Search: “applications”

An Information-Theoretic Approach to Identifying Formulaic Clusters in Textual Data

arXiv:2503.07303v3 Announce Type: replace Abstract: Texts, whether literary or historical, exhibit structural and stylistic patterns shaped by their purpose, authorship, and cultural context. Formulai

researcharxiv-cs-cl

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Research

Are the High-weight Neurons the Important Ones in Image Classification Neural Networks?

DGX agent

arXiv:2607.25529v1 Announce Type: new Abstract: As neural network models for image classification advance, neurons play critical roles in pruning, backdoor defense, and interpretability. Yet existing

researcharxiv-cs-ai

29 Jul 2026

Automatic Knowledge Graph Construction and Query for Earthquake Catalogs

arXiv:2607.24984v1 Announce Type: cross Abstract: In recent years, the number of events in earthquake catalogs has significantly increased due to the utilization of more effective deep learning based

agentsarxiv-cs-ai

Behavior-Driven Explainability

arXiv:2607.24881v1 Announce Type: new Abstract: As system complexity has vastly increased, it has become significantly more challenging for a single person or a team to fully understand all aspects of

safetyarxiv-cs-lg

Contrastive Weak-to-strong Generalization

arXiv:2510.07884v3 Announce Type: replace-cross Abstract: Weak-to-strong generalization provides a promising paradigm for scaling large language models (LLMs) by training stronger models on samples fr

safetyarxiv-cs-ai

Data-Dependent Regret and Polyak Corrections for Constrained Online Convex Optimization

arXiv:2607.25480v1 Announce Type: new Abstract: Constrained online convex optimization requires minimizing regret against adversarial convex costs while satisfying a convex constraint at every round,

safetyarxiv-cs-lg

Decision-Level Hijacking: Injecting Cognitive Bias into Large Language Models via Bit-Flip Attacks

arXiv:2607.25227v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly

Desktop-Delta Bench: Do Computer-Use Models Understand Desktop GUI Transitions?

model-releasesarxiv-cs-ai

arXiv:2607.26041v1 Announce Type: new Abstract: Computer-use agents (CUAs) increasingly act through desktop GUIs to complete long-horizon tasks. Current benchmarks primarily measure end-task success o

Diff-ID: Identity Consistent Facial Image Generation and Morphing via Diffusion Models

arXiv:2607.25078v1 Announce Type: new Abstract: Generative diffusion models have revolutionized facial image synthesis, yet robust identity preservation in high resolution outputs remains a critical c

Distributing Security Controls Through Harness Engineering

arXiv:2607.25890v1 Announce Type: new Abstract: AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizatio

agentsarxiv-cs-ai

Tutorials

From Idea to Classroom in Days: Using 'Vibe Coding' to Create a Programming Process Visualizer from IDE Activity Logs

arXiv:2607.24757v1 Announce Type: cross Abstract: This paper reports on the rapid development and classroom deployment of a Thonny log visualizer built using AI-assisted ``vibe coding'' to make studen

tutorialsarxiv-cs-ai

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI

arXiv:2602.15021v2 Announce Type: replace-cross Abstract: Cross-survey generalization is a critical challenge in stellar spectral analysis, particularly in cases such as transferring from low- to mode

HOLODECK 2.0: Vision-Language-Guided 3D World Generation with Editing

arXiv:2508.05899v3 Announce Type: replace Abstract: 3D scene generation plays a crucial role in gaming, artistic creation, virtual reality, and many other domains. However, current 3D scene design sti

Instruction-Tuned Language Models Cannot Sample from Distributions They Can Describe

model-releasesarxiv-cs-ai

arXiv:2607.25292v1 Announce Type: new Abstract: Silicon sampling uses language models as proxies for human survey respondents, treating each model call as an independent draw from the persona's respon

LGFNet: A CTC-Guided Local-Global Fusion Framework for Single-Channel Sleep Staging

arXiv:2607.25197v1 Announce Type: new Abstract: Sleep staging remains challenging due to long-range temporal dependencies, ambiguous stage transitions-particularly in N1-and substantial distribution s

safetyarxiv-cs-cv

Machine Intelligence on the Edge: Interpretable Cardiac Pattern Localisation Using Reinforcement Learning

arXiv:2508.21652v2 Announce Type: replace-cross Abstract: Matched filters are widely used to localise signal patterns due to their high efficiency and interpretability. However, their effectiveness de

agentsarxiv-cs-lg

MemLens: A Value-Aware Memory Management System with Interactive Analytics for LLM-based Agents

arXiv:2607.25992v1 Announce Type: cross Abstract: Recently, memory management has become a key infrastructure for LLM-based agents, as it directly affects long-horizon reasoning, personalized response

Local Ai

Mind the Missing Split: Resolving Feature Heterogeneity in Swarm Learning with Random Forests

arXiv:2607.25538v1 Announce Type: new Abstract: Swarm Learning is a decentralized collaborative learning mechanism that allows multiple organizations to train a shared model without central coordinati

local-aiarxiv-cs-lg

MODUS: Decoder-Only Any-to-Any Modeling of Diverse Modalities

arXiv:2607.25948v1 Announce Type: cross Abstract: Any-to-any models predict any modality from any combination of others within a single network, a formulation used in multimodal vision and vision-lang

Motion Generation With Environmental Constraints

arXiv:2607.25053v1 Announce Type: new Abstract: Robot motion planning faces challenges in high-dimensional spaces and uncertain environments, often constrained by the need for collision-free motions.

safetyarxiv-cs-ro

Tutorials

On the Design and Evaluation of Human-centered Explainable AI Systems: A Systematic Review and Taxonomy

arXiv:2510.12201v2 Announce Type: replace Abstract: As AI becomes more common in everyday living, there is an increasing demand for intelligent systems that are both performant and understandable. Exp

tutorialsarxiv-cs-ai

Optimal Ansatz-free Hamiltonian Learning In Situ

arXiv:2606.19486v2 Announce Type: replace-cross Abstract: Characterizing the features of a Hamiltonian that governs a quantum system serves as a fundamental subroutine of quantum device calibration, s

researcharxiv-cs-lg

PerceptionBench: Evaluating Atomic Visual Perception in Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2607.24957v1 Announce Type: new Abstract: We introduce PerceptionBench, a benchmark specifically designed to evaluate the atomic visual perception capabilities of Multimodal Large Language Model

Local Ai

Physics-Informed CNN-LSTM for Street-Scale Urban Flood Prediction: Reconciling Aggregate Accuracy and Street-Level Plausibility

arXiv:2607.25148v1 Announce Type: new Abstract: Deep learning surrogate models trained with mean-squared-error loss produce statistically accurate but physically unconstrained flood predictions: water

local-aiarxiv-cs-lg

Tutorials

PILA: Plug-and-Play Insertion for LLM-native Advertising

arXiv:2607.25590v1 Announce Type: new Abstract: How to monetize large language models (LLMs) by naturally integrating sponsored content into their responses, known as LLM-native advertising, has recen

tutorialsarxiv-cs-cl

Real-Time Driver Safety Scoring Through Inverse Crash Probability Modeling

arXiv:2603.14841v3 Announce Type: replace-cross Abstract: Road crashes remain a leading cause of preventable fatalities. Existing prediction models predominantly produce binary outcomes, which offer l

safetyarxiv-cs-ai

Real-time Spatial Retrieval Augmented Generation for Urban Environments

arXiv:2505.02271v2 Announce Type: replace Abstract: The proliferation of Generative Artificial Ingelligence (AI), especially Large Language Models, presents transformative opportunities for urban appl

Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes

arXiv:2601.20043v2 Announce Type: replace Abstract: Standard Bayesian Optimization (BO) assumes uniform smoothness across the search space an assumption violated in multi-regime problems such as molec

Right-sizing Recommendations (RSR): Cloud Workload Conformal Prediction for Virtual Machines in Data Center Operations

arXiv:2607.24773v1 Announce Type: new Abstract: Managing cloud infrastructure efficiently, especially in environments of large cloud providers or hyperscalers, requires optimizing the use of physical

RoboHarness: Memory-Driven Orchestration of Heterogeneous Robot Policies for Long-Horizon Planning

arXiv:2607.18060v2 Announce Type: replace Abstract: Long-horizon robotic tasks require diverse capabilities that no single policy can reliably provide. Heterogeneous policies offer complementary stren

safetyarxiv-cs-ro

S2A2: Audio-Visual Imitation Learning for Manipulation Tasks Using Acoustic Spatial Information

arXiv:2607.26047v1 Announce Type: new Abstract: Acoustic information provides rich cues about object location, material properties, and changes caused by contact or motion. This paper introduces a new

safetyarxiv-cs-ro

SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing

model-releasesarxiv-cs-ro

arXiv:2607.25388v1 Announce Type: new Abstract: Autonomous multi-vehicle racing requires real-time planning of diverse competitive behaviors in intense interactions. Existing planners often struggle t

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies

model-releasesarxiv-cs-cl

arXiv:2607.25716v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving training of automatic speech recognition (ASR) systems across distributed data sources, yet its appli

Steering topology distributions for unified generative design of architected metamaterials

arXiv:2607.24777v1 Announce Type: new Abstract: Architected metamaterials derive their functions from structure, creating vast opportunities to program physical responses through topology design. Howe

The LAIA Dataset: Labelled Attention for Intelligent Automobiles

arXiv:2607.25570v1 Announce Type: cross Abstract: The development of autonomous vehicles (AVs) usually relies heavily on data-driven artificial intelligence (AI) models that require large volumes of s

agentsarxiv-cs-ai

TIGA: Trajectory-Injected Generative Attack against Black-box AIGC Detectors

arXiv:2607.25894v1 Announce Type: new Abstract: Recent diffusion models have achieved remarkable realism in facial image synthesis, posing growing challenges to artificial intelligence-generated conte

Untangling Co-Drift: Proactive Multi-Intent Failure Prediction and Root-Cause Disambiguation for Self-Driving Networks

arXiv:2607.25989v1 Announce Type: cross Abstract: The vision of self-driving networks that monitor, reason, and act upon themselves with minimal human intervention relies on tightly coupled monitoring

Wall Shear Stress Reconstruction from Concentration: Differentiable Physics and Physics-Informed Neural Networks

arXiv:2606.06313v2 Announce Type: replace-cross Abstract: Wall shear stress (WSS) governs near-wall transport dynamics and is a key hemodynamic indicator in cardiovascular flows, yet remains difficult

A Modern ConvNet for Solar Filament Detection

arXiv:2607.24525v1 Announce Type: cross Abstract: Automated solar filament detection using deep learning faces several challenges. Semantic segmentation of solar filaments is a complicated multiscale

Adaptive Multi-Scale Forecasting and Gate-Localized Conformal Prediction for Multivariate Nonstationary Time Series

arXiv:2607.23165v1 Announce Type: cross Abstract: We propose ABF-T-GLCP, a model-agnostic framework for forecasting and uncertainty quantification in nonstationary multivariate time series. The centra

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data

arXiv:2603.07841v2 Announce Type: replace Abstract: Recent advances in large language models have strengthened Text2SQL systems that translate natural language questions into database queries. A persi

researcharxiv-cs-cl

AptAvatar: Fast and Vivid Long-Form Audio-Driven Video Generation for Production-Ready Avatars

model-releasesarxiv-cs-cv

arXiv:2607.24013v1 Announce Type: new Abstract: Production-ready audio-driven avatar generation requires efficient inference without sacrificing fidelity or motion expressiveness. However, existing ac

Asymmetric Hierarchical Anchoring for Robust Audio-Visual Cross-Modal Generalization

arXiv:2602.03570v2 Announce Type: replace Abstract: Audio-visual joint representation learning under Cross-Modal Generalization (CMG) aims to transfer knowledge from a labeled source modality to an un

safetyarxiv-cs-lg

AutoCluster, AutoTopicModeling, AutoTrendAnalysis: A Complete AutoML Pipeline for Predicting Emerging Trends

arXiv:2607.22641v1 Announce Type: cross Abstract: Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability.

Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment

arXiv:2607.22752v1 Announce Type: new Abstract: Face Image Quality Assessment (FIQA) aims to estimate the utility of facial images for reliable recognition. The evaluation of FIQA methods is predomina

Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks

arXiv:2410.02596v2 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) are a novel class of generative models designed to sample from unnormalized distributions and have found

safetyarxiv-cs-ai

Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities

arXiv:2607.24056v1 Announce Type: cross Abstract: Network-wide traffic volume estimation typically relies on propagating measurements from fixed sensors, making performance highly dependent on sensor

Catalyst Diffusion Transformer: Generative Inverse Design of Heterogeneous Catalysts

arXiv:2607.24272v1 Announce Type: cross Abstract: The vast chemical design space and complex, interdependent design variables make catalyst discovery for targeted properties highly labor- and resource

researcharxiv-cs-lg