Search: “models”

Climate-based Pre-screening of Self-sustaining Regreening Opportunities in Drylands: A Case Study for Saudi Arabia

arXiv:2605.04206v1 Announce Type: new Abstract: Large-scale restoration in drylands is widely promoted to address land degradation and biodiversity loss, yet many efforts rely on long-term irrigation,

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Agents

Collision-Aware Object-Goal Visual Navigation via Two-Stage Deep Reinforcement Learning

DGX agent

arXiv:2502.13498v2 Announce Type: replace-cross Abstract: Object-goal visual navigation aims to reach a specific target object using egocentric visual observations. Recent deep reinforcement learning

agentsarxiv-cs-cv

7 May 2026

Local Ai

Contextual Multi-Objective Optimization: Rethinking Objectives in Frontier AI Systems

arXiv:2605.03900v1 Announce Type: new Abstract: Frontier AI systems perform best in settings with clear, stable, and verifiable objectives, such as code generation, mathematical reasoning, games, and

local-aiarxiv-cs-ai

Continual Knowledge Updating in LLM Systems: Learning Through Multi-Timescale Memory Dynamics

arXiv:2605.05097v1 Announce Type: cross Abstract: LLMs are trained once, then deployed into a world that never stops changing. External memory compensates for this, but most systems manage it explicit

researcharxiv-cs-cl

Cryptographic Registry Provenance: Structural Defense Against Dependency Confusion in AI Package Ecosystems

arXiv:2605.03309v1 Announce Type: cross Abstract: Dependency confusion attacks exploit a structural gap in software distribution: once a package is installed, there is no cryptographic proof of which

applicationsarxiv-cs-ai

Hardware

CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention Kernels

arXiv:2605.05023v1 Announce Type: new Abstract: Efficient CUDA implementations of attention mechanisms are critical to modern deep learning systems, yet supporting diverse and evolving attention varia

hardwarearxiv-cs-lg

Deco: Extending Personal Physical Objects into Pervasive AI Companion through a Dual-Embodiment Framework

arXiv:2605.03882v1 Announce Type: cross Abstract: Individuals frequently form deep attachments to physical objects (e.g., plush toys) that usually cannot sense or respond to their emotions. While AI c

researcharxiv-cs-ai

Decompose to Understand, Fuse to Detect: Frequency-Decoupled Anomaly Detection for Encrypted Network Traffic

arXiv:2605.02970v1 Announce Type: cross Abstract: Network traffic anomaly detection represents a critical cybersecurity task, yet widespread encryption makes this task increasingly challenging. In res

safetyarxiv-cs-ai

Disentangled Learning Improves Implicit Neural Representations for Medical Reconstruction

arXiv:2605.04234v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a powerful paradigm for medical imaging via physics-informed unsupervised learning. Classical INR

Distributional Principal Autoencoders

arXiv:2404.13649v2 Announce Type: replace-cross Abstract: Dimension reduction techniques usually lose information in the sense that reconstructed data are not identical to the original data. However,

Efficient Handwriting-Based Alzheimer,s Disease Diagnosis Using a Low-Rank Mixture of Experts Deep Learning Framework

arXiv:2605.04079v1 Announce Type: new Abstract: Early and reliable detection of Alzheimer's disease (AD) is crucial for timely clinical intervention and improved patient management. It also supports t

Encoding Predictability and Legibility for Style-Conditioned Diffusion Policy

arXiv:2603.16368v2 Announce Type: replace-cross Abstract: Striking a balance between efficiency and transparent motion is a core challenge in human-robot collaboration, as highly expressive movements

Endogenous Regime Switching Driven by Scalar-Irreducible Learning Dynamics

arXiv:2605.04054v1 Announce Type: new Abstract: Achieving endogenous regime switching is crucial for the emergence of autonomous intelligence, yet remains a central challenge for existing machine lear

agentsarxiv-cs-lg

Evaluation Cards for XAI Metrics

arXiv:2605.04410v1 Announce Type: new Abstract: The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and

Evidence-based anomaly detection in clinical domains

arXiv:2605.04664v1 Announce Type: new Abstract: Anomaly detection methods can be very useful in identifying interesting or concerning events. In this work, we develop and examine new probabilistic ano

Local Ai

FaSTA^*: Fast-Slow Toolpath Agent with Subroutine Mining for Efficient Multi-turn Image Editing

arXiv:2506.20911v2 Announce Type: replace Abstract: We develop a cost-efficient neurosymbolic agent to address challenging multi-turn image editing tasks such as ``Detect the bench in the image while

local-aiarxiv-cs-cv

FlowDIS: Language-Guided Dichotomous Image Segmentation with Flow Matching

arXiv:2605.05077v1 Announce Type: new Abstract: Accurate image segmentation is essential for modern computer vision applications such as image editing, autonomous driving, and medical image analysis.

agentsarxiv-cs-cv

FMI_SU_Yotkova_Kastreva at SemEval-2026 Task 13: Lightweight Detection of LLM-Generated Code via Stylometric Signals

arXiv:2605.04157v1 Announce Type: new Abstract: SemEval-2026 Task 13 investigates machine-generated code detection across multiple programming languages and application scenarios, asking participating

researcharxiv-cs-cl

GeoDecider: A Coarse-to-Fine Agentic Workflow for Explainable Lithology Classification

arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati

agentsarxiv-cs-ai

Gradient Flow Structure and Quantitative Dynamics of Multi-Head Self-Attention

arXiv:2605.04279v1 Announce Type: new Abstract: Transformer self-attention can be interpreted as a gradient flow on the unit sphere, in which tokens evolve under softmax interaction potentials and ten

GraphPI: Efficient Protein Inference with Graph Neural Networks

arXiv:2605.04376v1 Announce Type: new Abstract: The integration of deep learning approaches in biomedical research has been transformative, enabling breakthroughs in various applications. Despite thes

Height-Guided Projection Reparameterization for Camera-LiDAR Occupancy

arXiv:2605.05072v1 Announce Type: new Abstract: 3D occupancy prediction aims to infer dense, voxel-wise scene semantics from sensor observations, where the 2D-to-3D view transformation serves as a cru

applicationsarxiv-cs-cv

Hierarchical Support Vector State Partitioning for Distilling Black Box Reinforcement Learning Policies

arXiv:2605.04254v1 Announce Type: new Abstract: We introduce State Vector Space Partitioning (SVSP), a novel method to mimic a black box reinforcement learning policy using a set of human-interpretabl

Human-AI Co-Mentorship in Project-Based Learning: A Case Study in Financial Forecasting

arXiv:2605.05144v1 Announce Type: new Abstract: This paper reflects on a AI research project carried out by a team of high-school and early-undergraduate students under the mentorship of graduate rese

Improving Bias Correction Standards by Quantifying its Effects on Treatment Outcomes

arXiv:2407.14861v3 Announce Type: replace-cross Abstract: With the growing access to administrative health databases, retrospective studies have become crucial evidence for medical treatments. Yet, no

Improving Medical VQA through Trajectory-Aware Process Supervision

arXiv:2605.04064v1 Announce Type: cross Abstract: Reasoning capabilities are crucial for reliable medical visual question answering (VQA); however, existing datasets rarely include reasoning explanati

safetyarxiv-cs-cv

InterFuserDVS: Event-Enhanced Sensor Fusion for Safe RL-Based Decision Making

arXiv:2605.04355v1 Announce Type: new Abstract: Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often

safetyarxiv-cs-cv

InterMesh: Explicit Interaction-Aware End-to-End Multi-Person Human Mesh Recovery

arXiv:2605.04554v1 Announce Type: new Abstract: Humans constantly interact with their surroundings. Existing end-to-end multi-person human mesh recovery methods, typically based on the DETR framework,

ITBoost: Information-Theoretic Trust for Robust Boosting

arXiv:2605.04671v1 Announce Type: new Abstract: Gradient boosting remains a strong and widely used method for tabular data learning, but its performance often degrades when training labels are noisy.

Kinematic Discriminants of Deceleration Behavior Modes in Car-Following: Evidence from NGSIM Trajectory Data

arXiv:2605.05050v1 Announce Type: cross Abstract: Gap-closing rate and visual looming swap discriminative dominance depending on deceleration intensity - a finding that reconciles a long-standing conf

agentsarxiv-cs-lg

Layerwise LQR for Geometry-Aware Optimization of Deep Networks

arXiv:2605.04230v1 Announce Type: new Abstract: Geometry-aware optimizers such as Newton and natural gradient can improve conditioning in deep learning, but scalable variants such as K-FAC, Shampoo, a

Tutorials

LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection

arXiv:2605.04445v1 Announce Type: new Abstract: The rapid advancement of generative technologies has made synthetic images nearly indistinguishable from real ones, thereby creating an urgent need for

tutorialsarxiv-cs-cv

Lightning Unified Video Editing via In-Context Sparse Attention

arXiv:2605.04569v1 Announce Type: new Abstract: Video editing has evolved toward In-Context Learning (ICL) paradigms, yet the resulting quadratic attention costs create a critical computational bottle

LTGS: Long-Term Gaussian Scene Chronology From Sparse View Updates

arXiv:2510.09881v3 Announce Type: replace Abstract: Recent advances in novel-view synthesis can create the photo-realistic visualization of real-world environments from conventional camera captures. H

applicationsarxiv-cs-cv

MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks

arXiv:2312.06423v3 Announce Type: replace-cross Abstract: Machine learning (ML) has gained significant adoption in Android malware detection to address the escalating threats posed by the rapid prolif

Hardware

Massively Parallel Exact Inference for Hawkes Processes

arXiv:2604.01342v2 Announce Type: replace Abstract: Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as O(N^2) i

hardwarearxiv-cs-lg

Material Database Agent: A Multimodal Agentic Framework for Scientific Literature Mining

arXiv:2605.04278v1 Announce Type: new Abstract: Materials science workflows rely on structured and unstructured data from the vast body of available scientific literature. However, most of the experim

agentsarxiv-cs-cl

MenuNet: A Strategy-Proof Mechanism for Matching Markets

arXiv:2605.03216v1 Announce Type: cross Abstract: Strategy-proofness is a fundamental desideratum in mechanism design, ensuring truthful reporting and robust participation. Stability is another centra

safetyarxiv-cs-ai

Morphology-Guided Cross-Task Coupling for Joint Building Height and Footprint Estimation

arXiv:2605.04731v1 Announce Type: new Abstract: Building height (BH) and building footprint (BF) jointly describe the vertical and horizontal extent of the built environment and are required inputs fo

Multi-Scale Wavelet Transformers for Operator Learning of Dynamical Systems

arXiv:2602.01486v2 Announce Type: replace Abstract: Recent years have seen a surge in data-driven surrogates for dynamical systems that can be orders of magnitude faster than numerical solvers. Howeve

On the Architectural Complexity of Neural Networks

arXiv:2605.04325v1 Announce Type: new Abstract: We introduce a unified theoretical framework for the rigorous analysis and systematic construction of deep neural networks (DNNs). This framework addres

Optimize-at-Capture: Highly-adaptive Exposure Controlling for In-Vehicle Non-contact Heart-rate Monitoring

arXiv:2605.04397v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) holds great promise for continuous heart-rate monitoring of drivers in intelligent vehicles. However, its performance

Pack it in: Packing into Partially Filled Containers Through Contact

arXiv:2602.12095v3 Announce Type: replace Abstract: The automation of warehouse operations is crucial for improving productivity and reducing human exposure to hazardous environments. One operation fr

researcharxiv-cs-ro

PAIR-CI: Calibrated Conditional Independence Testing for Causal Discovery with Incomplete Data

arXiv:2605.04838v1 Announce Type: cross Abstract: The standard constraint-based paradigm for causal discovery with incomplete data -- impute first, test second -- is frequently miscalibrated: any cons

PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World

arXiv:2605.05163v1 Announce Type: new Abstract: Synthesizing physics-grounded 3D assets is a critical bottleneck for interactive virtual worlds and embodied AI. Existing methods predominantly focus on

Physical Adversarial Clothing Evades Visible-Thermal Detectors via Non-Overlapping RGB-T Pattern

arXiv:2605.04675v1 Announce Type: new Abstract: Visible-thermal (RGB-T) object detection is a crucial technology for applications such as autonomous driving, where multimodal fusion enhances performan

agentsarxiv-cs-cv

Predictive and Prescriptive AI toward Optimizing Wildfire Suppression

arXiv:2605.04510v1 Announce Type: cross Abstract: Intense wildfire seasons require critical prioritization decisions to allocate scarce suppression resources over a dispersed geographical area. This p

Programmatic Context Augmentation for LLM-based Symbolic Regression

arXiv:2605.03101v1 Announce Type: new Abstract: Symbolic regression (SR), the task of discovering mathematical expressions that best describe a given dataset, remains a fundamental challenge in scient

researcharxiv-cs-ai