Search: “models”

SOAR: Real-Time Joint Optimization of Order Allocation and Robot Scheduling in Robotic Mobile Fulfillment Systems

arXiv:2605.03842v1 Announce Type: cross Abstract: Robotic Mobile Fulfillment Systems (RMFS) rely on mobile robots for automated inventory transportation, coordinating order allocation and robot schedu

agentsarxiv-cs-ro

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Local Ai

Stochastic Attention: Connectome-Inspired Randomized Routing for Expressive Linear-Time Attention

DGX agent

arXiv:2604.00754v2 Announce Type: replace Abstract: The whole-brain connectome of a fruit fly comprises over 130K neurons connected with a probability of merely 0.02%, yet achieves an average shortest

local-aiarxiv-cs-cl

6 May 2026

TabSurv: Adapting Modern Tabular Neural Networks to Survival Analysis

arXiv:2605.03944v1 Announce Type: new Abstract: Survival analysis on tabular data is a well-studied problem. However, existing deep learning methods are often highly task-specific, which can limit the

applicationsarxiv-cs-lg

The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence

arXiv:2408.12622v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is reshaping society, from video generation to medical diagnosis, coding agents to autonomous vehicles. Yet resea

safetyarxiv-cs-lg

Hardware

The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm

arXiv:2505.16932v5 Announce Type: replace-cross Abstract: Computing the polar decomposition and the related matrix sign function has been a well-studied problem in numerical analysis for decades. Rece

hardwarearxiv-cs-cl

Toggling stiffness via multistability

arXiv:2510.09511v2 Announce Type: replace-cross Abstract: Variable stiffness is a key capability in biological and robotic systems, enabling adaptive interaction across tasks and environments. Mechani

researcharxiv-cs-ro

Tracing Like a Clinician: Anatomy-Guided Spatial Priors for Cephalometric Landmark Detection

arXiv:2605.03358v1 Announce Type: new Abstract: When orthodontists trace cephalometric radiographs, they follow a structured workflow: identify the soft tissue profile, partition the skull into anatom

safetyarxiv-cs-cv

Transformers with Selective Access to Early Representations

arXiv:2605.03953v1 Announce Type: cross Abstract: Several recent Transformer architectures expose later layers to representations computed in the earliest layers, motivated by the observation that low

Truth or Tribe: How In-group Favoritism Prioritize Facts in Persona Agents

arXiv:2605.01329v1 Announce Type: new Abstract: In-group favoritism refers to the phenomena of favoring members of one's in-group over out-group members and is widely observed in numerous social coope

agentsarxiv-cs-ai

Two Calls, Two Moments, and the Vote-Accuracy Curve of Repeated LLM Inference

arXiv:2605.03379v1 Announce Type: cross Abstract: Repeated sampling is a standard way to spend test-time compute, but its benefit is controlled by the latent distribution of correctness across example

Uncertainty-Aware Trip Purpose Inference from GPS Trajectories via POI Semantic Zones and Pareto Calibration

arXiv:2605.01257v1 Announce Type: new Abstract: Large-scale GPS trajectory data offer rich observations of human mobility, yet assigning trip purposes to detected stops remains challenging due to the

safetyarxiv-cs-ai

Uncovering and Understanding FPR Manipulation Attack in Industrial IoT Networks

arXiv:2601.14505v2 Announce Type: replace-cross Abstract: In the network security domain, due to practical issues -- including imbalanced data and heterogeneous legitimate network traffic -- adversari

Local Ai

Unsupervised Monocular Road Segmentation for Autonomous Driving via Scene Geometry

arXiv:2510.16790v2 Announce Type: replace Abstract: This paper presents a fully unsupervised approach for binary road segmentation (road vs. non-road), eliminating the reliance on costly manually labe

local-aiarxiv-cs-cv

ValueBlindBench: Agreement-Gated Stress Testing of LLM-Judged Investment Rationales Before Returns Are Observable

arXiv:2604.25224v2 Announce Type: replace Abstract: LLM-based financial agents increasingly produce investment rationales before the outcomes needed to evaluate them are observable. This creates a del

tutorialsarxiv-cs-ai

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach

arXiv:2510.08952v4 Announce Type: replace Abstract: Text-attributed graphs (TAGs) have become a key form of graph-structured data in modern data management and analytics, combining structural relation

agentsarxiv-cs-lg

Will the Carbon Border Adjustment Mechanism Impact European Electricity Prices? A GNN-Based Network Analysis

arXiv:2605.03304v1 Announce Type: new Abstract: The European Union's Carbon Border Adjustment Mechanism (CBAM) creates a complex challenge for the interconnected European electricity market. Tradition

safetyarxiv-cs-lg

2026 Roadmap on Artificial Intelligence and Machine Learning for Smart Manufacturing

arXiv:2605.00839v1 Announce Type: cross Abstract: The evolution of artificial intelligence (AI) and machine learning (ML) is reshaping smart manufacturing by providing new capabilities for efficiency,

agentsarxiv-cs-lg

2D-ThermAl: Physics-Informed Framework for Thermal Analysis of Circuits using Generative AI

arXiv:2512.01163v2 Announce Type: replace Abstract: Thermal analysis is increasingly critical in modern integrated circuits, where non-uniform power dissipation and high transistor densities can cause

3D Gaussian Splatting against Moving Objects for High-Fidelity Street Scene Reconstruction

arXiv:2503.12001v4 Announce Type: replace Abstract: The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Tra

agentsarxiv-cs-cv

A Comprehensive Review of Fish Feeding Behavior Analysis in Aquaculture: Tasks, Techniques, and Applications

arXiv:2502.15311v3 Announce Type: replace Abstract: Fish feeding behavior analysis is a key foundation for intelligent feeding and precision aquaculture management, and plays an important role in impr

applicationsarxiv-cs-cv

A dimensional R2 regression metric

arXiv:2605.01066v1 Announce Type: new Abstract: R2 score is the standard metric for evaluating regression tasks, offering a normalized magnitude-agnostic measure of accuracy that captures variance. Ho

A Principled Approach for Creating High-fidelity Synthetic Demonstrations for Imitation Learning

arXiv:2605.01232v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled visually realistic demonstration generation from a single expert trajectory and a short mul

safetyarxiv-cs-ro

A Proof-of-Concept Study of Multitask Learning for Cranial Synthetic CT Generation Across Heterogeneous MRI Field Strengths

arXiv:2605.00923v1 Announce Type: cross Abstract: Accurate synthesis of computed tomography (CT) images from magnetic resonance imaging (MRI) is clinically valuable for cranial applications such as at

A skin-like conformal sensor for real-time shape mapping

arXiv:2605.01170v1 Announce Type: cross Abstract: Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based appr

researcharxiv-cs-ro

A Survey of Reasoning-Intensive Retrieval: Progress and Challenges

arXiv:2605.00063v1 Announce Type: cross Abstract: Reasoning-Intensive Retrieval (RIR) targets retrieval settings where relevance is mediated by latent inferential links between a query and supporting

tutorialsarxiv-cs-ai

Adaptive Alarm Threshold Prediction in 4G Mobile Networks: A Percentile-Guided Deep Learning Framework with Interpretable Outputs

arXiv:2605.00838v1 Announce Type: cross Abstract: In mobile telecommunications, alarms act as early warning signals. They are triggered when a cell, the basic unit of radio coverage, shuts down or beh

safetyarxiv-cs-lg

Hardware

aerial-autonomy-stack -- a Faster-than-real-time, Autopilot-agnostic, ROS2 Framework to Simulate and Deploy Perception-based Drones

arXiv:2602.07264v2 Announce Type: replace Abstract: Unmanned aerial vehicles are rapidly transforming multiple applications, from agricultural and infrastructure monitoring to logistics and defense. I

hardwarearxiv-cs-ro

AgentReputation: A Decentralized Agentic AI Reputation Framework

arXiv:2605.00073v1 Announce Type: new Abstract: Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security audi

safetyarxiv-cs-ai

AI Adoption Among Teachers: Insights on Concerns, Support, Confidence, and Attitudes

arXiv:2605.00343v1 Announce Type: cross Abstract: The study examines the adoption of artificial intelligence (AI) tools in education by analyzing the roles of institutional support, teacher confidence

applicationsarxiv-cs-ai

Are Tools All We Need? Unveiling the Tool-Use Tax in LLM Agents

arXiv:2605.00136v1 Announce Type: new Abstract: Tool-augmented reasoning has become a popular direction for LLM-based agents, and it is widely assumed to improve reasoning and reliability. However, we

agentsarxiv-cs-ai

Asymmetric Invertible Threat: Learning Reversible Privacy Defense for Face Recognition

arXiv:2605.01217v1 Announce Type: new Abstract: Face Recognition systems are widely deployed in real-world applications, but they also raise privacy concerns due to unauthorized collection and misuse

tutorialsarxiv-cs-cv

Autonomous QA Agent: A Retrieval-Augmented Framework for Reliable Selenium Script Generation

arXiv:2601.06034v1 Announce Type: cross Abstract: Software testing is critical in the software development lifecycle, yet translating requirements into executable test scripts remains manual and error

agentsarxiv-cs-lg

BaldWhisper: Faster Whisper with Head Shearing and Layer Merging

arXiv:2510.08599v2 Announce Type: replace-cross Abstract: Pruning large pre-trained transformers in a data-scarce scenario is challenging, as it often requires massive retraining data to recover perfo

Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation

arXiv:2605.01302v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) systems predominantly rely on semantic relevance as a proxy for utility. However, this assumption collapse

safetyarxiv-cs-cl

Beyond Sentiment: A Multi-Agent Pipeline for Actionable Business Advice from Reviews

arXiv:2601.12024v2 Announce Type: replace-cross Abstract: Customer reviews contain valuable signals about service quality, but converting large-scale review corpora into actionable business recommenda

agentsarxiv-cs-cl

Beyond Structure: Revolutionising Materials Discovery via AI-Driven Synthesis Protocol-Property Relationships

arXiv:2605.00313v1 Announce Type: cross Abstract: The current structure-centric paradigm in artificial intelligence (AI)-driven materials discovery, despite delivering thousands of candidate structure

researcharxiv-cs-ai

Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials

arXiv:2605.00639v1 Announce Type: cross Abstract: Autonomous science is transforming how we discover materials and chemical systems for advanced energy technologies. However, many initially promising

agentsarxiv-cs-ai

CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization

arXiv:2605.01171v1 Announce Type: new Abstract: Despite recent progress, recovering parametric CAD construction sequences from geometric input, such as meshes or point clouds, is a key challenge for d

applicationsarxiv-cs-cv

Causal Representation Learning with Optimal Compression under Complex Treatments

arXiv:2603.11907v2 Announce Type: replace Abstract: Estimating Individual Treatment Effects (ITE) in multi-treatment scenarios faces two critical challenges: the Hyperparameter Selection Dilemma for b

CCNETS: A Modular Causal Learning Framework for Pattern Recognition in Imbalanced Datasets

arXiv:2401.04139v4 Announce Type: replace Abstract: Handling class imbalance remains a central challenge in machine learning, particularly in pattern recognition tasks where identifying rare but criti

tutorialsarxiv-cs-lg

Certified vs. Empirical Adversarial Robust-ness via Hybrid Convolutions with Attention Stochasticity

arXiv:2605.01519v1 Announce Type: new Abstract: We introduce Hybrid Convolutions with Attention Stochasticity (HyCAS), an adversarial defense that narrows the long-standing gap between provable robust

Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation

arXiv:2605.01284v1 Announce Type: cross Abstract: Iterative Retrieval-Augmented Generation (iRAG) has emerged as a powerful paradigm for answering complex multi-hop questions by progressively retrievi

Colinearity Decay: Training Quantization-Friendly ViTs with Outlier Decay

arXiv:2605.01330v1 Announce Type: new Abstract: Low-bit quantization is a practical route for efficiently deploying vision Transformers, yet activation outliers complicate fully quantized deployment.

safetyarxiv-cs-cv

Correlates of Image Memorability in Vision Encoders: Activations, Attention Entropy, Patch Uniformity and Autoencoder Losses

arXiv:2509.01453v2 Announce Type: replace Abstract: Images vary in how memorable they are to humans. Inspired by findings from cognitive science and computer vision, we explore correlates of image mem

Cross-Domain Adversarial Augmentation: Stabilizing GANs for Medical and Handwriting Data Scarcity

arXiv:2605.01815v1 Announce Type: new Abstract: Generative Adversarial Networks (GANs) offer a pragmatic route to mitigate data scarcity in vision tasks. We study generative augmentation across two lo

Cross-Polarization Fusion of VV AND VH SAR Observations for Improved Flood Mapping

arXiv:2605.02153v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mappi

Cross-Scale Pretraining: Enhancing Self-Supervised Learning for Low-Resolution Satellite Imagery for Semantic Segmentation

arXiv:2601.12964v2 Announce Type: replace Abstract: Self-supervised pretraining in remote sensing is mostly done using mid-spatial resolution (MR) image datasets due to their high availability. Given

tutorialsarxiv-cs-cv

CUE: Concept-Aware Multi-Label Expansion to Mitigate Concept Confusion in Long-Tailed Learning

arXiv:2605.01309v1 Announce Type: new Abstract: Long-tailed distributions are common in real-world recognition tasks, where a few head classes have many samples while most tail classes have very few.

safetyarxiv-cs-cv