Search: “models”

Concept Drift Adaptation Using Self-Supervised and Reinforcement Learning In Android Malware Detection

arXiv:2605.24294v1 Announce Type: cross Abstract: Android malware detectors often degrade after deployment because of concept drift, while full retraining at each maintenance step is costly. We propos

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Context-CoT: Enhancing Context Learning via High-Quality Reasoning Synthesis

DGX agent

arXiv:2605.25354v1 Announce Type: new Abstract: While LLMs excel at reasoning over prompts using static pretrained knowledge, they struggle significantly with context learning-the ability to dynamical

researcharxiv-cs-ai

26 May 2026

Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards

arXiv:2602.08499v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is an effective paradigm for improving the reasoning capabilities of large language mode

CRISP -- Clustering-Based Redundancy-Reduced Instance Sampling for Pathology Case Representation and Retrieval

arXiv:2605.24253v1 Announce Type: cross Abstract: Digital pathology archives increasingly contain multiple whole-slide images (WSIs) per case, capturing spatially distinct tumour regions and reflectin

agentsarxiv-cs-ai

Cross-Stage Attention Multi-Expert Network for Radiologist-Inspired Breast Ultrasound Diagnosis

arXiv:2605.25518v1 Announce Type: cross Abstract: Breast ultrasound imaging is an important noninvasive method for early breast cancer diagnosis, but automatic benign/malignant classification remains

Cultivating Machine Intelligence: The OMEGA Shift from Top-Down Optimization to Autopoietic Cognitive Ecologies

arXiv:2605.25062v1 Announce Type: cross Abstract: The dominant artificial intelligence paradigm trains neural architectures via gradient descent against proxy objectives and reinforcement learning fro

CUNY at CLPsych 2026: A Pipeline Approach to Classification and Summarization of Mental Health Changes

arXiv:2605.24164v1 Announce Type: new Abstract: We describe our submission to the CLPsych~2026 Shared Task on capturing and characterizing mental health changes through social media timeline dynamics.

researcharxiv-cs-cl

DeGRe: Dense-supervised Generative Reranking for Recommendation

arXiv:2605.25749v1 Announce Type: cross Abstract: In multi-stage recommender systems, reranking optimizes overall utility by capturing intra-list contextual dependencies, yet its central challenge lie

Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces

arXiv:2602.05961v2 Announce Type: replace Abstract: Sampling from a distribution p(x) propto e^{-E(x)} known up to a normalising constant is an important and challenging problem in statistics. Recent

Diverse via bounded Agreement: Geometric Regularization for Multimodal Fusion

arXiv:2601.21670v3 Announce Type: replace-cross Abstract: Multimodal fusion is often treated as an optimization-balancing problem, where training signals are adjusted to prevent one modality from domi

Document Classification Pattern Recognition via Information Fusion: A Systematic Review of Multimodal and Multiview Representation Approaches

arXiv:2605.23910v1 Announce Type: cross Abstract: Information fusion is used widely to improve document classification by the integration of multiple data sources (multimodal) or representations (mult

Dynamic Relational Priming Improves Transformer in Multivariate Time Series

arXiv:2509.12196v2 Announce Type: replace-cross Abstract: Standard attention mechanisms in transformers employ static token representations that remain unchanged across all pair-wise computations in e

Enhanced INS/GNSS State Estimation using GNSS-Based Acceleration Measurements

arXiv:2605.24767v1 Announce Type: new Abstract: Accurate and reliable navigation is essential for autonomous ground vehicle operations. Standard INS/GNSS fusion relies on GNSS position updates, which

agentsarxiv-cs-ro

Evolutionary Physics-Informed Temporal Fusion for Lane-Change Intention Prediction

arXiv:2512.24075v5 Announce Type: replace Abstract: Early lane-change intention prediction is essential for autonomous driving and ADAS, but it remains challenging because lane-changing behavior depen

agentsarxiv-cs-lg

Exploring Profiles of Cognitive Distortions Associated with Mental Health Disorders

arXiv:2605.24996v1 Announce Type: new Abstract: Cognitive distortions, distorted patterns of thinking, have been increasingly studied in computational mental health research. Although they are related

researcharxiv-cs-cl

Feature Lottery? A Bifurcation Theory of Concept Emergence

arXiv:2605.24057v1 Announce Type: cross Abstract: Neural networks acquire structured representations at specific moments during training, yet identifying these transitions typically relies on retrospe

Tutorials

Fermi-Dirac machines as quantizations of neurons

arXiv:2605.24386v1 Announce Type: cross Abstract: Fermi-Dirac machines were proposed recently as an approach to solving semidefinite optimization problems on quantum computers. Here, we reinterpret th

tutorialsarxiv-cs-lg

FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning

arXiv:2502.01184v2 Announce Type: replace-cross Abstract: Molecular representation learning methods typically tokenize molecules as individual atoms or use rigid, rule-based fragment decompositions, l

From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems

arXiv:2605.23955v1 Announce Type: new Abstract: Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabil

agentsarxiv-cs-ai

Local Ai

G-DRAGON: Geospatial Reasoning and Dynamic Planning for Retrieval-Augmented Outdoor Navigation

arXiv:2605.25646v1 Announce Type: new Abstract: Autonomous ground robots operating in large-scale outdoor environments require both robust long-range navigation and fine-grained ''last-mile'' explorat

local-aiarxiv-cs-ro

Tutorials

Gaussian Rank-Based Neighborhood Degree for Graph Neural Networks in Image Classification

arXiv:2605.24367v1 Announce Type: cross Abstract: The exponential growth of data has intensified the gap between the availability of unlabeled data and the high cost of manual annotation. Graph Neural

tutorialsarxiv-cs-lg

Generative AI impacts on intra-urban inequality and skill premium in Beijing

arXiv:2605.25505v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) is the first automation wave to reach high-cognitive tasks at scale, yet its effects on intra-urban inequal

GeoMathCode: Understanding Interleaved Math-Code Reasoning for Geometry Problem Solving

arXiv:2605.25384v1 Announce Type: new Abstract: Mathematical reasoning is a hallmark of human intelligence, requiring logical deduction, symbolic manipulation, and abstract thinking. Recent multimodal

researcharxiv-cs-cl

Geometric Workspace Analysis and Transmission-Aware Dynamics of a Serial Spherical Tool for Microsurgery

arXiv:2605.24760v1 Announce Type: new Abstract: We present a kinematic and transmission-aware design framework for a serial spherical mechanism with an additional translational degree of freedom for m

researcharxiv-cs-ro

Global Sequential Testing for Multi-Stream Auditing

arXiv:2602.21479v2 Announce Type: replace-cross Abstract: Across many risk-sensitive areas, it is critical to continuously audit machine learning systems as we receive more data to quickly determine i

applicationsarxiv-cs-lg

GRAIL: AI translation for scientists application workflow on satellite data

arXiv:2605.24784v1 Announce Type: new Abstract: Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrate

agentsarxiv-cs-ai

Growing a Neural Network in Breadth, Depth, and Time

arXiv:2605.25174v1 Announce Type: cross Abstract: Spatial and temporal resource constraints are critical for both biological and artificial intelligent systems. Here we define differentiable cost term

Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning

arXiv:2605.24613v1 Announce Type: cross Abstract: Post-hoc repair of LLM mathematical reasoning introduces an asymmetric risk: fixing an incorrect reasoning trace is useful, but replacing a trace that

Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs

arXiv:2605.24774v1 Announce Type: new Abstract: We propose Hermite-NGP, a gradient-augmented multi-resolution hash encoding designed to enable fast and accurate computation of spatial derivatives for

Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio

arXiv:2605.25967v1 Announce Type: new Abstract: As policy catches up with the capabilities of generative AI, watermarking is central to content provenance efforts. Inference-time watermarks for autore

Hide-and-Shill: A Reinforcement Learning Framework for Market Manipulation Detection in Symphony-a Decentralized Multi-Agent System

arXiv:2507.09179v3 Announce Type: replace Abstract: Decentralized finance (DeFi) has introduced a new era of permissionless financial innovation but also led to unprecedented market manipulation. With

Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment

arXiv:2605.24180v1 Announce Type: cross Abstract: Collaboration is the defining mode of modern science, yet its core mechanism -- feedback -- remains hard to observe, difficult to scale, and unequally

applicationsarxiv-cs-ai

Hybrid Quantum Neural Network for Multivariate Clinical Time Series Forecasting

arXiv:2603.08072v2 Announce Type: replace Abstract: Forecasting physiological signals can support proactive monitoring and timely clinical intervention by anticipating critical changes in patient stat

Hyperspectral Image Data Reduction for Endmember Extraction

arXiv:2512.10506v3 Announce Type: replace-cross Abstract: Endmember extraction from hyperspectral images aims to identify the spectral signatures of materials present in a scene. Recent studies have s

Implicit Null-space Manifold Generation for Redundant Robotic Systems

arXiv:2605.25770v1 Announce Type: new Abstract: Robotic systems with redundant degrees of freedom can achieve the same task outcome using multiple configurations, resulting in solution sets that form

researcharxiv-cs-ro

Incorporating Deep Learning Design in Database Queries

arXiv:2605.24207v1 Announce Type: cross Abstract: Deep learning over relational databases is conventionally realized by translating data into graph representations and applying graph-based neural netw

Influence-Inspired Spectral Rotations for Extreme Low-Bit LLM Quantization

arXiv:2605.25203v1 Announce Type: cross Abstract: We apply the influence-adaptive Walsh geometry of a companion theory paper (arXiv:2605.01637) to extreme low-bit weight-only LLM quantization. The rec

Invariant-Based Weight Sharing for Message Passing

arXiv:2605.25750v1 Announce Type: new Abstract: Message-passing neural networks (MPNNs) are a powerful framework for learning representations of graph-structured domains. However, weights in MPNNs act

applicationsarxiv-cs-lg

Is Decentralized AI Governable? From Regulative Policy to Constitutive Protocol

arXiv:2605.24538v1 Announce Type: cross Abstract: Every major framework for governing artificial intelligence presupposes an identifiable entity -- a developer, deployer, or operator -- who can be hel

Iterative Feature Space Optimization through Incremental Adaptive Evaluation

arXiv:2501.14889v2 Announce Type: replace Abstract: Iterative feature space optimization involves systematically evaluating and adjusting the feature space to improve downstream task performance. Howe

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients

arXiv:2605.24876v1 Announce Type: cross Abstract: We introduce a novel neural operator architecture designed to approximate solutions of linear elliptic partial differential equations with high-contra

L2IR: Revealing Latent Intent in Graph Fraud Detection

arXiv:2605.26040v1 Announce Type: new Abstract: Graph fraud detection has long depended on Graph Neural Networks (GNNs) to propagate and aggregate information across relational data. A critical obstac

applicationsarxiv-cs-ai

Lake Detection and Water Quality Estimation in Sentinel-2 Data

arXiv:2605.24515v1 Announce Type: new Abstract: With climate change and increasing human pressure on natural landscapes, inland water resources are becoming progressively scarcer, more vulnerable, and

applicationsarxiv-cs-lg

Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition

arXiv:2605.23960v1 Announce Type: cross Abstract: Proteins encode diverse functions within complex three-dimensional structures, yet most deep learning representations remain highly entangled, obscuri

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling

arXiv:2605.23957v1 Announce Type: new Abstract: Learning-assisted hyper-heuristics can select among dispatching rules while preserving the feasibility and interpretability of constructive Job Shop Sch

Tutorials

Mean-Shift PCA by Knockoff Mean

arXiv:2605.25460v1 Announce Type: cross Abstract: Removing noise is difficult, but adding noise is easy. In this work, we show how to eliminate mean-shift noisy components from PCA by deliberately int

tutorialsarxiv-cs-lg

Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data

arXiv:2605.25004v1 Announce Type: cross Abstract: Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intellig

Mitigating Gradient Pathology in PINNs through Aligned Constraint

arXiv:2605.25001v1 Announce Type: new Abstract: While Physics-Informed Neural Networks (PINNs) are powerful for solving Partial Differential Equations (PDEs), their training is often paralyzed by grad