Search: “papers”

Koopman Representation of Nonlinear Virtual Environments in Kinesthetic Haptic Systems

arXiv:2608.11461v1 Announce Type: new Abstract: Rendering haptic feedback with nonlinear virtual environments (VEs) is important in many applications that require highly accurate force feedback. This

researcharxiv-cs-ro

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Latent variable models for simultaneous EOV identification and removal in population-based SHM

DGX agent

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

model-releasesarxiv-cs-lg

13 Aug 2026

Locomotion Variability and User Experience in Smart Wheelchair Human-Robot Interaction

arXiv:2608.11417v1 Announce Type: new Abstract: Human movement is inherently variable, with variability structured according to task relevance: movements are typically more consistent at task-critical

researcharxiv-cs-ro

Tutorials

Low-Interaction-Rank Learning: Unifying Multiplicative Dual-Encoder Heads

arXiv:2608.11661v1 Announce Type: cross Abstract: A multiplicative dual-encoder network computes a real-valued output for a pair of inputs as the inner product of their separate encodings. This archit

tutorialsarxiv-cs-ai

Machine Learning-Based Cyber Defense for Cloud Infrastructure: An Adaptive Deep Q-Network Architecture for Intelligent Intrusion Detection and Automated Threat Mitigation

arXiv:2608.12190v1 Announce Type: cross Abstract: With the increasing complexity of cyber assaults in cloud environments, adaptable security solutions are needed that can support real-time detection a

safetyarxiv-cs-ai

Market-Information-Aware Gated-LoRA of Foundation Models for Transferable Day-Ahead Electricity Price Forecasting

arXiv:2608.11359v1 Announce Type: new Abstract: Electricity price forecasting is crucial for market participants but remains difficult because prices are volatile, market-specific, and closely tied to

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning

model-releasesarxiv-cs-ai

arXiv:2608.11749v1 Announce Type: cross Abstract: Multi-objective optimization (MOO) has demonstrated significant success in multi-task learning by mitigating task conflicts through gradient manipulat

OEIS Open: How many conjectures can language models turn into theorems?

model-releasesarxiv-cs-ai

arXiv:2608.11941v1 Announce Type: new Abstract: We construct OEIS Open, a benchmark based on 492 open mathematical conjectures from the OEIS, formalized in Lean by Tsoukalas et al. Whereas these conje

Local Ai

OrderMoE: An expert similarity driven distributed edge MoE inference

arXiv:2607.17154v2 Announce Type: replace-cross Abstract: Although mixture-of-experts, MoE, models have been increasingly adopted to scale large language models with moderate computation cost, it rema

local-aiarxiv-cs-lg

Proportional Analogies on Probability Distributions via Bayesian Updating

arXiv:2608.11724v1 Announce Type: new Abstract: Analogies are quaternary relations of the form 'A is to B as C is to D'. Among the various formalizations of analogical reasoning, proportional analogie

ProtoHGF-Net: Prototype HyperGraph Fusion with Intra-modal Calibration for RGBT Object Detection

arXiv:2608.11595v1 Announce Type: new Abstract: RGB-Thermal (RGBT) object detection enables robust perception in complex scenes by leveraging the complementary strengths of visible textures and therma

Quantifying the Relationship Between Clinical Safety and Environmental Impact in Therapeutic LLMs

arXiv:2608.11830v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) in mental health contexts raises questions about the relationship between clinical safety and environme

safetyarxiv-cs-cl

Reducing Symmetry Increase in Equivariant Neural Networks

arXiv:2608.12010v1 Announce Type: new Abstract: Equivariant Neural Networks (ENNs) have empowered numerous applications in scientific fields. Despite their remarkable capacity for representing geometr

applicationsarxiv-cs-lg

RevCRN: Reversible Analog Computation using Chemical Reaction Networks

arXiv:2608.11362v1 Announce Type: cross Abstract: The computability of real numbers and functions using Turing Machines has been a central area of theoretical computer science since the mid-20th centu

researcharxiv-cs-cl

Self-Harness: Harnesses That Improve Themselves

model-releasesarxiv-cs-cl

arXiv:2606.09498v2 Announce Type: replace Abstract: The performance of LLM-based agents is jointly shaped by their base models and the harnesses that mediate their interaction with the environment. Be

Soft-Attention Improves Skin Cancer Classification Performance

arXiv:2105.03358v4 Announce Type: replace-cross Abstract: In clinical applications, neural networks must focus on and highlight the most important parts of an input image. Soft-Attention mechanism ena

Sparse and robust geometric twin support vector machine via asymmetric RoBoSS loss function

arXiv:2608.11567v1 Announce Type: new Abstract: In real-world scenarios, the training data usually contains redundant features, label noise and feature noise, which provide severe challenges for the e

applicationsarxiv-cs-lg

Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages

arXiv:2608.12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced commu

applicationsarxiv-cs-ai

Structuring the Space of Perspectives

arXiv:2608.12113v1 Announce Type: new Abstract: The same event can be reported from different perspectives depending on the experiences, background, and beliefs of the writer or speaker. A variety of

researcharxiv-cs-cl

Top-down Traffic Scenario Generation via Joint Initial-Goal Diffusion and Trajectory Infilling

arXiv:2608.11407v1 Announce Type: new Abstract: Robust traffic simulators are crucial for developing and testing autonomous vehicles to reduce the costly, labor-intensive real-world data collection pr

agentsarxiv-cs-ro

Towards Model-based Run-time Cybersecurity: On Control-Flow Anomaly Detection, Attack Identification, and Hardware Monitoring

arXiv:2608.11802v1 Announce Type: cross Abstract: Methods to increase the resilience of systems to cyber-attacks become increasingly important. Control-flow monitoring provides a principled basis to e

Towards Truly Unsupervised Evaluation of Feature Selection

arXiv:2608.12057v1 Announce Type: new Abstract: Feature selection is one of the most important and fundamental tasks in data mining, tackled by a family of methods with an established set of evaluatio

TradingMoE: Routing the Right Experts in Evolving Markets

arXiv:2608.11785v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for financial analysis and trading, but direct trading remains challenging because the predicti

Local Ai

Transferable Above-Ground Biomass (AGB) Estimation Model from Multi-Sensor Data with Sparse Field Calibration

arXiv:2608.11638v1 Announce Type: cross Abstract: Spatially continuous quantification of forest above-ground biomass (AGB) is what makes carbon accounting credible and mitigation strategies actionable

local-aiarxiv-cs-cv

Uncertainty-Aware and Explainable Ensemble Deep Learning Framework for Multi-Class Skin Lesion Classification

arXiv:2608.11280v1 Announce Type: cross Abstract: Skin cancer diagnosis from dermoscopic images remains challenging due to high intra-class variability, inter-class similarity, class imbalance, and th

VLMs Win a Systematic Evaluation of Underwater Image Reconstruction

arXiv:2608.11425v1 Announce Type: new Abstract: Underwater image restoration consists of recovering an image which looks like there is no water present. To date, evaluation has not been systematic. Th

Tutorials

VQ-bench: A Composable Vector Quantization Framework

arXiv:2608.11240v1 Announce Type: new Abstract: Vector quantization is an old problem but has recently become central to AI infrastructure. It is therefore experiencing a surge of renewed engineering

tutorialsarxiv-cs-ai

Warping Earth Observations for better ice labeling in the Marginal Marginal Ice Zone

model-releasesarxiv-cs-cv

arXiv:2608.11883v1 Announce Type: new Abstract: Multimodal satellite imagery provides complementary information for Earth Observation, but accurately combining heterogeneous sensors remains challengin

Who Would You Vote For? Auditing Political Alignment in LLMs: An Italian Case-Study

arXiv:2608.11649v1 Announce Type: new Abstract: As users increasingly turn to Large Language Models (LLMs) for information and advice on political matters, particularly during election periods, the po

safetyarxiv-cs-cl

XYZFlow:Scaling Multi dimensional Shortcut Flows for Efficient Generative Modeling

arXiv:2608.12276v1 Announce Type: new Abstract: High-fidelity image generation faces a trade-off between speed and quality. Diffusion models produce strong visuals but require costly iterative samplin

3D Weighted Geometric Graph Neural Networks for Sheep Facial Pain Assessment

arXiv:2608.11050v1 Announce Type: cross Abstract: Deep learning systems perform mainly within the 2D for a single image domain and take the face as a single-dimension representation, losing sight of t

A Convolutional Layer Activation Dimensionality Reduction for Out-of-Distribution and Adversarial Attack Detection Methods

arXiv:2608.10203v1 Announce Type: new Abstract: Despite the success of convolutional neural networks in image classification tasks and their general application in multi-modal models, their susceptibi

safetyarxiv-cs-cv

A Gateway Architecture for Enterprise MCP Authentication: Unifying Heterogeneous Auth, Identity Delegation, and the User / Non-User Persona Problem

arXiv:2608.10760v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has become the de-facto interface for connecting LLM agents to enterprise tools, and adoption has been explosive: wit

agentsarxiv-cs-ai

A Neural Network Based Teleoperation for Remote Controlled Vehicles

arXiv:2608.10367v1 Announce Type: new Abstract: Direct teleoperation of vehicles faces critical technical bottlenecks: communication latency and the operator's inability to physically perceive unmodel

safetyarxiv-cs-ro

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications

arXiv:2511.00366v3 Announce Type: replace-cross Abstract: Digital twins are developed to model the behavior of a specific physical asset (or twin), and they can consist of high-fidelity physics-based

Agentic Instruction Data Selection: Let DataMaster Interpret Your Intent

arXiv:2608.10579v1 Announce Type: new Abstract: Although existing instruction data selection methods have introduced various metrics, the inherent complexity of real-world datasets makes it impractica

agentsarxiv-cs-ai

Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift

arXiv:2505.02257v2 Announce Type: replace-cross Abstract: In regions lacking medically certified causes of death, verbal autopsy (VA) is a widely used tool to ascertain the cause of death through inte

applicationsarxiv-cs-lg

Beyond Decision Boundaries: Relational Geometry Attacks on Contrastive Embedding Manifolds

arXiv:2608.10237v1 Announce Type: new Abstract: Contrastive learning and Siamese embedding models have become the foundation of modern verification systems, where decisions are governed not by discret

Bridging Severe Cross-Modal Misalignment: End-to-End Visible-Infrared Object Detection via Explicit Feature-Domain Affine Registration

model-releasesarxiv-cs-cv

arXiv:2608.10680v1 Announce Type: new Abstract: Visible-infrared object detection relies on complementary RGB and thermal cues, but its performance is often degraded by cross-modal spatial misalignmen

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

arXiv:2608.10299v1 Announce Type: new Abstract: Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, s

agentsarxiv-cs-cl

Conflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022-2025

arXiv:2608.09936v1 Announce Type: new Abstract: Do French news headlines frame left- and right-populist challengers as symmetric ``extremes,'' or as fundamentally different political adversaries? We e

researcharxiv-cs-cl

Continuous Interaction Diffusion: A Diffusion-Native Runtime for Asynchronous Tool-Augmented Reasoning

arXiv:2608.10438v1 Announce Type: new Abstract: Large language models increasingly rely on external tools to access up-to-date information, perform computation, and interact with the outside world. Fo

agentsarxiv-cs-ai

Curate Before You Connect: Identity and Ontology Tagging in a Production Knowledge Graph

model-releasesarxiv-cs-ai

arXiv:2608.10644v1 Announce Type: new Abstract: Extraction produces candidate entities and relationships; writing them into a graph is where identity is decided, and identity decisions are destructive

Dreamer-SAC: Off-Policy Learning in Latent World Models for Sample-Efficient Autonomous Driving

arXiv:2608.10386v1 Announce Type: new Abstract: Sample-efficient reinforcement learning for autonomous driving is often limited by the trade-off between data efficiency and model bias. While world mod

safetyarxiv-cs-lg

DriveVLA-M0: Failure-Aware Memory Augmentation for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2608.10413v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for end-to-end autonomous driving by enabling unified reasoning across

Dual Stress: Runtime Safety Monitoring for Safety-Constrained MPC Navigation

arXiv:2608.10791v1 Announce Type: new Abstract: Runtime hazard monitors for autonomous naviga- tion are conventionally built from geometric quantities: predicted clearance, time to collision, and requ

safetyarxiv-cs-ro

Efficient Weak-Entropy PINN for Solving Hyperbolic Conservation Laws

arXiv:2608.10389v1 Announce Type: cross Abstract: In recent years, neural networks have significantly advanced numerical solutions of partial differential equations (PDEs). However, solving PDEs with

Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608.09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis. Deep learning (DL) mod