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arXiv:2602.19326v3 Announce Type: replace-cross Abstract: Urban renewal requires incremental modifications to existing geospatial plans, yet manually updating complex layouts under spatial constraints

agentsarxiv-cs-ai

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CMNIE: An Information Extraction Benchmark for Chinese Military News

DGX agent

arXiv:2609.10722v1 Announce Type: new Abstract: Structured extraction from Chinese military news supports intelligence analysis, decision-making, and knowledge base construction. However, existing res

model-releasesarxiv-cs-cl

11 Sept 2026

CMoE: Contrastive Mixture of Experts for Motion Control and Terrain Adaptation of Humanoid Robots

arXiv:2603.03067v2 Announce Type: replace Abstract: For effective deployment in real-world environments, humanoid robots must autonomously navigate a diverse range of complex terrains with abrupt tran

applicationsarxiv-cs-ro

Agents

Cognitive Digital Twins: Ethical Risks and Governance for AI Systems That Model the Mind

arXiv:2606.23094v2 Announce Type: replace-cross Abstract: As AI systems become increasingly persistent and personalized, they make possible a class of technologies that we call cognitive digital twins

agentsarxiv-cs-cl

Coherent Floquet quantum reservoirs for molecular property prediction

arXiv:2609.11071v1 Announce Type: cross Abstract: Quantum reservoir computing (QRC) uses quantum dynamics to represent input histories for prediction through a trained classical readout. Discrete time

Combining Synthetic and Real Data for Low-Resource Historical OCR: A Manchu Case Study

arXiv:2609.11495v1 Announce Type: new Abstract: Manchu, now critically endangered, was one of the principal languages of the Qing empire (1636-1912), and its extensive archival record is increasingly

applicationsarxiv-cs-lg

Complex-Text Robustness Evaluation and Failure Diagnosis for Low-Resource Multilingual Text-to-Speech

arXiv:2609.11545v1 Announce Type: new Abstract: Low-resource multilingual text-to-speech (TTS) systems have expanded language coverage, but their robustness under complex text inputs remains insuffici

Component-Aware Differential Privacy for Federated Multilingual Speech-LLMs

model-releasesarxiv-cs-cl

arXiv:2609.11762v1 Announce Type: new Abstract: Per-layer differential privacy (DP) clipping improves gradient fidelity in federated learning by allocating per-matrix clipping budgets proportional to

Hardware

Composable CXL Memory as a Kubernetes-Native Shared Memory for LLM Serving

arXiv:2609.10790v1 Announce Type: cross Abstract: We present a Kubernetes Dynamic Resource Allocation (DRA) driver that makes composable CXL memory a schedulable cluster resource, and evaluate the res

hardwarearxiv-cs-lg

Compute-Bounded Security Assurance - Coverage, Verification, and Response under Resource Constraints

model-releasesarxiv-cs-ai

arXiv:2609.09229v1 Announce Type: cross Abstract: Additional inference compute can increase the number of correctly resolved security-assurance tasks, but repeated success, unique coverage, accepted e

Configuration-Dependent Lower Bounds for Approximation by Shallow ReLU^k Networks on the Sphere

arXiv:2510.04060v3 Announce Type: replace-cross Abstract: We establish two related but logically distinct results for shallow ReLU^k neural networks on the unit sphere SS^d. First, for an arbitrary se

Conformal Calibration Transfer

arXiv:2609.10737v1 Announce Type: new Abstract: Conformal prediction converts point predictions into set-valued predictions with coverage guarantees under exchangeability between calibration and deplo

Contact-Aware Incremental Model Predictive Control for an Underactuated Aerial Manipulator

arXiv:2609.11661v1 Announce Type: new Abstract: We present a robust contact-aware control framework for aerial writing on an underactuated platform. The framework combines nonlinear model predictive c

applicationsarxiv-cs-ro

Context operations to architecture modelling output from large language models and evaluation criteria for their use in systems engineering design

arXiv:2609.10132v1 Announce Type: cross Abstract: The development of generative artificial intelligence resources enables opportunities of speeding up systems and engineering design work. This contrib

safetyarxiv-cs-ai

Local Ai

ContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance

arXiv:2609.09458v1 Announce Type: new Abstract: As LLM agents move from answering questions to carrying out procedures, failures can be unwarranted rather than visibly wrong: the final response looks

local-aiarxiv-cs-ai

Convex Optimization with Nested Evolving Feasible Sets (CONES) under Time-Varying Loss Functions

arXiv:2609.11207v1 Announce Type: new Abstract: Convex Optimization with Nested Evolving Feasible Sets (CONES)} was introduced in ite{CONESVaze} where the objective function (f) remains fixed but the

CoRA-NAS: Coarse Ranking and Anchor-Residual Refinement for Neural Architecture Search

arXiv:2609.11884v1 Announce Type: cross Abstract: Zero-cost proxies rank architectures cheaply, but their reliability varies across search spaces. We introduce CoRA-NAS (COarse Ranking + Anchor-residu

Counterfactual Marginalisation: Framework for Evaluating Robustness to Nuisance Variables

arXiv:2609.10778v1 Announce Type: new Abstract: Machine learning models can achieve strong test performance while relying on demographic or acquisition-related shortcuts. We propose counterfactual (CF

Local Ai

Cross-Lingual Clinical Annotation Projection as Constrained Text Generation: A Six-Language Study

arXiv:2609.11450v1 Announce Type: new Abstract: Background: To determine whether cross-lingual clinical annotation projection can be formulated as a text-preserving, document-level generative task tha

local-aiarxiv-cs-cl

CryptoL: Towards Scale Dominance and Physics Constraints Mitigation in Financial Multivariate Time Series Forecasting

arXiv:2609.11206v1 Announce Type: cross Abstract: Cryptocurrency forecasting presents a distinctive combination of extreme cross-asset scale heterogeneity, non-stationary dynamics, and structural depe

CS-Guard: Benchmarking LLM Guardrails for Code Generation Security

model-releasesarxiv-cs-ai

arXiv:2609.09798v1 Announce Type: cross Abstract: Large language models (LLMs) have been ex- ploited to generate malware, but the effective- ness of guardrails for code generation secu- rity remains u

Agents

Data-Efficient Language Modeling: From Frontier Advancement to Principle-Guided Model Improvement

arXiv:2609.10702v1 Announce Type: new Abstract: Learning from limited text requires models to use context, generalize to new inputs, and retain useful capabilities. Qiushi Engine conducted a long-hori

agentsarxiv-cs-cl

Data Scarcity and Model Sparsity: Mixtures-of-Experts Overfit More to Repeated Data

arXiv:2609.11917v1 Announce Type: cross Abstract: As the supply of human-written text is exhausted, it has become standard practice to repeat language model training data. Prior work has studied data

Decision Shifts, Lost Label Functionality, and an Inconclusive Grounding Audit in Correctness-Gated Multi-Teacher Distillation

model-releasesarxiv-cs-ai

arXiv:2609.09702v1 Announce Type: new Abstract: Candidate decision correctness and rationale grounding are different objectives. We examine correctness-gated multi-teacher distillation in a fixed expe

Deep operator learning for efficient sampling from invariant measures of stochastic differential equations

arXiv:2609.11376v1 Announce Type: cross Abstract: We introduce an amortized neural sampler that combines operator learning with flow methods for sampling. It maps SDE coefficient functions to pushforw

DeepResearch Bench II: Diagnosing Deep Research Agents via Rubrics from Expert Reports

model-releasesarxiv-cs-cl

arXiv:2601.08536v3 Announce Type: replace Abstract: Deep Research Agents (DRA) aim to help users search the web, synthesize information, and deliver comprehensive investigative reports. Prior benchmar

DeFiFlowBench: Benchmarking and Improving Safe Executability in Natural-Language DeFi Workflow Synthesis

arXiv:2609.11504v1 Announce Type: new Abstract: A structurally valid DeFi workflow can still authorize a costly trade. We introduce DeFiFlowBench, a benchmark of 207 team-authored prompts for natural-

DefVINS: Visual-Inertial Odometry for Deformable Scenes

arXiv:2601.00702v3 Announce Type: replace-cross Abstract: Deformable scenes violate the rigidity assumptions underpinning classical visual--inertial odometry (VIO), often leading to over-fitting to lo

Detectable Only Where It Is Confounded: What Verified Duplication Counts Say About Membership Evidence in Language Models

arXiv:2609.10830v1 Announce Type: new Abstract: When a language model finds a sentence unusually cheap to predict, it is tempting to conclude that the sentence was in its training data. Almost every p

Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

arXiv:2609.11777v1 Announce Type: cross Abstract: Clinical electroencephalography (EEG) data are valuable for healthcare research and for developing artificial intelligence (AI)-based clinical decisio

applicationsarxiv-cs-lg

Local Ai

DINO-Med: A Unified Patch-Based Adaptation Framework for Multi-Modal Medical Image Analysis Applied to Liver Fibrosis Staging

arXiv:2609.11380v1 Announce Type: new Abstract: Adapting natural-image foundation models like DINOv3 to multi-modal medical imaging is challenging due to the significant domain gap between natural col

local-aiarxiv-cs-cv

DirectSwap: Paired, Mask-Free Video Head Swapping with Full-Reference Evaluation

arXiv:2512.09417v2 Announce Type: replace Abstract: Head swapping replaces an entire head while preserving pose, expression, body motion, and scene. Progress is limited by the lack of cross-identity p

Distance generalization in transformers: why bother with positional encoding?

arXiv:2609.11913v1 Announce Type: new Abstract: Out-of-distribution length generalization, namely to extrapolate a task from short to longer context, has been studied intensively for transformers. Her

Distributed Optimization of Modular Production Systems using Model-based Reinforcement Learning with Inverse Models

arXiv:2609.11615v1 Announce Type: cross Abstract: This paper presents a novel approach for data-driven self-learning control of highly flexible, modular manufacturing systems. Specifically, we employ

safetyarxiv-cs-lg

Distributed Physical Layer Authentication and Collaborative RSMA in Non-Terrestrial Networks via Graph Reinforcement Learning

arXiv:2609.09475v1 Announce Type: cross Abstract: Existing physical-layer authentication (PLA) schemes for non-terrestrial networks (NTNs) often rely on single-anchor verification, lack joint authenti

researcharxiv-cs-ai

Distribution-aware Language Neuron Identification in Multilingual Large Language Models

arXiv:2609.10993v1 Announce Type: new Abstract: Multilingual large language models (mLLMs) contain a small fraction of feed-forward neurons that are sensitive to particular languages, commonly termed

Divergence-Based Similarity Function for Multi-View Contrastive Learning

arXiv:2507.06560v5 Announce Type: replace Abstract: Recent success in contrastive learning has sparked growing interest in more effectively leveraging multiple augmented views of data. While prior met

researcharxiv-cs-cv

Diversity of EML-type operators

arXiv:2609.11210v1 Announce Type: cross Abstract: The discovery of the EML operator, sufficient to evaluate the standard explicit purely transcendental elementary functions, has led to considerable in

DNA: Differentially private Neural Augmentation for contact tracing

arXiv:2404.13381v2 Announce Type: replace Abstract: The COVID19 pandemic had enormous economic and societal consequences. Contact tracing is an effective way to reduce infection rates by detecting pot

Do Agents Know When They Succeed? Calibrating Agent Confidence from Internal Representations

arXiv:2609.09448v1 Announce Type: new Abstract: As agentic systems getting adopted rapidly in safety critical applications, it is vital to measure the confidence associated with the agentic actions. I

safetyarxiv-cs-ai

Do Vision-Language Models Understand Visual Persuasiveness? A Diagnosis via Visual Persuasive Factors

arXiv:2511.17036v2 Announce Type: replace Abstract: Visual persuasion uses images to shape cognition, emotion, and behavior, with its effects depending on both visual attributes and semantic context.

safetyarxiv-cs-cl

Does Linguistic Structure Enrichment Enhance Coherence Assessment? Not With Current Architectures

arXiv:2609.10893v1 Announce Type: new Abstract: Recent advances in large language models have transformed human-computer interaction. Despite their fluency, these models often produce texts that are g

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture

arXiv:2607.09835v2 Announce Type: replace Abstract: The recently introduced YOLO26 architecture incorporates NMS-free end-to-end inference and is optimized for deployment on resource-constrained CPU-b

Domain Elastic Transform: Bayesian Function Registration for High-Dimensional Scientific Data

arXiv:2603.21235v2 Announce Type: replace-cross Abstract: Nonrigid registration is conventionally divided into point set registration, which aligns sparse geometries, and image registration, which ali

Domain-Specific Hallucination Detection in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.11878v1 Announce Type: new Abstract: Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detectio

DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

arXiv:2609.10796v1 Announce Type: new Abstract: Pretrained diabetic retinopathy (DR) prediction models differ in their input fields, serialization formats, preprocessing requirements, and output seman

Dream4D: Lifting Camera-Controlled I2V towards Spatiotemporally Consistent 4D Generation

arXiv:2508.07769v3 Announce Type: replace Abstract: The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fi

researcharxiv-cs-cv

DriftNet: A Dual-Head Trajectory Transformer for Detecting and Localizing Prompt Injection in LLM Agents

arXiv:2609.10892v1 Announce Type: cross Abstract: When an indirect prompt injection succeeds against an LLM agent, the compromise is visible in the agent's own behavior: a benign prefix of tool calls,