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Jin Cao

Publications and source records attributed to Jin Cao.

At least 19 recordsLinked to original sources

When Core-Network Elements Become Reachable: Field-Level Exploitability Analysis in Diameter

The increasing exposure of cellular core-network elements to public networks has turned Diameter signaling interfaces into a practical attack surface. While large language models (LLMs) show promise for protocol exploitability analysis, we find that their judgments on Diameter can be unreliable because they may deviate from the tacit analysis discipline followed by security experts and reach conclusions without considering complete protocol evidence. To address this challenge, we present LENS, an LLM-based system for reliable field-level Diameter exploitability analysis. LENS guides LLMs using both exploitability-analysis discipline and the protocol evidence needed for analysis. It infers analysis discipline from existing exploit writeups and evidence-collection guidance from exploitability-analysis failures, enabling systematic evidence collection, exploitability assessment, and proof-of-concept (PoC) attack generation when applicable. Our experiments show that LENS performs reliable analysis across four LLMs and repeated runs, achieving mean recall of 94.00% to 98.00%, precision of 78.73% to 88.94%, and accuracy of 84.00% to 92.00%. We find that more than 25% of field paths in the S6a and Cx interfaces are exploitable under the considered threat model. We further assess their impact on practical implementations and uncover 95 previously unknown vulnerabilities, including 17 in open-source EPC/IMS implementations and 78 in commercial deployments, causing service disruption, information leakage, subscriber tracking, and accelerated battery depletion. Applying LENS to 16 additional protocols spanning cellular, network, industrial, and host-internal systems uncovers 118 previously unknown vulnerabilities, demonstrating its strong generalizability.

cs.CR↗

Gauss-Manin connection in disguise: limiting periods and quasi-Jacobi forms

We construct a six-dimensional algebraic moduli space of elliptic curves equipped with two ordered marked points, an enhanced relative de Rham frame, and a nonzero tensor of endpoint tangents. Its normalized period map is a biholomorphism. On the classical period locus, the regular coordinates pull back under its inverse to Weierstrass, Eisenstein, and theta functions. The associated Gauss-Manin vector fields realize differential operators on quasi-Jacobi forms of integer index. To relate this elliptic space to the genus-two construction, we study a specified smoothing family over a five-dimensional space of limiting enhancements. For this family, we identify the regularized period matrix and the boundary pullback of the holomorphic part of the logarithmic connection with respect to the chosen plumbing parameter. We then compute the unit relating the algebraic smoothing parameter to the Siegel period parameter and the limits of the specified genus-two generators. Separately, we express classical Fourier-Jacobi coefficients in enhanced elliptic coordinates.

math.AG↗

Crossed Electric Spin Generation in Multilayers

We propose a crossed electric spin generation effect in multilayer structures. This effect combines the advantages of in-plane and gate electric fields for manipulating spin, and unveils a nice quantum geometric structure in terms of the underlying hybrid Berry curvatures that are unique to quasi-2D systems and manifest inherent spin-layer-orbital coupling. Combining our theory with first-principles calculations, we predict sizable spin generation in 2D ferromagnetic Fe3GeTe2 and altermagnetic V2Te2O. Our theory opens a new Berry-curvature route for all-electric spin manipulation in 2D materials

cond-mat.mtrl-sci↗

Iterated cotangent-difference integrals over totally real cyclotomic fields

We study iterated cotangent integrals with cyclotomic shifts and express their values along specified reference paths in terms of cyclotomic multiple zeta values. Differences of cotangent forms extend to a punctured projective line over a totally real cyclotomic field, giving a family of "real cyclotomic multiple zeta values." With rational tangential endpoints, these difference integrals are periods of mixed Tate motives over that field; integral endpoint data yield periods over its ring of integers after inverting primes dividing the level. The associated framed motivic classes generate a Hopf subalgebra under Goncharov's coproduct.

math.NT↗

Valley Berry curvature dipole induced nonlinear valley Hall effect

Valley Hall effect is a signature effect in the field of valleytronics, and recent studies have pushed this effect into the nonlinear regime. Here, we reveal a previously unexplored type of nonlinear valley Hall effect which arises from a valley Berry curvature dipole (vBCD) mechanism. We show this nonlinear valley Hall effect is forbidden for conventional time-reversal-connected valleys, but is supported in the class of valleytronic systems featuring time-reversal-invariant valleys. The candidate layer groups and detailed symmetry constraints on vBCD are obtained. It shows the nonlinear valley Hall response, as well as the nonlinear charge Hall response, can be well controlled by tuning the driving field direction. We demonstrate our proposal in an effective model study and in a concrete material example, strained Nb$_{3}$SBr$_{7}$, by first-principles calculations. The nonlocal transport signature of this vBCD induced nonlinear valley Hall effect is also discussed.

cond-mat.mes-hall↗

Hybrid-parity sliding multiferroics

In this work, we introduce a class of hybrid-parity sliding multiferroics in which the spontaneous ferroelectric polarization is coupled to certain nonrelativistic spin splitting components through interlayer sliding, allowing these components to be reversibly switched in an electrical way. Symmetry analysis identifies coplanar magnets as natural platforms for realizing this form of sliding multiferroicity. First-principles calculations establish bilayer VBr$_2$ as a representative example, demonstrating the coupled reversal of the out-of-plane ferroelectric polarization and the signs of both even- and odd-parity nonrelativistic spin splitting components via an interlayer-sliding pathway. The signs of these nonrelativistic spin splitting components are locked to the sliding-switchable ferroelectric polarization and encoded in the spin-current responses, providing a signature of the coupled ferroic switching. Our findings expand the scope of sliding multiferroics and the functionality of sliding ferroelectrics for low-energy, nonvolatile logic devices.

cond-mat.mtrl-sci↗

ASTRA - Agentic System for Ticket Resolution and Analysis

Technical operations teams resolve large volumes of incidents by synthesizing fragmented evidence from ticket text, historical cases, system logs, and technical documentation. Existing automation often relies on monolithic generation without explicit evidence modeling or provenance, making outputs difficult to verify when critical signals are sparse across sources. We propose ASTRA, an agentic system for ticket resolution in which a central orchestrator coordinates three specialist information-gathering agents and drives a judge-orchestrator refinement loop to produce evidence-backed troubleshooting reports. TicketSimilarityAgent retrieves relevant historical precedents through dense retrieval and LLM reranking; LogAgent distills hundreds of thousands of log lines into structured, quote-grounded findings using deterministic filtering and constrained LLM analysis; and DomainKnowledgeAgent retrieves relevant technical knowledge via the Model Context Protocol (MCP). Their outputs are transformed into a claim-evidence representation linking each claim to a verbatim source passage, assigning a support level, and preventing cross-attribution. A JudgeAgent scores the report on five criteria, while the OrchestratorAgent converts low scores into targeted follow-up queries for bounded iterative refinement. Evaluated on 987 real-world telecom fault tickets across seven product lines, ASTRA achieves a mean quality score of 4.13/5.0, with 59.9% of reports identifying the fault area at the component-family level or better. Relevance and Clarity scores are 4.88 and 4.94, respectively, while fabricated technical details remain below 3% of error cases. Stratification by fault type reveals that hardware faults remain substantially harder than software or configuration faults (Cohen's d=0.80), pointing to a fundamental limitation of text-based evidence channels for hardware fault diagnosis.

cs.MA↗

TraceGrant: A Contract-Governed Security Framework for the Task-Effect Lifecycle of Networked LLM Agents

Networked large language model (LLM) agents retrieve information from email, cloud storage, calendars, transaction platforms, and Web services to complete multistep tasks that produce persistent external effects. The same content needed for legitimate execution may also contain indirect prompt injections that redirect tool use, alter sensitive arguments, or disrupt task completion. Existing defenses mainly constrain untrusted content or individual tool calls, leaving user intent, runtime evidence, realized effects, and task completion insufficiently connected. We present TraceGrant, a security framework that governs the task-effect lifecycle of networked LLM agents through an explicit Contract. Before execution, TraceGrant establishes a task-effect boundary from the trusted user request. During execution, admitted evidence can instantiate only authority already established by the Contract. After execution, task completion is verified against actual tool results. Across 949 AgentDojo and 400 Agent Security Bench attack cases under fixed benchmark settings, TraceGrant recorded no attack successes while retaining utility under attack rates of 77.32% and 83.00%, respectively. We further evaluate TraceGrant through white-box defense-aware attacks, Contract quality analysis, stage ablations, targeted stress tests, and runtime overhead measurements. The results show that TraceGrant provides a unified governance layer that connects trusted user intent, runtime evidence, concrete tool execution, and verified task completion.

cs.CR↗

ShadowDancer: Teaching Video World Models Any Action by Learning Unified Dynamics Representations from a Video and Its Shadow

We present ShadowDancer, a novel approach to any-action, frame-level control of interactive video world models. The obstacle is representational: existing interfaces either encode an action loosely, leaving how it unfolds for the model to improvise, or encode it exactly through structured signals that serve one family and are hard to acquire, so precise control across diverse dynamics remains impractical. Demonstration videos are the natural remedy, specifying any dynamics frame by frame; yet a video shows its dynamics only through one particular appearance, a single shadow of the underlying dynamics, so actions learned from demonstrations transfer poorly to new scenes. ShadowDancer addresses this with two key innovations: (1) shadow pairs, video pairs that replay the same dynamics under independently resampled appearance, constructed at scale by our Shadow Library, so that a dynamics family becomes controllable exactly when such pairs can be constructed for it; and (2) cross-shadow prediction, which learns actions by predicting one shadow from the other, so that whatever the pairing resamples is discarded by construction and whatever it preserves becomes the action, yielding a unified dynamics representation that drives a block-causal world model. Any demonstrated clip thus becomes a reusable action asset, replayed in new environments without action labels, motion estimators, or fine-tuning. Experiments demonstrate improved action transfer and long action rollout over strong latent-action and interactive world model baselines across diverse dynamics families, with an average blinded win rate of 86% in rollout comparisons. We show video results at https://ShadowDancer-1.github.io

cs.CV↗

IndustryBench-MIPU: Benchmarking Multi-Image Attribute Value Extraction for Industrial Products

Industrial products such as valves and circuit breakers are defined by dense technical specifications that govern procurement, compatibility, and safety across supply chains. These specifications are scattered across multiple heterogeneous product images, including specification tables, nameplates, and technical drawings, yet whether Multimodal Large Language Models (MLLMs) can reliably recover them remains underexplored. To fill this gap, we introduce IndustryBench-MIPU, the first large-scale benchmark for multi-image industrial product understanding, built around structured attribute extraction -- recovering property-value pairs from product images. This task jointly probes text recognition on specification tables and nameplates, visual reasoning over technical drawings, domain knowledge to decode industrial terminology, and cross-image evidence integration to assemble scattered specifications. Concretely, the benchmark comprises 4,559 products across 27,652 images with 103,703 annotations spanning 18 industrial categories, constructed through multi-model consensus and three-tier quality assurance. Evaluating nine MLLMs under both single-image and product-level multi-image settings reveals a stark completeness gap: models achieve high precision (86--94%) but the best recovers only 49.9% of product-level attributes; moving from single-image to multi-image extraction costs 15--34 percentage points of recall. Multi-image completeness, not single-image accuracy, is the core bottleneck. Dataset and code are publicly available.

cs.CV↗

Surface Originated Cross-Field Anomalous Transport in Magnetoelectric Multilayers

In material systems with slab geometry, the surface contribution to physical responses is commonly expected to diminish rapidly with increasing thickness, giving way to the bulk response. Here, we show that this conventional wisdom is violated in a class of gate-induced responses, including gate-induced orbital and spin magnetization as well as cross-field anomalous thermoelectric transport. We develop a general framework for these effects, which naturally decomposes the total response into surface- and bulk-contributions treated on equal footing. Remarkably, the volume-averaged surface contribution remains finite in the thick-slab limit and exhibits the same thickness scaling as the bulk term. Furthermore, the surface response originates from band geometric quantities distinct from those in the bulk, being constrained solely by surface symmetries. As a result, it can dominate the overall response when the bulk contribution is symmetry-forbidden. Taking MnBi$_2$Te$_4$ multilayers as an example, we predict a strong surface-dominated cross-field anomalous Nernst effect arising from surface Berry curvature, which is readily accessible to experimental detection. These findings reveal a previously overlooked significance of surface response and open a new direction in the study of surface quantum geometry.

cond-mat.mes-hall↗

Nonperturbative Magnetic Orbital Hall Effect in Altermagnets

Recent studies on altermagnets have focused considerable attention on nonrelativistic effects that persist in the absence of spin-orbit coupling (SOC). As a result, the relative importance of various phenomena in altermagnets has commonly been judged by their dependence on SOC. Here, we challenge this common wisdom by uncovering the magnetic orbital Hall effect, which is nonperturbative in SOC strength. We establish the symmetry properties of this effect, demonstrating that it is strictly forbidden in conventional collinear antiferromagnets yet universally allowed in all ten spin-Laue classes of collinear altermagnets. Counterintuitively, although SOC-induced, it reaches giant magnitudes in altermagnets-comparable to or even exceeding the nonrelativistic spin Hall effect. Moreover, altermagnetic symmetry enables unconventional collinear-polarized orbital currents, allowing field-free manipulation of perpendicular magnetization. Our first-principles calculations predict strong room-temperature responses in the experimentally established altermagnets CrSb and FeSb2. These findings reveal the previously overlooked potential of altermagnetic orbitronics and broaden the horizons for altermagnets in high-performance magnetic memory applications.

cond-mat.mtrl-sci↗

Hasse-Witt invariants of Calabi-Yau varieties

We define the Hasse-Witt invariant of Calabi-Yau varieties in two different ways. The first method is through Cartier operator and the second method is through the theory of Calabi-Yau modular forms developed by the third author. We conjecture that these two definitions are equivalent and provide many examples of Calabi-Yau varieties in support of this conjecture.

math.AG↗

Nonlinear Magnetic Orbital Hall Effect Induced by Spin-Orbit Coupling

Electrical readout of 180$^\circ$ switching in strictly compensated collinear antiferromagnets remains a major challenge in antiferromagnetic spintronics. Electrical writing of perpendicularly magnetized ferromagnets by out-of-plane orbital torque remains an important challenge in orbitronics. In this work, we propose a second-order nonlinear magnetic orbital Hall effect in the source antiferromagnet as a simultaneous recipe for both difficulties. This orbitronics effect is induced by spin-orbit coupling and is odd in the Néel vector, thus is a unique effect that integrates both functionalities via electric control of the Néel vector in the source antiferromagnet. Our first-principles calculations in CuMnAs predict significant non-perturbative orbital effects from spin-orbit coupling, with a orbital Berry-curvature dipole mechanism. These findings unveil new possibilities opened by topological antiferromagnetic orbitronics.

cond-mat.mtrl-sci↗

Eccentricity valley Hall effect

Valleytronics harnesses the valley degree of freedom -- energy-degenerate extrema in the electronic band structure -- for information storage and processing. Valley Hall effect (VHE) is a cornerstone of valleytronics, enabling electric generation of pure valley currents. While extensively studied in systems with valleys located at time-reversal-breaking points, here, we shift the paradigm to valleytronic platforms with time-reversal-invariant valleys (TRIVs), revealing a novel phenomenon: eccentricity VHE. Unlike conventional VHE, the valley Hall angle for eccentricity VHE is an intrinsic geometric property, governed solely by the eccentricity of the valley Fermi surface, rendering it highly robust against variations in temperature or carrier density. Eccentricity VHE emerges universally across all 25 layer groups supporting TRIVs. We demonstrate these distinctive features in monolayer GeS$_{2}$ via first-principles calculations, predicting a significant valley Hall angle of 0.74. This effect can be detected through nonlocal transport measurements exhibiting characteristic scaling behavior, or, in certain cases, through valley-layer coupling. Our findings reveal a critical overlooked facet of valley Hall physics, transcend the established VHE paradigm, and significantly broadens the scope of valleytronics.

cond-mat.mes-hall↗

Wearable-informed generative digital avatars predict task-conditioned post-stroke locomotion

Dynamic prediction of locomotor capacity after stroke could enable more individualized rehabilitation, yet current assessments largely provide static impairment scores and do not indicate whether patients can perform specific tasks such as slope walking or stair climbing. Here, we present a wearable-informed data-physics hybrid generative framework that reconstructs a stroke survivor's locomotor control from wearable inertial sensing and predicts task-conditioned post-stroke locomotion in new environments. From a single 20 m level-ground walking trial recorded by five IMUs, the framework personalizes a physics-based digital avatar using a healthy-motion prior and hybrid imitation learning, generating dynamically feasible, patient-specific movements for inclined walking and stair negotiation. Across 11 stroke inpatients, predicted postures reached 82.2% similarity for slopes and 69.9% for stairs, substantially exceeding a physics-only baseline. In a multicentre pilot randomized study (n = 21; 28 days), access to scenario-specific locomotion predictions to support task selection and difficulty titration was associated with larger gains in Fugl-Meyer lower-extremity scores than standard care (mean change 6.0 vs 3.7 points; $p < 0.05$). These results suggest that wearable-informed generative digital avatars may augment individualized gait rehabilitation planning and provide a pathway toward dynamically personalized post-stroke motor recovery strategies.

cs.CE↗

Frobenius induced morphisms on moduli of sheaves on curves

We show the Frobenius pullback of a general semi-stable vector bundle in the moduli space of vector bundles with fixed rank and degree is still semi-stable by deformation trick. We then present several applications of the main theorem.

math.AG↗

WonderZoom: Multi-Scale 3D World Generation

We present WonderZoom, a novel approach to generating 3D scenes with contents across multiple spatial scales from a single image. Existing 3D world generation models remain limited to single-scale synthesis and cannot produce coherent scene contents at varying granularities. The fundamental challenge is the lack of a scale-aware 3D representation capable of generating and rendering content with largely different spatial sizes. WonderZoom addresses this through two key innovations: (1) scale-adaptive Gaussian surfels for generating and real-time rendering of multi-scale 3D scenes, and (2) a progressive detail synthesizer that iteratively generates finer-scale 3D contents. Our approach enables users to "zoom into" a 3D region and auto-regressively synthesize previously non-existent fine details from landscapes to microscopic features. Experiments demonstrate that WonderZoom significantly outperforms state-of-the-art video and 3D models in both quality and alignment, enabling multi-scale 3D world creation from a single image. We show video results and an interactive viewer of generated multi-scale 3D worlds in https://wonderzoom.github.io/

cs.CV↗