Search: “models”

Graph Is the Verifier: Agentic Reinforcement Learning for Interprocedural Vulnerability Detection

arXiv:2607.26656v1 Announce Type: cross Abstract: Real-world vulnerabilities often span multiple functions, yet most learning-based detectors classify each function in isolation: on a sample of real C

safetyarxiv-cs-ai

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Heterogeneous Ranking in Industrial-Scale Recommender Systems: A Case Study

DGX agent

arXiv:2607.27577v1 Announce Type: cross Abstract: Heterogeneous recommendation feeds present complex challenges that extend beyond those found in highly homogeneous environments (e.g., music-only or v

safetyarxiv-cs-lg

31 Jul 2026

Improved Classification of Nitrogen Stress Severity in Plants Under Combined Stress Conditions Using Spatio-Temporal Deep Learning Framework

arXiv:2509.06625v3 Announce Type: replace Abstract: Plants in their natural habitats endure an array of interacting stresses, both biotic and abiotic, that rarely occur in isolation. Nutrient stress-p

Improving the Robustness/Accuracy Tradeoff Against Adversarial Attacks Using Information Bottleneck Distillation Through Dual Teachers

arXiv:2607.27737v1 Announce Type: new Abstract: Deep neural networks (DNNs) have achieved remarkable success in classical machine learning problems. However, they are known to be vulnerable to adversa

Information Bottleneck Learning for Faithful Time Series Forecasting Explanations

arXiv:2607.28124v1 Announce Type: new Abstract: As forecasts increasingly drive decisions in fields such as energy, transportation, and healthcare, understanding the historical data behind these predi

applicationsarxiv-cs-lg

Isolating to Harness: Cross-Division Distillation for Fully Unsupervised Anomaly Detection

arXiv:2508.18007v2 Announce Type: replace Abstract: Fully Unsupervised Anomaly Detection (FUAD) addresses the practical scenario where training data is contaminated with unlabeled anomalies. This sett

tutorialsarxiv-cs-cv

Learning to Detect Cyber Attacks: Neural Anomaly Detection for Cybersecurity with Theoretical Insights

arXiv:2409.08521v2 Announce Type: replace-cross Abstract: In cybersecurity practice, new forms of cyberattacks continuously emerge, deliberately designed to evade defense systems that rely on previous

tutorialsarxiv-cs-lg

MIND: Multimodal Intent-Driven Network via Diffusion Transformers for Medical Image Fusion

arXiv:2607.28565v1 Announce Type: new Abstract: Medical image fusion aims to integrate complementary information from diverse imaging modalities to support clinical diagnosis. Existing methods typical

safetyarxiv-cs-cv

MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian

arXiv:2209.00546v5 Announce Type: replace-cross Abstract: Signed and directed networks are ubiquitous in real-world applications. However, there has been relatively little work proposing spectral grap

applicationsarxiv-cs-lg

Now You Have My Healthy Attention: A U-DiT for Brain-MRI Inpainting

arXiv:2607.27974v1 Announce Type: new Abstract: The ASNR-MICCAI BraTS Local Synthesis (Inpainting) task asks for the anatomically plausible completion of healthy brain tissue within a masked region of

local-aiarxiv-cs-cv

Agents

Pramana: A Composable, Domain-Specific Backend for Empirical Networking Research

arXiv:2607.26352v1 Announce Type: cross Abstract: Networking research advances by turning hypotheses into empirical evidence, so accelerating it means reducing the lag between ideation (synthesizing a

agentsarxiv-cs-ai

Quadratic Objective Perturbation: Curvature-Based Differential Privacy

arXiv:2605.05905v2 Announce Type: replace Abstract: Objective perturbation is a standard mechanism in differentially private empirical risk minimization. In particular, Linear Objective Perturbation (

Random Projection Flows for Efficient Manifold Density Estimation

arXiv:2509.25228v3 Announce Type: replace Abstract: Accurate density estimation is crucial for understanding complex high-dimensional data, but it becomes challenging when the data lies on or near low

Hardware

ReGenVC: End-to-End Real-Time Generative Video Coding at Ultra-Low Bitrate

arXiv:2607.28144v1 Announce Type: cross Abstract: We present ReGenVC, an end-to-end generative video codec that compresses talking-head video to an ultra-low bitrate and decodes it in real time. The e

hardwarearxiv-cs-cv

Rethinking EEG-Based Disease Diagnosis: Decoupling Instance Representation Learning from Subject-Level Supervision

arXiv:2607.27274v1 Announce Type: new Abstract: EEG-based disease diagnosis requires one prediction per subject, yet common pipelines segment recordings into short instances, inherit the subject label

SAFViT: Spatial Attention Fusion Gating for Vision Transformer-Based Nucleus Segmentation and Classification

arXiv:2607.27835v1 Announce Type: new Abstract: Accurate cell segmentation and classification are foundational to digital pathology, enabling quantitative tissue analysis for diagnosis and treatment p

tutorialsarxiv-cs-cv

SciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions

arXiv:2607.27955v1 Announce Type: cross Abstract: Scientific processes are often described in heterogeneous article discourse, with details needed for comparison, reproducibility, reuse, and automatio

SCOPE: Supply-Chain Operations through Coupled Policies for End-to-End Coordination

arXiv:2607.28488v1 Announce Type: cross Abstract: Can supply-chain AI move beyond isolated decision modules toward unified operational planning? A complete replenishment plan specifies which products

safetyarxiv-cs-lg

Semantic-Aligned Structural Abstraction for Multimodal Sentiment Analysis

arXiv:2607.27790v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) aims to interpret complex human emotions by integrating natural language with non-verbal modalities. Non-verbal moda

Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus

arXiv:2607.28304v1 Announce Type: new Abstract: Machine learning is transforming molecular sciences by accelerating property prediction, simulation, and the discovery of new molecules and materials. A

Structuring Quantitative Image Analysis with Object Prominence

arXiv:2409.00216v2 Announce Type: replace Abstract: When photographers or media professionals compose an image, they make deliberate choices about what to foreground and what to background, shaping ho

SUNSET - A Sensor-fUsioN based semantic SegmEnTation exemplar for ROS-based self-adaptation

arXiv:2601.13732v2 Announce Type: replace Abstract: The fact that robots are getting deployed more often in dynamic environments, together with the increasing complexity of their software systems, rai

tutorialsarxiv-cs-ro

TCA-SIR: Learning Target-Conditioned Abstractions for Scientific Inspiration Retrieval

arXiv:2607.28498v1 Announce Type: cross Abstract: Scientific hypothesis generation for AI for Science typically involves Scientific Inspiration Retrieval (SIR) followed by hypothesis composition. Exis

Towards joint scaling laws with optimal batch size schedules

arXiv:2607.27731v1 Announce Type: new Abstract: Modern deep learning typically keeps the batch size static throughout training, thus overlooking the joint effect of learning rate and batch size on the

Towards Structurally Explainable Machine-Generated Text Detection: A Graph-Perspective Framework

arXiv:2505.12507v2 Announce Type: replace Abstract: Despite the success of machine-generated text detectors, the black-box nature remains a critical limitation. Traditional explainability methods rely

TSOG: A Format For Temporally And Spatially Ordered Gaussians

arXiv:2607.28049v1 Announce Type: cross Abstract: We propose Temporally and Spatially Ordered Gaussians (TSOG), a format for efficient representation of 4D Gaussian Splatting (4DGS) content. TSOG exte

Uncertainty-Aware Multimodal Fusion for Oral Lesion Classification

arXiv:2511.12268v3 Announce Type: replace-cross Abstract: Early detection of oral cancer and potentially malignant diseases is a major challenge in low-resource settings due to the scarcity of annotat

applicationsarxiv-cs-cv

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning

arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver

applicationsarxiv-cs-cl

ZAPs: A Reward Attribution Framework for DeFi Ecosystems with Adversarial-Robust Scoring via Parallel Anomaly Ensemble Detection

arXiv:2607.27859v1 Announce Type: cross Abstract: Incentive programs are central to user acquisition in decentralized finance, but many reward systems rely on raw volume, transaction count, and wallet

applicationsarxiv-cs-lg

3DGBGS: 3D Granular Ball Gaussian Splatting for Compact Novel View Synthesis

arXiv:2607.26578v1 Announce Type: new Abstract: Three-dimensional Gaussian Splatting (3DGS) enables high-quality real-time novel-view synthesis through explicit Gaussian primitives and differentiable

local-aiarxiv-cs-cv

AgentGUI: An Interface for Observing and Steering Long-Running AI Agents

arXiv:2607.26300v1 Announce Type: new Abstract: AI agents are increasingly adept at tackling complex, long-running tasks. With the rapid surge of autonomous capabilities, human oversight is systematic

local-aiarxiv-cs-cl

AIGen: Automating AI Bill of Materials Generation Through Hybrid MLOps Integration

arXiv:2607.26652v1 Announce Type: new Abstract: The responsible development and deployment of artificial intelligence (AI) systems requires rigorous documentation of their constituent artifacts, e.g.,

Benchmarking ConvLSTM for One-Day-Ahead IMDAA Rainfall-Field Prediction across Four Indian Cities

arXiv:2607.26581v1 Announce Type: new Abstract: Convolutional long short-term memory networks (ConvLSTMs) are widely used for precipitation forecasting, but most evidence for their performance comes f

Chaos Is a LADDER: Domain Generalization Beyond Invariance via Reweighting

arXiv:2607.26458v1 Announce Type: cross Abstract: Domain generalization (DG) aims to learn from multiple source domains and generalize to unseen target domains. Most DG methods pursue invariance: they

tutorialsarxiv-cs-lg

Contrastive ESA: Human Evaluation of Multiple Translations at Once

arXiv:2607.26640v1 Announce Type: new Abstract: Current human evaluation of machine translation typically assesses single outputs in isolation, a paradigm that suffers from high annotator noise and co

Domain adaptation for handwriting trajectory reconstruction from IMU sensors

arXiv:2607.26736v1 Announce Type: new Abstract: Digital pens are commonly used to write on digital devices, providing the handwriting trace and enhancing human-computer interation. This study focuses

Agents

DVPSFormer: Efficient Online Depth-aware Video Panoptic Segmentation for Autonomous Driving

arXiv:2607.26165v1 Announce Type: new Abstract: Safe autonomous navigation requires a holistic understanding of dynamic environments, necessitating the simultaneous estimation of metric depth, semanti

agentsarxiv-cs-cv

Feature Bagging Provides Stability

arXiv:2607.26964v1 Announce Type: cross Abstract: We study feature bagging through the lens of algorithmic stability. Feature bagging is an ensemble strategy that aggregates base learners trained on r

Hierarchical Spatio-Temporal Transformer for Coherent Emergency Department Forecasting

arXiv:2607.27106v1 Announce Type: new Abstract: Emergency Departments (EDs) are critical access points in healthcare systems, yet they face persistent pressure from unpredictable patient demand, seaso

local-aiarxiv-cs-lg

Interpretable Image-Level Acne Severity Grading via EfficientNet-B0 Transfer Learning and Grad-CAM

arXiv:2607.26461v1 Announce Type: new Abstract: Acne vulgaris affects most adolescents and many adults. Accurate severity grading guides treatment, monitoring, and clinical trial endpoints, but manual

LAMUS: A Large-Scale Corpus for Legal Argument Mining from U.S. Caselaw using LLMs

arXiv:2603.08286v2 Announce Type: replace Abstract: Legal argument mining aims to identify and classify the functional components of judicial reasoning, such as facts, issues, rules, analysis, and con

applicationsarxiv-cs-cl

Learning the Word Problem: Geodesic Lengths and Cryptographic Applications

arXiv:2607.26241v1 Announce Type: cross Abstract: The Word Problem has been a subject of intensive mathematical study for over a century, initially driving advances in combinatorial group theory and m

One-Frame Calibration with Siamese Network in Facial Action Unit Recognition

arXiv:2409.00240v2 Announce Type: replace Abstract: Automatic facial action unit (AU) recognition is used widely in facial expression analysis. Most existing AU recognition systems aim for cross-parti

safetyarxiv-cs-cv

Physically Real-time Infrared Attack against Optical Flow Estimation Networks

arXiv:2607.26651v1 Announce Type: new Abstract: With the promising performance of deep neural networks on image-based tasks, different real-world applications such as autonomous driving and motion det

safetyarxiv-cs-cv

Q-Steer: Action-Value Guidance for Molecular Policy Optimization

arXiv:2607.26391v1 Announce Type: new Abstract: Oracle-limited molecular optimization gives reward only after a complete molecule is generated, while each rollout requires many local next-token decisi

local-aiarxiv-cs-lg

Registration-Grounded Spectral Fusion for Unregistered WLI/NBI Endoscopic Lesion Segmentation

arXiv:2607.26395v1 Announce Type: new Abstract: White-light imaging (WLI) and narrow-band imaging (NBI) provide complementary views of endoscopic lesions, but their paired observations are often spati

Robostreet Flow: A Lightweight, Ultra-Low-Drag Electric Tractor and Four-Truck Hybrid Convoy Architecture for Minimum-Cost Point-to-Point Freight

arXiv:2607.26250v1 Announce Type: new Abstract: Line-haul trucking costs are dominated by three comparably sized components: energy, driver labor, and equipment. Most efficiency technologies address o

safetyarxiv-cs-cl

SceneExpander: Text-Guided 3D Scene Expansion via Free-Form View Insertion

arXiv:2603.27084v3 Announce Type: replace Abstract: World building with 3D scene representations is increasingly important for content creation, simulation, and interactive experiences, yet real workf