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Junwei Liu

Publications and source records attributed to Junwei Liu.

At least 19 recordsLinked to original sources
arXiv2026

MedResearcher-R1: Expert-Level Medical Deep Researcher via A Knowledge-Informed Trajectory Synthesis Framework

Large Language Model (LLM)-based agents have recently demonstrated remarkable capabilities in deep research tasks, yet their application to the medical domain remains challenging. The leading proprietary systems achieve only modest results on complex medical benchmarks. This exposes two key bottlenecks: (i) limited clinical-reasoning capability in the underlying model, and (ii) unreliable access to authoritative medical evidence when constrained to open-web retrieval. To address these limitations and equip agents with robust clinical reasoning capabilities, we present MedResearcher-R1, a medical deep research agent featuring two core innovations. First, we propose Knowledge-Informed Trajectory Synthesis (KISA), a novel approach that builds medical knowledge graphs to construct complex multi-hop question-answer pairs centered on rare medical entities, overcoming the scarcity of high-quality domain-specific training data. Second, we integrate a medical retrieval engine alongside general-purpose tools, enabling precise and reliable synthesis of medical evidence. Through this methodology, we yield over 2,100 diverse trajectories spanning 12 medical specialties. Trained with supervised fine-tuning and reinforcement learning, our MedResearcher-R1-32B achieves state-of-the-art performance on MedBrowseComp (27.5/50 vs. 25.5/50 for o3-deepresearch) while demonstrating strong general performance on GAIA and xBench benchmarks. To the best of our knowledge, we present the first high-quality, tool-augmented medical dataset paired with a domain-specialized deep-research agent, demonstrating that smaller open-source models can surpass substantially larger proprietary systems on specialized medical tasks.

cs.CL↗
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

LapaFM: A Laparoscopic Foundation Model via Multi-Stage Continual Learning

Artificial intelligence-based analysis of intraoperative laparoscopic videos has the potential to improve surgical decision-making and precision. However, effective surgical assistance requires models that can generalize across diverse intraoperative tasks. Here we present LapaFM, a foundation model for laparoscopic surgery trained on more than 20,000 minutes of surgical videos using a multi-stage continual learning strategy that mitigates catastrophic forgetting and inter-task interference. LapaFM learns multimodal visual representations and supports multiple tasks, including smoke removal, surgical phase recognition, instrument and polyp segmentation, and lesion identification. The model was evaluated on 13 retrospective and two prospective cohorts collected from different imaging devices. LapaFM consistently outperformed task-specific models and existing foundation models across datasets, and also generalized to gastrointestinal endoscopy tasks, including polyp detection and classification. Notably, it recovered over 90% of smoke-obscured frames and achieved clinician-level or superior performance in lymph node metastasis prediction and prospective polyp classification.

cs.CV↗
arXiv2026

Hidden Staggered Superconducting Order in V2Se2O-Family Altermagnets

$η$ pairing describes a staggered superconducting condensate whose order parameter changes sign between neighboring unit cells while maintaining a uniform magnitude. Nearly four decades after its theoretical proposal by C. N. Yang, a material platform for stabilizing $η$ pairing has remained elusive. Here, we reveal that altermagnetism, despite being pair breaking for conventional BCS pairing, naturally favors $η$-like pairing in V$_2$Se$_2$O-family altermagnets. Their valley-contrasting spin structure gives rise to oppositely spin-polarized, symmetry-related valleys centered at $X=(π,0)$ and $Y=(0,π)$, which form spin-singlet pairing partners separated by the commensurate momentum $\mathbf Q=(π,π)$, thereby favoring an $η$-like condensate. Self-consistent calculations demonstrate that the resulting $η$-like state remains robust over broad variations of chemical potential, hopping parameters, and Fermi-surface topology. To detect this hidden staggered order, we propose a phase-sensitive Josephson measurement with a uniform superconductor, where destructive interference suppresses single-Cooper-pair tunneling while preserving two-Cooper-pair processes. This constitutes a charge-$4e$-like Josephson response despite a bulk condensate composed of charge-$2e$ Cooper pairs, providing a direct phase-sensitive signature of the otherwise elusive $η$-like condensate in V$_2$Se$_2$O-family altermagnets.

cond-mat.supr-con↗
arXiv2026

Where Does the Performance Go? Understanding and Recovering Performance Regressions in C-to-Rust Translation

Rust is increasingly adopted as a memory-safe successor to C, and transpilers such as \crust{} can migrate entire C projects while preserving their behavior. Preserving behavior, however, does not guarantee preserving performance. We study this gap on 20 real-world C projects and their \crust{} translations. On the eight projects used for analysis, the translated Rust is more than 3\% slower than the original C on 12 of 19 operations, by up to 62.2\%. By comparing execution-cost profiles, optimized LLVM IR, and compiler optimization remarks across each C--Rust pair, we trace these slowdowns to nine recurring performance issues, spanning residual runtime work, missed compiler optimizations, and C-style source patterns, and derive an optimization direction for each. We then present \ourtool{}, an LLM-based approach that encodes these issues as reusable optimization rules to recover the performance of translated Rust. \ourtool{} profiles each project to locate hot functions and matches them against rule-specific patterns. The LLM then checks each rule's rewrite preconditions against the project context before rewriting, and a rewrite is kept only if it passes both functional and performance validation. On 41 operations from twelve held-out projects, \ourtool{} preserves C outputs on all tested workloads and speeds up 40 operations over the \crust{} translations, 18 of which end up faster than the original C. It outperforms the general-purpose coding agent \codex{} on 31 of the 37 operations where both preserve C outputs, and outperforms its own variant without rule guidance on 34 of the 41 operations.

cs.AI↗
arXiv2026

Chemical-Potential-Dependent Superconducting Spectroscopy on Bi2Te3/NbSe2 Heterostructures

High-resolution scanning tunneling spectroscopy performed at dilution refrigerator temperatures was employed to investigate the superconducting properties of topological insulator/superconductor (Bi2Te3/NbSe2) heterostructures. Coherence peaks with inner kinks or inner peaks, deviating from the conventional single s-wave spectral line shape, were observed in both 5 quintuple-layer (5QL) and 7QL Bi2Te3 thin films. Based on the combination of chemical-potential-dependent spectroscopic measurements and model simulations, we conclude that these spectral features arise from contributions of bulk and surface states in Bi2Te3 by selectively proximity-coupled to a single superconducting gap from NbSe2, rather than inheriting the complicated superconductor's order parameter of NbSe2.

cond-mat.supr-con↗
arXiv2026

Emergent magnetic nonanalyticity in Dirac altermagnets

Symmetry has long provided the organizing principle for understanding how materials respond to external perturbations. Here we show that what is permitted by symmetry need not be what actually emerges from the underlying system, and this distinction becomes particularly consequential for symmetry-related gapless Dirac fermions such as in altermagnets. A perturbation that shifts the Dirac points drives a Lifshitz reconstruction and generates an intrinsically nonanalytic effective potential, giving rise to undiscovered singular responses. In Dirac altermagnets, this nonanalyticity acquires a magnetic manifestation through $C$-paired spin-polarized Dirac cones: breaking the pairing symmetry $C$ lifts their degeneracy and converts the associated Lifshitz reconstruction into an itinerant magnetization. As a consequence, piezomagnetism, the induction of a net magnetization by a mechanical strain, becomes nonlinear and nonanalytic, with $M\propto\mathrm{sgn}(\varepsilon)\varepsilon^2$, whereas the linear response is absent despite being allowed by symmetry. Accordingly, the leading response cannot be inferred from the conventional symmetry-based paradigm of material response built upon the cornerstones of Neumann's principle and analytic Landau expansion. First-principles calculations identify the monolayer Fe$_2$S as a candidate material realization for such singular magnetic responses. These results suggest quantum singularities as a new degree of freedom for engineering material responses.

cond-mat.mtrl-sci↗
arXiv2026

Correlation-driven quantum geometry effects in a Kondo system

Quantum geometry, including quantum metric and Berry curvature, which describes the topology of electronic states, can induce fascinating physical properties. Symmetry-dependent nonlinear transport has emerged as a sensitive probe of these quantum geometric properties. However, its interplay with strong electronic correlations has rarely been explored in bulk materials, particularly in a Kondo lattice system. Here, we uncover correlation-driven quantum geometry in centrosymmetric antiferromagnetic iron telluride (FeTe). We experimentally observe the quantum metric quadrupole-induced third-order nonlinear transport, whose angular dependence reflects magnetic structure in FeTe. The nonlinear transport signals follow Kondo lattice crossover and vanish at high temperatures. Our theory suggests that a Kondo lattice formed at low temperatures explains the emergence of quantum geometry, which is induced by the opening of a hybridization gap near the Fermi energy. This discovery establishes a paradigm where quantum geometry arises not from static symmetry breaking but from dynamic many-body effects and provides a zero-field probe for sensing antiferromagnetic order.

cond-mat.str-el↗
arXiv2026

B-type Quadratic Planar Hall Effect as a Probe of Altermagnetic Order

Conventional transport and optical responses, such as the Hall effect, can only distinguish material phases with substantially different symmetries. However, many quantum materials, such as candidate altermagnetic materials, host competing phases with similar structures, making it difficult to differentiate them using conventional transport or optical measurements. Here, guided by symmetry principles, we introduce a B-type quadratic planar Hall effect (B2-PHE) as a sensitive probe of magnetic structures. B2-PHE features a planar Hall current that scales quadratically with the applied magnetic field. This response originates from the interplay among external magnetic fields, intrinsic magnetic order, and quantum geometric properties of the electronic bands. We investigate B2-PHE in two altermagnetic candidates, KV2Se2O and RuO2, whose ground-state magnetic orders are under intense debate. Remarkably, B2-PHE emerges in their altermagnetic phases but is symmetry-forbidden in their antiferromagnetic (nonmagnetic) phases. We also show that B2-PHE should be detectable under a moderate magnetic field on the order of 1 Tesla. These findings establish B2-PHE as an experimentally convenient and potentially unambiguous probe of altermagnetic order, which is otherwise difficult to realize.

cond-mat.mtrl-sci↗
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 $σ_{\rm AHE}\approx90\,Ω^{-1}\cdot{\rm cm}^{-1}$, 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$_{1-δ}$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

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

Towards Iterative End-to-End Software Development: A Feature-Driven Multi-Agent Framework

Recent advances in large language model agents offer the promise of automating end-to-end software development from natural language requirements. However, existing approaches largely adopt linear, waterfall-style pipelines, which oversimplify the iterative nature of real-world development and struggle with complex, large-scale projects. To address these limitations, we propose EvoDev, an iterative software development framework inspired by feature-driven development. EvoDev decomposes user requirements into a set of user-valued features and constructs a Feature Map, a directed acyclic graph that explicitly models dependencies between features. Each feature node in the feature map maintains multi-layer contexts, including business logic, software design, and code implementation, which are propagated along dependencies to provide context for subsequent development iterations. We evaluate EvoDev on challenging Android development tasks and show that it outperforms the best-performing baseline, Claude Code, by 57.3%, while improving single-agent performance by 16.0%-58.5% across different base LLMs, highlighting the importance of feature decomposition, dependency modeling, context propagation, and workflow-aware agent design for end-to-end software development. Moreover, our work summarizes practical insights for designing iterative, LLM-driven development frameworks and informs future training of base LLMs to better support iterative software development.

cs.SE↗
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↗