arXiv subjects

Zhichao Zhou

Publications and source records attributed to Zhichao Zhou.

At least 19 recordsLinked to original sources

arXiv2026

Retrieval-grounded robot program generation and simulation-based correction via Model Context Protocol

Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based workflow that generates, validates, and iteratively corrects ABB RAPID robot programs from natural language task descriptions. A dual-stream retrieval-augmented generation (RAG) pipeline grounds code generation in verified technical documentation and production templates, reducing domain-specific errors produced by ungrounded language models. A custom Model Context Protocol (MCP) server connects the language-model client directly to ABB RobotStudio for automated code upload, simulation execution, and diagnostic feedback. The evaluation combines a 30-query retrieval benchmark, scoped code-generation checks, and RobotStudio case studies in a simulated pickand- place manufacturing cell. The simulation loop exposes execution failures that static and semantic checks alone cannot catch, including suction release-height errors, unreachable placement targets, and configuration-dependent recovery motions. The results show how RAG and MCP can connect grounded code generation with executable feedback from industrial robot simulation software, while reducing but not eliminating expert setup and final supervision.

cs.AI↗

arXiv2026

Valley-contrasting Spin Textures in Janus Metal Phosphochalcogenides

Momentum-resolved spin textures and potential valley-contrasting physical properties in the momentum space are two intriguing characteristics of noncentrosymmetric materials, and they have broad applications in spintronics and valleytronics. The realization of diverse spin textures within a single material, along with their further coupling to the valley degree of freedom, is highly desirable. Via first-principles calculations, we investigate electronic properties of Janus MP$_2$S$_3$Se$_3$ monolayers, which exhibits distinct spin textures at different valleys. While Ising-type spin textures are located at $K_\pm$ valleys, the symmetry breaking from the Janus structure brings about a coexistence of Weyl-type and Rashba-type spin textures at $Γ$ valley. In addition to valley-contrasting spin textures, valley dependence also occurs in Berry-curvature-driven anomalous Hall currents and optical selectivity. Besides, energy differences between $Γ$ and $K_\pm$, as well as band gaps, are highly tunable by applied strain. These findings present an intriguing coupling between diverse spin textures and multiple valleys, and pave the way for designing advanced electronic devices that leverage spin and valley degrees of freedom.

cond-mat.mtrl-sci↗

arXiv2026

Valleytronics in 2D Materials Roadmap

Valleytronics exploits non-equivalent energy extrema in the electronic band structure of crystalline solids -- the valley degree of freedom -- to encode, manipulate, and read out information. The advent of 2D materials, first graphene and then transition-metal dichalcogenides, made valley control practical through optical, electrical, and magnetic routes. This foundation has enabled remarkable progress in recent years spanning established frontiers, such as valley exciton physics and valley Hall effects, as well as emerging directions including lightwave valleytronics, nanophotonic integration, flat-band valleytronics, and spin-valley qubits. In parallel, there are sustained efforts to scale up valleytronic materials and to predict new valleytronic platforms. This Roadmap brings together perspectives from leading experts to chart the key opportunities and challenges at the forefront of 2D material valleytronics. Each section captures a snapshot of progress in a key research area, identifies critical open challenges, and outlines pathways toward future valleytronics breakthroughs.

cond-mat.mes-hall↗

arXiv2025

DreamFoley: Scalable VLMs for High-Fidelity Video-to-Audio Generation

Recent advances in video generation have achieved remarkable improvements in visual content fidelity. However, the absence of synchronized audio severely undermines immersive experience and restricts practical applications of these technologies. To address this challenge, several pioneering works have explored diffusion transformer architectures for generating plausible video-synchronized audio, including Kling-foley, HunyuanVideo-foley and Thinksound. Distinct from existing works, we introduce an autoregressive audio generation architecture (DreamFoley) that harnesses the capabilities of large vision-language models (VLMs) to jointly model sequential interactions among video, audio, and text modalities. Our approach features a dual-visual encoder module that effectively captures both audio-aligned and text-aligned visual features. Additionally, we employ a Residual Vector Quantization audio tokenizer with a delay-pattern generation scheme to balance the trade-off between training efficiency and audio quality. Moreover, we introduce the classifier-free guidance strategy into VLMs to bootstrap generated audio quality. Furthermore, we establish an efficient data production pipeline to scale audio-video-text triple collection. Finally, extensive experiments are conducted to validate the effectiveness of our model, achieving promising performance across popular benchmarks. We hope that the findings in this study provide a strong foundation for future video-to-audio generation research. We also release the previously missing audio-visual textual descriptions from the public benchmark, aiming to facilitate subsequent researchers in conducting more convenient and effective evaluations and comparisons.

cs.SD↗

arXiv2025

Magnetically controllable nonlinear valley Hall effect in centrosymmetric ferromagnets

Valley Hall effect is fundamental to valleytronics and provides a promising avenue for advancing information technology. While conventional valley Hall effect requires the inversion symmetry breaking, the recently proposed nonlinear valley Hall (NVH) effect removes the symmetry constraint, and broaden material choices. However, existing studies are limited to nonmagnetic materials without spin involvement and rely on external strain to break rotational symmetry. Here, to address these limitations, we design a magnetically controllable NVH effect in centrosymmetric ferromagnets, by the tight-binding model and first-principles calculations. The model calculations demonstrate nonvanishing NVH conductivities can emerge in pristine hexagonal lattice without external strain, with the magnitude, sign, and spin polarization of the conductivities being all dependent on the magnetization orientation. The effect thus generates various spin-polarized valley Hall currents, characterized by distinct combinations of current direction and spin polarization. First-principle results on a ferromagnetic VSi$_2$N$_4$ bilayer confirm considerable NVH conductivities and their dependence on the magnetization. The magnetically controllable NVH effect unlocks the potential of centrosymmetric magnets for valleytronics, and offer opportunities for novel spintronic and valleytronic devices.

cond-mat.mes-hall↗

arXiv2025

Thinking With Videos: Multimodal Tool-Augmented Reinforcement Learning for Long Video Reasoning

The video reasoning ability of multimodal large language models (MLLMs) is crucial for downstream tasks like video question answering and temporal grounding. While recent approaches have explored text-based chain-of-thought (CoT) reasoning for MLLMs, these methods often suffer from limited cross-modal interaction and increased hallucination, especially with longer videos or reasoning chains. To address these challenges, we propose Video Intelligence via Tool-Augmented Learning (VITAL), a novel end-to-end agentic video reasoning framework. With a visual toolbox, the model can densely sample new video frames on demand and generate multimodal CoT for precise long video reasoning. We observe that temporal grounding and question answering are mutually beneficial for video understanding tasks. Therefore, we construct two high-quality multi-task video reasoning datasets MTVR-CoT-72k for supervised fine-tuning and MTVR-RL-110k for reinforcement learning. Moreover, we propose a Difficulty-aware Group Relative Policy Optimization algorithm (DGRPO) to mitigate difficulty imbalance in multi-task reinforcement learning. Extensive experiments on 11 challenging video understanding benchmarks demonstrate the advanced reasoning ability of VITAL, outperforming existing methods in video question answering and temporal grounding tasks, especially in long video scenarios. Code is available at https://zhang9302002.github.io/thinkingwithvideos-page/.

cs.CV↗

arXiv2025

Staggered nonlinear spin generations in centrosymmetric altermagnets under electric current

Current-induced spin generations are of significant importance for electrically controllable magnetization. Due to symmetry constraints, linear spin generation is absent in centrosymmetric magnets and nonlinear contributions become crucial. However, nonlinear spin generations have few examples in centrosymmetric compensated magnets with opposite-spin sublattices, which hinders electric control of associated magnetization. Here, we study nonlinear spin generations in altermagnets with opposite-spin sublattices. In a square altermagnetic model, both staggered and uniform nonlinear spin generations appear at opposite-spin sublattices. They vary as the magnetization direction rotates, with emerging out-of-plane components that can be utilized in perpendicular magnetization switching of high-density storage devices. By first-principles calculations, out-of-plane, staggered nonlinear spin generations are found to be considerable in a typical altermagnet, Fe$_2$Se$_2$O monolayer. Our findings provide opportunities for electrically manipulating magnetization and designing energy-efficient magnetic devices based on compensated magnets.

cond-mat.mes-hall↗

arXiv2025

Artemis: Toward Accurate Detection of Server-Side Request Forgeries through LLM-Assisted Inter-Procedural Path-Sensitive Taint Analysis

Server-side request forgery (SSRF) vulnerabilities are inevitable in PHP web applications. Existing static tools in detecting vulnerabilities in PHP web applications neither contain SSRF-related features to enhance detection accuracy nor consider PHP's dynamic type features. In this paper, we present Artemis, a static taint analysis tool for detecting SSRF vulnerabilities in PHP web applications. First, Artemis extracts both PHP built-in and third-party functions as candidate source and sink functions. Second, Artemis constructs both explicit and implicit call graphs to infer functions' relationships. Third, Artemis performs taint analysis based on a set of rules that prevent over-tainting and pauses when SSRF exploitation is impossible. Fourth, Artemis analyzes the compatibility of path conditions to prune false positives. We have implemented a prototype of Artemis and evaluated it on 250 PHP web applications. Artemis reports 207 true vulnerable paths (106 true SSRFs) with 15 false positives. Of the 106 detected SSRFs, 35 are newly found and reported to developers, with 24 confirmed and assigned CVE IDs.

cs.CR↗

arXiv2024

Nonlinear valley Hall effect in a bilayer transition metal dichalcogenide

Valley-contrasting Hall transport conventionally relies on the inversion symmetry breaking in two-dimensional systems, which greatly limits the selection range of valley materials. In particular, while monolayer transition metal dichalcogenides have been widely utilized as a well-known class of valley materials in valleytronics, the centrosymmetric nature hinders the realization of valley-contrasting properties in the bilayer counterparts. Here, taking MoS$_{2}$ as an example, we discover valley-contrasting transport in bilayer transition metal dichalcogenides by exploring nonlinear transport regime. Using effective models and first-principles calculations, our work demonstrates that nonvanishing nonlinear valley Hall conductivities emerge in a uniaxially strained MoS$_{2}$ bilayer, owing to strain-induced band tilts of Dirac fermions. With the aid of small spin-orbit-coupling induced band splittings, the conduction bands generate much remarkable nonlinear valley Hall conductivity. Moreover, the nonlinear conductivities are highly tunable through modulating the strength and the direction of the strain, chemical potential, and interlayer gap. Our findings not only expands material choices for valleytronic applications, but also provides opportunities for designing advanced electronic devices that leverage nonlinear valley transports.

cond-mat.mes-hall↗

arXiv2024

Multiple types of spin textures and robust valley physics in MP$_2$X$_6$

Both spin textures and multiple valleys in the momentum space have attracted great attentions due to their versatile applications in spintronics and valleytronics. It is highly desirable to realize multiple types of spin textures in a single material and further couple the spin textures to valley degree of freedom. Here, we study electronic properties of SnP$_{2}$Se$_{6}$ monolayer by first-principles calculations. The monolayer exhibits rare Weyl-type and Ising-type spin textures at different valleys, which can be conveniently expressed by electron and hole dopings, respectively. Besides valley-contrasting spin textures, Berry-curvature-driven anomalous Hall currents and optical selectivity are found to be valley dependent as well. These valley-related properties also have generalizations to SnP$_{2}$Se$_{6}$ few-layers and other MP$_{2}$X$_{6}$. Our findings open new avenue for exploring appealing interplay between spin textures and multiple valleys, and designing advanced device paradigms based on spin and valley degrees of freedom.

cond-mat.mtrl-sci↗

arXiv2024

An LLM-based Readability Measurement for Unit Tests' Context-aware Inputs

Automated test techniques usually generate unit tests with higher code coverage than manual tests. However, the readability of automated tests is crucial for code comprehension and maintenance. The readability of unit tests involves many aspects. In this paper, we focus on test inputs. The central limitation of existing studies on input readability is that they focus on test codes alone without taking the tested source codes into consideration, making them either ignore different source codes' different readability requirements or require manual efforts to write readable inputs. However, we observe that the source codes specify the contexts that test inputs must satisfy. Based on such observation, we introduce the \underline{C}ontext \underline{C}onsistency \underline{C}riterion (a.k.a, C3), which is a readability measurement tool that leverages Large Language Models to extract primitive-type (including string-type) parameters' readability contexts from the source codes and checks whether test inputs are consistent with those contexts. We have also proposed EvoSuiteC3. It leverages C3's extracted contexts to help EvoSuite generate readable test inputs. We have evaluated C3's performance on $409$ \java{} classes and compared manual and automated tests' readability under C3 measurement. The results are two-fold. First, The Precision, Recall, and F1-Score of C3's mined readability contexts are \precision{}, \recall{}, and \fone{}, respectively. Second, under C3's measurement, the string-type input readability scores of EvoSuiteC3, ChatUniTest (an LLM-based test generation tool), manual tests, and two traditional tools (EvoSuite and Randoop) are $90\%$, $83\%$, $68\%$, $8\%$, and $8\%$, showing the traditional tools' inability in generating readable string-type inputs.

cs.SE↗

arXiv2024

Mott insulating states of the anisotropic SU(4) Dirac fermions

We employ the large-scale quantum Monte-Carlo simulations to investigate the Mott-insulating states of the half-filled SU(4) Hubbard model on the square lattice with a staggered-flux pattern. The noninteracting band structure that evolves from a nested Fermi surface at zero flux to isotropic Dirac cones at $π$ flux, exhibits anisotropic Dirac cones as the flux varies in between. Our simulations show transitions between the three phases of Dirac semimetal, antiferromagnet and valence-bond solid. A direct continuous transition between the antiferromagnetic phase and the valence-bond-solid phase is realized via varying the flux in the Mott regime. The simulated critical exponents remarkably agree with those of SU(4) $J$-$Q$ model. Inside the valence-bond-solid phase induced by the flux, the plaquette valence-bond state with vanishing single-particle gap is identified. At strong coupling, the valence-bond-solid phase disappears and the Mott-insulating state is always accompanied by antiferromagnetic ordering, regardless of the magnitude of the flux.

cond-mat.quant-gas↗

arXiv2024

Coverage Goal Selector for Combining Multiple Criteria in Search-Based Unit Test Generation

Unit testing is critical to the software development process, ensuring the correctness of basic programming units in a program (e.g., a method). Search-based software testing (SBST) is an automated approach to generating test cases. SBST generates test cases with genetic algorithms by specifying the coverage criterion (e.g., branch coverage). However, a good test suite must have different properties, which cannot be captured using an individual coverage criterion. Therefore, the state-of-the-art approach combines multiple criteria to generate test cases. Since combining multiple coverage criteria brings multiple objectives for optimization, it hurts the test suites' coverage for certain criteria compared with using the single criterion. To cope with this problem, we propose a novel approach named \textbf{smart selection}. Based on the coverage correlations among criteria and the subsumption relationships among coverage goals, smart selection selects a subset of coverage goals to reduce the number of optimization objectives and avoid missing any properties of all criteria. We conduct experiments to evaluate smart selection on $400$ Java classes with three state-of-the-art genetic algorithms under the $2$-minute budget. On average, smart selection outperforms combining all goals on $65.1\%$ of the classes having significant differences between the two approaches. Secondly, we conduct experiments to verify our assumptions about coverage criteria relationships. Furthermore, we assess the coverage performance of smart selection under varying budgets of $5$, $8$, and $10$ minutes and explore its effect on bug detection, confirming the advantage of smart selection over combining all goals.

cs.SE↗

arXiv2023

Quantum anomalous Hall state in a fluorinated 1T-MoSe$_2$ monolayer

The quantum anomalous Hall state with a large band gap and a high Chern number is significant for practical applications in spintronics. By performing first-principles calculations, we investigate electronic properties of the fully fluorinated 1T-MoSe$_{2}$ monolayer. Without considering the spin-orbit coupling, the band structure demonstrates single-spin semi-metallic properties and the trigonal warping around $K_{\pm}$ valleys. The introduction of the spin-orbit coupling opens considerable band gaps of $117.2$ meV around the two valleys, leading to a nontrivial quantum anomalous Hall state with a Chern number of $|C|=2$, which provides two chiral dissipationless transport channels from topological edge states and associated quantized anomalous Hall conductivity. In addition, an effective model is constructed to describe the low-energy physics of the monolayer. Our findings in the MoSe$_{2}$F$_{2}$ monolayer sheds light on large-gap quantum anomalous Hall states in two-dimensional materials with the chemical functionalization, and provides opportunities in designing low-power and noise-tolerant spintronic devices.

cond-mat.mes-hall↗

arXiv2023

Trion states and quantum criticality of attractive SU(3) Dirac fermions

We perform the projector quantum Monte Carlo (QMC) simulation to study the trion formation and quantum phase transition in the half-filled attractive SU(3) Hubbard model on a honeycomb lattice. With increasing attractive Hubbard interaction, our simulations demonstrate a continuous quantum phase transition from the semimetal to charge density wave (CDW) at the critical coupling $U_c/t=-1.52(2)$. The critical exponents $ν=0.82(3)$ and $η=0.58(4)$ determined by the QMC simulation remarkably disagree with those of the $N=3$ chiral Ising universality class suggested by the effective Gross-Neveu-Yukawa (GNY) theory, but coincide with the $N=1$ chiral Ising universality class. In the CDW phase, we show that on-site and off-site trions coexist and the off-site trion forms a local bond state. Our work not only illustrates the formation of off-site trions in two-dimensional Hubbard model, but also raises doubts about the extent of applicability of GNY model on the attractive SU(3) Dirac fermions.

cond-mat.quant-gas↗

arXiv2023

ChatGPT vs SBST: A Comparative Assessment of Unit Test Suite Generation

Recent advancements in large language models (LLMs) have demonstrated exceptional success in a wide range of general domain tasks, such as question answering and following instructions. Moreover, LLMs have shown potential in various software engineering applications. In this study, we present a systematic comparison of test suites generated by the ChatGPT LLM and the state-of-the-art SBST tool EvoSuite. Our comparison is based on several critical factors, including correctness, readability, code coverage, and bug detection capability. By highlighting the strengths and weaknesses of LLMs (specifically ChatGPT) in generating unit test cases compared to EvoSuite, this work provides valuable insights into the performance of LLMs in solving software engineering problems. Overall, our findings underscore the potential of LLMs in software engineering and pave the way for further research in this area.

cs.SE↗

arXiv2023

Vision Transformer with Attention Map Hallucination and FFN Compaction

Vision Transformer(ViT) is now dominating many vision tasks. The drawback of quadratic complexity of its token-wise multi-head self-attention (MHSA), is extensively addressed via either token sparsification or dimension reduction (in spatial or channel). However, the therein redundancy of MHSA is usually overlooked and so is the feed-forward network (FFN). To this end, we propose attention map hallucination and FFN compaction to fill in the blank. Specifically, we observe similar attention maps exist in vanilla ViT and propose to hallucinate half of the attention maps from the rest with much cheaper operations, which is called hallucinated-MHSA (hMHSA). As for FFN, we factorize its hidden-to-output projection matrix and leverage the re-parameterization technique to strengthen its capability, making it compact-FFN (cFFN). With our proposed modules, a 10$\%$-20$\%$ reduction of floating point operations (FLOPs) and parameters (Params) is achieved for various ViT-based backbones, including straight (DeiT), hybrid (NextViT) and hierarchical (PVT) structures, meanwhile, the performances are quite competitive.

cs.CV↗

arXiv2022

A New Position Calibration Method for MUSER Images

The Mingantu Spectral Radioheliograph (MUSER), a new generation of solar dedicated radio imaging-spectroscopic telescope, has realized high-time, high-angular, and high-frequency resolution imaging of the sun over an ultra-broadband frequency range. Each pair of MUSER antennas measures the complex visibility in the aperture plane for each integration time and frequency channel. The corresponding radio image for each integration time and frequency channel is then obtained by inverse Fourier transformation of the visibility data. In general, the phase of the complex visibility is severely corrupted by instrumental and propagation effects. Therefore, robust calibration procedures are vital in order to obtain high-fidelity radio images. While there are many calibration techniques available -- e.g., using redundant baselines, observing standard cosmic sources, or fitting the solar disk -- to correct the visibility data for the above-mentioned phase errors, MUSER is configured with non-redundant baselines and the solar disk structure cannot always be exploited. Therefore it is desirable to develop alternative calibration methods in addition to these available techniques whenever appropriate for MUSER to obtain reliable radio images. In the case that a point-like calibration source containing an unknown position error, we have for the first time derived a mathematical model to describe the problem and proposed an optimization method to calibrate this unknown error by studying the offset of the positions of radio images over a certain period of the time interval. Simulation experiments and actual observational data analyses indicate that this method is valid and feasible. For MUSER's practical data the calibrated position errors are within the spatial angular resolution of the instrument. This calibration method can also be used in other situations for radio aperture synthesis observations.

astro-ph.IM↗