel "pre-train, prompt and predict" paradigm from raw source code. Our approach is lightweight and has minimum requirements on code compilation. Unlike existing symbolic name and context matching for type inference, our prompt-tuned code MLM packs FQN syntax and usage in its parameters and supports fuzzy neural type inference. We systematically evaluate our approach on a large amount of source code from GitHub and Stack Overflow. Our results confirm the effectiveness of our approach design and the practicality for partial code type inference. As the first of its kind, our neural type inference method opens the door to many innovative ways of using partial code.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Regulate the direct-indirect electronic band gap transition by electron-phonon interaction in BaSnO3

The neutron powder diffraction, specific heat, thermal conductivity, and Raman scattering measurements were presented to study the interplays of lattice, phonons and electrons of the Sr-doping Ba1-xSrxSnO3 (x was less than or equal to 0.1). Although Ba1-xSrxSnO3 kept the cubic lattice, the Raman spectra suggested a dynamic distortion at low temperature. The density functional theory was applied to analyze the electronic structures and phonon dispersions of Ba1-xSrxSnO3(x = 0, 0.0125), and the behaviors of electron bands around Fermi levels were discussed. According to the experimental and theoretical results, the Sr-doping played a significant role in tuning the indirect band gap of BaSnO3 and influenced the electron-phonon interaction.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Integrable and Superintegrable Extensions of the Rational Calogero-Moser Model in 3 Dimensions

We consider a class of Hamiltonian systems in 3 degrees of freedom, with a particular type of quadratic integral and which includes the rational Calogero-Moser system as a particular case. For the general class, we introduce separation coordinates to find the general separable (and therefore Liouville integrable) system, with two quadratic integrals. This gives a coupling of the Calogero-Moser system with a large class of potentials, generalising the series of potentials which are separable in parabolic coordinates. Particular cases are {\em superintegrable}, including Kepler and a resonant oscillator. The initial calculations of the paper are concerned with the flat (Cartesian type) kinetic energy, but in Section \ref{sec:conflat-general}, we introduce a {\em conformal factor} $φ$ to $H$ and extend the two quadratic integrals to this case. All the previous results are generalised to this case. We then introduce some 2 and 3 dimensional symmetry algebras of the Kinetic energy (Killing vectors), which restrict the conformal factor. This enables us to reduce our systems from 3 to 2 degrees of freedom, giving rise to many interesting systems, including both Kepler type and Hénon-Heiles type potentials on a Darboux-Koenigs $D_2$ background.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

MAX Phase Zr2SeC and Its Thermal Conduction Behavior

The elemental diversity is crucial to screen out ternary MAX phases with outstanding properties via tuning of bonding types and strength between constitutive atoms. As a matter of fact, the interactions between M and A atoms largely determine the physical and chemical properties of MAX phases. Herein, Se element was experimentally realized to occupy the A site of a MAX phase, Zr2SeC, becoming a new member within this nanolaminated ternary carbide family. Comprehensive characterizations including Rietveld refinement of X-ray Diffraction and atom-resolved transmission electron microscopy techniques were employed to validate this novel MAX phase. The distinct thermal conduction behaviors emerged are attributed to the characteristic interactions between Zr and Se atoms.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Neutron scattering investigation of proposed Kosterlitz-Thouless transitions in the triangular-lattice Ising antiferromagnet TmMgGaO4

The transverse-field Ising model on the triangular lattice is expected to host an intermediate finite-temperature Kosterlitz-Thouless (KT) phase through a mapping of the spins on each triangular unit to a complex order parameter. TmMgGaO$_4$ is a candidate material to realize such physics due to the non-Kramers nature of Tm$^{3+}$ ion and the resulting two-singlet single-ion ground state. Using inelastic neutron scattering, we confirm this picture by determining the leading parameters of the low-energy effective Hamiltonian of TmMgGaO$_4$. Subsequently, we track the predicted KT phase and related transitions by inspecting the field and temperature dependence of the ac susceptibility. We further probe the spin correlations in both reciprocal space and real space via single crystal neutron diffraction and magnetic total scattering techniques, respectively. Magnetic pair distribution function analysis provides evidence for the formation of vortex-antivortex pairs that characterize the proposed KT phase around 5~K. Although structural disorder influences the field-induced behavior of TmMgGaO$_4$, the magnetism in zero field appears relatively free from these effects. These results position TmMgGaO$_4$ as a strong candidate for a solid-state realization of KT physics in a dense spin system.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Halogenated MXenes with Electrochemically Active Terminals for High Performance Zinc Ion Batteries

The class of two-dimensional metal carbides and nitrides known as MXenes offer a distinct manner of property tailoring for a wide range of applications. The ability to tune the surface chemistry for expanding the property space of MXenes is thus an important topic, although experimental exploration of new surface terminals remains a challenge. Here, we synthesized Ti3C2 MXene with unitary, binary and ternary halogen terminals, e.g. -Cl, -Br, -I, -BrI and -ClBrI, to investigate the effect of surface chemistry on the properties of MXenes. The electrochemical activity of Br and I element result in the extraordinary electrochemical performance of the MXenes as cathodes for aqueous zinc ion batteries. The -Br and -I containing MXenes, e.g. Ti3C2Br2 and Ti3C2I2, exhibit distinct discharge platforms with considerable capacities of 97.6 mAh g-1 and 135 mAh g-1. Ti3C2(BrI) and Ti3C2(ClBrI) exhibit dual discharge platforms with capacities of 117.2 mAh g-1 and 106.7 mAh g-1. In contrast, the previously discovered MXenes Ti3C2Cl2 and Ti3C2(OF) exhibit no discharge platforms, and only ~50% of capacities and energy densities of Ti3C2Br2. These results emphasize the effectiveness of the Lewis-acidic-melt etching route for tuning the surface chemistry of MXenes, and also show promise for expanding the MXene family towards various applications.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Hybridized quadrupolar excitations in the spin-anisotropic frustrated magnet FeI2

Magnetic order is usually associated with well-defined magnon excitations. Exotic magnetic fluctuations with fractional, topological or multipolar character, have been proposed for radically different forms of magnetic matter such as spin-liquids. As a result, considerable efforts have searched for, and uncovered, low-spin materials with suppressed dipolar order at low temperatures. Here, we report neutron-scattering experiments and quantitative theoretical modeling of an exceptional spin-1 system -- the uniaxial triangular magnet FeI2 -- where a bright and dispersive band of mixed dipolar-quadrupolar fluctuations emerges just above a dipolar ordered ground-state. This excitation arises from anisotropic exchange interactions that hybridize overlapping modes carrying fundamentally different quantum numbers. Remarkably, a generalization of spin-wave theory to local SU(3) degrees of freedom accounts for all details of the low-energy dynamical response of FeI2 without going beyond quadratic order. Our work highlights that quantum excitations without classical counterparts can be realized even in presence of fully developed magnetic order.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

The role of Hume-Rothery's rules play in the MAX phases formability

MAX phases are a family of layered, hexagonal-structure ternary carbides or nitrides of a transitional metal and an A-group element. What makes this type of material fascinating and potentially useful is their remarkable combinations of metallic and ceramic characteristics; as well as the indispensable role in 'top-down' synthesis of their 2D counterparts, MXenes. To enhance the efficiency in the successful search for potential novel MAX phases, the main efforts could go toward creating an informationprediction system incorporating all MAX phases' databases, as well as generally valid principles and the high-quality regularities. In this work, we employ structure mapping methodology, which has shown its merit of being useful guides in materials design, with Hume-Rothery parameters to provide guiding principles in the search of novel MAX phases. The formable/non-formable data on MAX phases can be ordered within a twodimensional plot by using proposed expression of geometrical and electron concentration factors.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Multielemental single-atom-thick A layers in nanolaminated V2(Sn, A)C (A=Fe, Co, Ni, Mn) for tailoring magnetic properties

Tailoring of individual single-atom-thick layers in nanolaminated materials offers atomic-level control over material properties. Nonetheless, multielement alloying in individual atomic layers in nanolaminates is largely unexplored. Here, we report a series of inherently nanolaminated V2(A'xSn1-x)C (A'=Fe, Co, Ni and Mn, and combinations thereof, with x=1/3) synthesized by an alloy-guided reaction. The simultaneous occupancy of the four magnetic elements and Sn, the individual single-atom-thick A layers in the compound constitute high-entropy-alloy analogues, two-dimensional in the sense that the alloying exclusively occurs in the A layers. V2(A'xSn1-x)C exhibit distinct ferromagnetic behavior that can be compositionally tailored from the multielement A-layer alloying. This two-dimensional alloying provides a structural-design route with expanded chemical space for discovering materials and exploit properties.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Superintegrable Systems on 3 Dimensional Conformally Flat Spaces

We consider Hamiltonians associated with 3 dimensional conformally flat spaces, possessing 2, 3 and 4 dimensional isometry algebras. We use the conformal algebra to build additional {\em quadratic} first integrals, thus constructing a large class of superintegrable systems and the complete Poisson algebra of first integrals. We then use the isometries to reduce our systems to 2 degrees of freedom. For each isometry algebra we give a {\em universal} reduction of the corresponding general Hamiltonian. The superintegrable specialisations reduce, in this way, to systems of Darboux-Koenigs type, whose integrals are reductions of those of the 3 dimensional system.

0 citations0 reviewsNo code linkedOpen access