arXiv subjects

Junwei Liu

Publications and source records attributed to Junwei Liu.

At least 19 recordsLinked to original sources

arXiv2026

Intrinsic anomalous Hall response in the bilayer kagome ferromagnet Co$_3$Sn

Transition-metal kagome magnets provide a rich platform for investigating the interplay between layer stacking, magnetic order, and band topology. Here, we report the molecular beam epitaxy and experimental investigation of high-quality thin films of the kagome metal Co$_3$Sn, which has not been synthesized in bulk form yet. Structural and chemical analyses confirm a hexagonal lattice structure ($P6_3/mmc$) composed of direct A-B stacked Co$_3$Sn kagome bilayers. Magnetometry reveals robust easy-plane ferromagnetism with a Curie temperature exceeding $300\,\text{K}$. Magneto-transport measurements demonstrate metallic behavior (carrier density $n\approx5.01\times10^{22}\,\text{cm}^{-3}$) alongside a temperature-independent anomalous Hall conductivity of $\sigma_{\rm AHE}\approx90\,\Omega^{-1}\cdot{\rm cm}^{-1}$, extending from $2\,\text{K}$ up to room temperature. Results from first-principles density functional theory calculations attribute this anomalous Hall response to intrinsic Berry curvature hotspots near the Fermi level in the spin-split band structure. Our results establish Co$_3$Sn as a room-temperature kagome ferromagnet and highlight the impact of the layer stacking sequence on the material properties of kagome metals from the CoSn family.

cond-mat.mtrl-sci↗

arXiv2026

ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering

Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many open-ended medical questions lack comparably cheap outcome verifiers: responses may be partly correct, incomplete, or contain clinically consequential errors. Rubrics written or validated by physicians offer strong clinical grounding, but involving experts in every instance is costly. Model-generated rubrics make this supervision scalable. We introduce ConRub-Med to preserve useful distinctions as rubric feedback moves from construction to policy optimization. For each prompt, three heterogeneous language models propose atomic criteria independently; a separate model reviews them, retaining only criteria with semantic support from all three generators. Three-State scoring distinguishes correct coverage, missing information, and incorrect claims. Errors receive negative rather than zero credit. When every response in a complete Group Relative Policy Optimization (GRPO) group receives the same final reward, a pairwise judge provides sequence advantages only if both candidate orders agree, without changing the scalar rewards. Groups without ties use vanilla GRPO. In a blinded study matched by question, two medical experts rate panels from the full pipeline as more clinically relevant than panels produced by one generator. Across the evaluated open models, ConRub-Med ranks first on six of nine benchmarks and achieves the highest medical and generalization averages. Using the resulting rubric dataset of 5,166 prompts, it scores $38.98 \pm 1.04$ (mean $\pm$ SD) on HealthBench-Hard, compared with InfiMed-ORBIT's 33.60 with 8,000 samples and 37.30 with 28,000.

cs.CL↗

arXiv2026

Conditional Diffusion for Nonparametric Instrumental Variable Quantile Regression

This work proposes deep nonparametric Instrumental variable quantile regression (IVQR), a two-stage estimator that combines conditional diffusion modeling with a kernel-smoothed conditional moment formulation. In the first stage, we estimate the joint conditional distribution of the outcome and endogenous covariates given the instrument using a variance-preserving conditional diffusion model. In the second stage, we approximate the conditional moment operator through Monte Carlo sampling and a kernel-smoothed surrogate for the indicator function, and then estimate the structural quantile function by empirical risk minimization over deep neural networks. We establish an excess-risk bound for the proposed estimator and derive end-to-end total variation guarantees for the conditional diffusion model under unbounded support, explicitly accounting for score estimation, early stopping, and discretization errors. Our theory is developed under a polynomial-tail envelope on the data distribution and degenerates continuously to the exponential setting: as the tail index grows, the obtained excess-risk rate converges to the minimax-optimal rate of nonparametric regression, thus our heavy-tailed theory covers the classical light-tailed nonparametric guarantees as a limiting case. Simulation studies and a real-data application demonstrate that the proposed method outperforms existing nonparametric IVQR approaches, with gains that become increasingly pronounced as the dimensionality of the covariates and instruments increases.

stat.ML↗

arXiv2026

Discovery of a symmetry-driven electronic cascade in a $d$-wave altermagnet

Altermagnets host magnetic compensation together with non-relativistic spin-split bands, a coexistence enabled by crystal symmetry. Yet whether and how crystal symmetry organizes collective electronic order remains largely unexplored. Here we uncover a symmetry-driven cascade of finite-$q$ charge order in a $d$-wave altermagnet Rb$_{1-{\delta}}$V$_2$Te$_2$O, using phase-resolved scanning tunneling microscopy. A primary density-wave instability drives an initial electronic reconstruction, followed by the emergence of a nematic component and an off-axis modulation with wave vectors geometrically tied to the preceding orders. Phase-resolved spectroscopy distinguishes these components through separate contrast-inversion energies and maps out branch-selective spectral-weight redistribution within the off-axis mode. Together with doping and temperature evolution, these observations establish a highly coordinated hierarchy of coupled density-wave instabilities, consistent with successive symmetry lowering. This multi-component hierarchy can be well described in the Landau framework through sequential softening of the charge orders, where bilinear coupling to their compatible octupolar partners at the lower-symmetry stages enables mutual stabilization within an intertwined charge-multipole state. Such a transparent realization of a charge-order cascade shows how altermagnetic symmetry can extend beyond band formation to organize collective electronic order, offering a new perspective on emergent many-body states in correlated quantum materials.

cond-mat.mes-hall↗

arXiv2026

MinInter: Minimizing Trajectory Interpolation During Data Augmentation for Imitation Learning

Imitation learning enables robots to acquire complex manipulation skills from demonstrations, but its effectiveness is limited by the cost of collecting high-quality data. Trajectory-level data augmentation methods alleviate this challenge by recombining expert demonstrations under varied initial states. However, such methods typically insert interpolations or other non-expert transition segments between disjoint parts, and such non-expert segments could reduce the quality of the generated data. This paper introduces Minimizing Interpolation (MinInter), an effective trajectory selection method that, for each sampled initial configuration, chooses the source demonstration requiring the least interpolation to form a complete trajectory. By explicitly minimizing interpolations during data generation, MinInter produces higher-quality synthetic demonstrations while remaining compatible with existing data generation frameworks. Experiments on 12 manipulation tasks with 26 variants from the MimicGen benchmark show that MinInter consistently improves both data generation success rates and policy success rates, with the largest gains on contact-rich, long-horizon and high-variance settings. Compared to the recent SkillGen framework, MinInter achieves higher policy success rates despite its conceptual simplicity, underscoring the value of interpolation minimization for data augmentation.

cs.RO↗

arXiv2026

Ising Dirac fermions across a topological phase transition

Dirac fermions have attracted significant interest due to their relativistic dispersions and close connections to topological physics, yet they are generally expected to be gapped in two-dimensional systems with strong Ising spin orbit coupling, making their realization in such materials an outstanding challenge. Here we report the emergence of six fold degenerate Dirac fermions in an Ising moire system across a quantum spin Hall transition in twisted WSe2. In a 3.65 degree device, we observe a quantum spin Hall phase at high electric fields with nearly quantized resistance h/(2e2), and a Dirac semimetal phase over a broad range of electric fields near zero field. Magnetotransport measurements of the Dirac phase exhibit a half-integer Landau fan sequence, characteristic of Dirac fermions, with six-fold degeneracy on the hole-doped side and two fold degeneracy on the electron-doped side. Temperature dependence shows weakly metallic behavior consistent with a semimetallic state. Our twist-angle-dependent transport measurements map out a complete phase diagram and identify a critical twist angle of 3.3 degree, establishing the phase boundary between the quantum spin Hall and Dirac semimetal regimes. Our work establishes a new route to realizing Dirac fermions in strongly spin orbit coupled moire systems through a topological phase transition, providing a promising platform for high mobility spintronics.

cond-mat.mes-hall↗

arXiv2026

Excitonic-Superconducting Coexistence and Emergent Nematic Superconductivity Driven by Spontaneous Symmetry Breaking

Excitonic insulating (EI) and superconducting (SC) orders are generally regarded as mutually exclusive electronic instabilities. Within a self-consistent microscopic theory, we study electronic systems hosting an EI phase in the presence of SC pairing and show that an intrinsic mismatch between electron and hole Fermi surfaces fundamentally reshapes this competition. This mismatch stabilizes FFLO-like electron-hole pairing and drives spontaneous symmetry breaking of the EI state. The resulting symmetry breaking reconstructs the pairing phase space for SC and EI state, such that different regions of the Fermi surface complementarily support either EI or SC correlations, leading to a natural coexistence of the two orders. Notably, the emergent SC state consequently breaks rotational symmetry and develops intrinsic nematic superconductivity, even in the absence of explicit symmetry-breaking fields (such as magnetic fields, spin-orbit coupling, or bare band-structure anisotropy). Our results suggest that candidate materials such as monolayer 1T$'$-MoTe$_2$ and the square-net semimetal NaAlSi may provide promising platforms for observing this phenomenon. More broadly, these findings reveal a unique mechanism by which competing many-body orders generate electronic nematicity, suggesting a broader route toward spontaneous anisotropic electronic states in correlated quantum materials.

cond-mat.supr-con↗

arXiv2026

Odd spin symmetry and anisotropy switching in p-wave magnet CeNiAsO

Odd-parity magnets, complementary to altermagnets, exhibit unique properties such as high efficiency in charge-spin conversion and compatibility with conventional superconductivity, of critical importance in the pursuit of energy-efficient spintronics and topological superconductors for quantum computation. For even-parity d-wave and g-wave altermagnets, the magnetic structure, spin-split band structure and physical properties are currently under intensive study. On the contrary, while hundreds of odd-parity magnets and the promising properties have been predicted in theory, experimental studies are scarce. Specifically, the magnetic structure and transport properties of candidates NiI2 and Ga3Ru4Al12 have been reported, yet the characteristic band structure and particularly the odd-parity spin symmetry remain elusive. Here we demonstrate experimentally the deterministic p-wave spin symmetry and resistance anisotropy switching for the prototype odd-parity magnet, CeNiAsO. Angle-resolved photoemission spectroscopy (ARPES) reveals two cleaved terminations with distinct surface band structure. By compensating the polar surface, we achieve intrinsic bulk band structure, for which the spin splitting can be well described by the p-wave magnetic structure through first-principles calculation. The bulk spin polarization measured by spin-resolved ARPES exhibits symmetry with only one degenerate plane, fingerprint of p-wave magnetism. We further demonstrate giant resistance anisotropy and switching between high-resistance and low-resistance states through modest field-induced domain selection, highlighting its potential for antiferromagnetic spin memory devices. The structural similarity between CeNiAsO and 1111-type Fe-based superconductors stimulates further exploration on the interplay between p-wave magnetism, superconductivity and band topology.

cond-mat.str-el↗

arXiv2026

Ultrafast Magneto-optical Fingerprints of Altermagnetism in MnTe

Recently identified altermagnets exhibit a distinctive dual-space nature: they possess spin-split electronic bands akin to ferromagnets in momentum space while maintaining the fully compensated magnetization of antiferromagnets in real space. This inherent duality, originating from the same crystal symmetry, gives rise to various intriguing physical phenomena unique to altermagnets. Consequently, a robust and efficient experimental signature capable of revealing this dual character is critically needed. The magneto-optical Kerr and Voigt effects, given their high sensitivity to ferromagnetism and antiferromagnetism, respectively, are ideally suited to probe this duality. Here, using time-resolved pump-probe magneto-optical measurements, we report the coexistence of pronounced Kerr and Voigt effects in the altermagnet MnTe. Combining the magnetization measurement and first-principles calculations, we demonstrate that the Kerr effect originates from the intrinsic Berry curvature of altermagnetism distribution in momentum space, while the Voigt effect arises from an anisotropic permittivity induced by the in-plane N\'eel order in real space, directly revealing the dual-space nature of altermagnets. Furthermore, the transient Kerr signal exhibits faster relaxation dynamics than the transient Voigt signal, underscoring their distinct origins in Berry curvature and N\'eel order, respectively. These findings establish transient magneto-optical responses as distinctive fingerprints of altermagnetism and position altermagnets as promising platforms for manipulating magneto-optical phenomena in ultrafast spin optoelectronics.

cond-mat.mtrl-sci↗

arXiv2026

Observation of a Mott quantum spin Hall insulator in twisted WSe2

Quantum spin Hall (QSH) insulators and Mott insulators are conventionally regarded as distinct insulating phases, arising from band topology and strong Coulomb interactions, respectively. Here, we report the observation of QSH edge transport in a magnetic-field-stabilized Mott insulating state at half filling of the second moire band in a 2.29 degree twisted WSe2 device. This state exhibits a resistance plateau identical to that of the single-particle QSH state at full filling of the first moire valence band, indicating the same number of helical edge channels. Electrical transport measurements reveal nearly quantized resistance that is insensitive to vertical electric field, out-of-plane magnetic field, and temperature below 5 K. Pronounced nonlocal transport and strong negative in-plane magnetoconductance further support helical edge conduction, establishing robust edge transport in the strongly correlated regime. Temperature-dependent Hall measurements reveal a characteristic temperature scale of approximately 10 K, corresponding to an energy scale of about 1 meV. Our results demonstrate that spin-conserved QSH edge states can persist in a half filled, strongly correlated insulating phase and under external magnetic field, opening a route toward interaction-resilient topological transport in moire quantum materials.

cond-mat.mes-hall↗

arXiv2026

Distinguishing and Separating In-Plane Hall Responses

Electric Hall effects generated by an in-plane magnetic field have recently gained attention owing to their intrinsic origin in topological electronic states and potential application in magnetic field sensing. In pratice, the measured transverse electric voltage typically combines contributions from multiple phenomena, such as anisotropy and Berry curvature effects, leading to interpretative ambiguities of the measurement signal. Here, we introduce a universal framework that disentangles these contributions via their distinct field-reversal symmetries and angular dependencies. Leveraging a 12-terminal Hall bar for independent control of the electric and in-plane magnetic field directions, we exemplify this method by analyzing the transverse electric voltage recorded on the the ferromagnetic Weyl semimetal Fe3Sn in an in-plane geometry. The standardized approach presented in this work will guide future studies of in-plane Hall responses in magnetic and topological materials.

cond-mat.mes-hall↗

arXiv2026

Direct observation of quadruple spin-texture locking in a 2D d-wave altermagnet

Altermagnets combine vanishing net magnetization with nonrelativistic, momentum-dependent spin splitting, offering a new paradigm for spintronics. Spin-crystal symmetry coupling, namely spin-lattice locking, is the defining mechanism of altermagnetism, enforcing opposite spin sublattices in real space and spin-momentum-locked electronic structure in reciprocal space. Direct atomic-scale visualization of spin-lattice locking therefore constitutes a decisive benchmark of the altermagnetic state, yet such evidence has remained elusive despite extensive efforts. Here we show that the electronic states in RbV2Se2O exhibit a d-wave-like spin texture at the sublattice level, providing the first atomic-scale evidence of spin-lattice locking with a predominantly c-axis spin orientation. By employing an in-situ, field-switchable spin-polarized Cr tip, we realize spin-contrast mapping of quasiparticle interference at identical energies, overcoming a long-standing experimental barrier in altermagnets. The resulting interference patterns exhibit pronounced spin-dependent modulations, establishing spin scattering locking and spin momentum locking as the real and reciprocal space manifestations. Unexpectedly, we uncover that the spin-selective scattering response is organized by a long-period stripe modulation, giving rise to a previously unidentified form of spin-texture locking, spin-stripe locking. We attribute this behavior to the emergence of a spin-density-wave moir\'e pattern. Together, these results establish a unified picture of quadruple spin-texture locking phenomena in a d-wave altermagnet, and position altermagnets as a versatile platform for exploring many-body interactions among intertwined degrees of freedom, including spin, lattice, momentum, moir\'e potential and valley.

cond-mat.mtrl-sci↗

arXiv2026

Does Pass Rate Tell the Whole Story? Evaluating Design Constraint Compliance in LLM-based Issue Resolution

Repository-level issue resolution benchmarks have become a standard testbed for evaluating LLM-based agents, yet success is still predominantly measured by test pass rates. In practice, however, acceptable patches must also comply with project-specific design constraints, such as architectural conventions, error-handling policies, and maintainability requirements, which are rarely encoded in tests and are often documented only implicitly in code review discussions. This paper introduces \textit{design-aware issue resolution} and presents \bench{}, a benchmark that makes such implicit design constraints explicit and measurable. \bench{} is constructed by mining and validating design constraints from real-world pull requests, linking them to issue instances, and automatically checking patch compliance using an LLM-based verifier, yielding 495 issues and 1,787 validated constraints across six repositories, aligned with SWE-bench-Verified and SWE-bench-Pro. Experiments with state-of-the-art agents show that test-based correctness substantially overestimates patch quality: fewer than half of resolved issues are fully design-satisfying, design violations are widespread, and functional correctness exhibits negligible statistical association with design satisfaction. While providing issue-specific design guidance reduces violations, substantial non-compliance remains, highlighting a fundamental gap in current agent capabilities and motivating design-aware evaluation beyond functional correctness.

cs.SE↗

arXiv2026

A Unified Theory of Deterministic Magnetic Switching

The deterministic switching of magnetic order parameters is critically important, as it forms the fundamental basis for manipulating information states in magnetic memory devices. This work presents a general theoretical framework that unifies the mechanisms of magnetic switching by introducing the concept of switching symmetry and establishing that the necessary condition for deterministic switching is the breaking of all switching symmetries, which can be achieved through asymmetric states, asymmetric barriers, and asymmetric torques. Our theory can successfully and universally explain all reported experimental cases of deterministic magnetic switching and provides unified and simple design principles for new switching devices of all magnetic materials without the need of complicated simulations.

cond-mat.other↗

arXiv2026

PulseMind: A Multi-Modal Medical Model for Real-World Clinical Diagnosis

Recent advances in medical multi-modal models focus on specialized image analysis like dermatology, pathology, or radiology. However, they do not fully capture the complexity of real-world clinical diagnostics, which involve heterogeneous inputs and require ongoing contextual understanding during patient-physician interactions. To bridge this gap, we introduce PulseMind, a new family of multi-modal diagnostic models that integrates a systematically curated dataset, a comprehensive evaluation benchmark, and a tailored training framework. Specifically, we first construct a diagnostic dataset, MediScope, which comprises 98,000 real-world multi-turn consultations and 601,500 medical images, spanning over 10 major clinical departments and more than 200 sub-specialties. Then, to better reflect the requirements of real-world clinical diagnosis, we develop the PulseMind Benchmark, a multi-turn diagnostic consultation benchmark with a four-dimensional evaluation protocol comprising proactiveness, accuracy, usefulness, and language quality. Finally, we design a training framework tailored for multi-modal clinical diagnostics, centered around a core component named Comparison-based Reinforcement Policy Optimization (CRPO). Compared to absolute score rewards, CRPO uses relative preference signals from multi-dimensional com-parisons to provide stable and human-aligned training guidance. Extensive experiments demonstrate that PulseMind achieves competitive performance on both the diagnostic consultation benchmark and public medical benchmarks.

cs.CV↗

arXiv2026

MLB: A Scenario-Driven Benchmark for Evaluating Large Language Models in Clinical Applications

The proliferation of Large Language Models (LLMs) presents transformative potential for healthcare, yet practical deployment is hindered by the absence of frameworks that assess real-world clinical utility. Existing benchmarks test static knowledge, failing to capture the dynamic, application-oriented capabilities required in clinical practice. To bridge this gap, we introduce a Medical LLM Benchmark MLB, a comprehensive benchmark evaluating LLMs on both foundational knowledge and scenario-based reasoning. MLB is structured around five core dimensions: Medical Knowledge (MedKQA), Safety and Ethics (MedSE), Medical Record Understanding (MedRU), Smart Services (SmartServ), and Smart Healthcare (SmartCare). The benchmark integrates 22 datasets (17 newly curated) from diverse Chinese clinical sources, covering 64 clinical specialties. Its design features a rigorous curation pipeline involving 300 licensed physicians. Besides, we provide a scalable evaluation methodology, centered on a specialized judge model trained via Supervised Fine-Tuning (SFT) on expert annotations. Our comprehensive evaluation of 10 leading models reveals a critical translational gap: while the top-ranked model, Kimi-K2-Instruct (77.3% accuracy overall), excels in structured tasks like information extraction (87.8% accuracy in MedRU), performance plummets in patient-facing scenarios (61.3% in SmartServ). Moreover, the exceptional safety score (90.6% in MedSE) of the much smaller Baichuan-M2-32B highlights that targeted training is equally critical. Our specialized judge model, trained via SFT on a 19k expert-annotated medical dataset, achieves 92.1% accuracy, an F1-score of 94.37%, and a Cohen's Kappa of 81.3% for human-AI consistency, validating a reproducible and expert-aligned evaluation protocol. MLB thus provides a rigorous framework to guide the development of clinically viable LLMs.

cs.LG↗

arXiv2026

Observation of spin-valley locked nodal lines in a quasi-2D altermagnet

The interplay among quantum degrees of freedom-spin, orbital and momentum-has emerged as a fertile ground for realizing magnetic quantum states with transformative potential for electronic and spintronic technologies. Prominent examples include ferromagnetic Weyl semimetals and antiferromagnetic axion insulators. Recently, altermagnets(AMs) have been identified as a distinct spin-splitting class of collinear antiferromagnets(AFMs), characterized by crystal symmetry that connects magnetic sublattices in real space and enforces C-paired spin-momentum locking in reciprocal space. These materials combine the advantages of nonrelativistic spin-polarization akin to FMs and vanished net-magnetization as AFMs, making them highly promising for spintronic applications. Furthermore, they introduce nontrivial spin-momentum locking spin texture as an additional degree of freedom for realizing novel quantum phases. In this work, we report the discovery of a new type of spin-valley-locked nodal line phase in the layered AM Rb-intercalated V{_2}Te{_2}O. By combining high-resolution spin and angle-resolved photoemission spectroscopy with first-principles calculations, we observe the coexistence of both spinless and spinful nodal lines near the Fermi level. Remarkably, the spinful nodal lines exhibit uniform spin polarization within each valley, while displaying opposite spin polarizations across symmetry-paired valleys-a unique feature we term spin-valley-locked nodal lines, which is exclusive to AMs. Direct measurements of out-of-plane band dispersion using a side-cleaving technique reveal the two-dimensional nature of these nodal lines. Our findings not only unveil a previously unexplored topological phase in AMs where valley-locked spin as an additional quantum character but also establish RbV{_2}Te{_2}O as a promising platform for spintronics, valleytronics, and moire-engineered quantum devices.

cond-mat.mtrl-sci↗

arXiv2026

MedDialogRubrics: A Comprehensive Benchmark and Evaluation Framework for Multi-turn Medical Consultations in Large Language Models

Medical conversational AI (AI) plays a pivotal role in the development of safer and more effective medical dialogue systems. However, existing benchmarks and evaluation frameworks for assessing the information-gathering and diagnostic reasoning abilities of medical large language models (LLMs) have not been rigorously evaluated. To address these gaps, we present MedDialogRubrics, a novel benchmark comprising 5,200 synthetically constructed patient cases and over 60,000 fine-grained evaluation rubrics generated by LLMs and subsequently refined by clinical experts, specifically designed to assess the multi-turn diagnostic capabilities of LLM. Our framework employs a multi-agent system to synthesize realistic patient records and chief complaints from underlying disease knowledge without accessing real-world electronic health records, thereby mitigating privacy and data-governance concerns. We design a robust Patient Agent that is limited to a set of atomic medical facts and augmented with a dynamic guidance mechanism that continuously detects and corrects hallucinations throughout the dialogue, ensuring internal coherence and clinical plausibility of the simulated cases. Furthermore, we propose a structured LLM-based and expert-annotated rubric-generation pipeline that retrieves Evidence-Based Medicine (EBM) guidelines and utilizes the reject sampling to derive a prioritized set of rubric items ("must-ask" items) for each case. We perform a comprehensive evaluation of state-of-the-art models and demonstrate that, across multiple assessment dimensions, current models face substantial challenges. Our results indicate that improving medical dialogue will require advances in dialogue management architectures, not just incremental tuning of the base-model.

cs.CL↗