Search: “applications”

Shape2Animal: Creative Animal Generation from Natural Silhouettes

arXiv:2506.20616v3 Announce Type: replace Abstract: Humans possess a unique ability to perceive meaningful patterns in ambiguous stimuli, a cognitive phenomenon known as pareidolia. This paper introdu

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Applications

Tailored Prompts, Targeted Protection: Vulnerability-Specific LLM Analysis for Smart Contracts

DGX agent

arXiv:2605.03697v1 Announce Type: cross Abstract: Smart contracts on blockchains are prone to diverse security vulnerabilities that can lead to significant financial losses due to their immutable natu

applicationsarxiv-cs-ai

7 May 2026

TNStream: Applying Tightest Neighbors to Micro-Clusters to Define Multi-Density Clusters in Streaming Data

arXiv:2505.00359v2 Announce Type: replace Abstract: In data stream clustering, systematic theory of stream clustering algorithms remains relatively scarce. Recently, density-based methods have gained

When LLMs get significantly worse: A statistical approach to detect model degradations

arXiv:2602.10144v2 Announce Type: replace-cross Abstract: Minimizing the inference cost and latency of foundation models has become a crucial area of research. Optimization approaches include theoreti

YOTOnet: Zero-Shot Cross-Domain Fault Diagnosis via Domain-Conditioned Mixture of Experts

arXiv:2605.04528v1 Announce Type: new Abstract: Mechanical equipment forms the critical backbone of modern industrial production, yet domain shift severely limits the generalization of deep learning b

Research

A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language

arXiv:2605.03696v1 Announce Type: new Abstract: The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there ar

researcharxiv-cs-cl

A Neuro-Symbolic Framework for Accountability in Public-Sector AI

arXiv:2512.12109v3 Announce Type: replace-cross Abstract: Automated eligibility systems increasingly determine access to essential public benefits, but the explanations they generate often fail to ref

A Unified Framework for Tabular Generative Modeling: Loss Functions, Benchmarks, and Improved Multi-objective Bayesian Optimization Approaches

arXiv:2405.16971v2 Announce Type: replace Abstract: Deep learning (DL) models require extensive data to achieve strong performance and generalization. Deep generative models (DGMs) offer a solution by

AhaRobot: A Low-Cost Open-Source Bimanual Mobile Manipulator for Embodied AI

arXiv:2503.10070v2 Announce Type: replace-cross Abstract: Scaling Vision-Language-Action models for embodied manipulation demands large volumes of diverse manipulation data, yet the high cost of comme

AI in Agriculture: A Survey of Deep Learning Techniques for Crops, Fisheries and Livestock

arXiv:2507.22101v2 Announce Type: replace Abstract: Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sec

AIs and Humans with Agency

arXiv:2605.02810v1 Announce Type: new Abstract: This paper compares agency in humans with potential agency in AI programs. Human agency takes many years to develop, as the frontal lobe is activated. E

AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics

arXiv:2605.03652v1 Announce Type: new Abstract: Video generation models internalize physical realism as their prior. Anime deliberately violates physics: smears, impact frames, chibi shifts; and its t

Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests

arXiv:2508.14936v3 Announce Type: replace-cross Abstract: Synthetic data holds substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns.

CC-OCR V2: Benchmarking Large Multimodal Models for Literacy in Real-world Document Processing

model-releasesarxiv-cs-cl

arXiv:2605.03903v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently shown strong performance on Optical Character Recognition (OCR) tasks, demonstrating their promising capabi

Conformalized Percentile Interval: Finite Sample Validity and Improved Conditional Performance

arXiv:2605.03233v1 Announce Type: cross Abstract: Conformal prediction provides distribution-free predictive intervals with finite-sample marginal coverage. However, achieving conditional validity and

Delay, Plateau, or Collapse: Evaluating the Impact of Systematic Verification Error on RLVR

arXiv:2605.02909v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a powerful approach for improving the reasoning capabilities of large language models (

Driving Style Recognition Like an Expert Using Semantic Privileged Information from Large Language Models

arXiv:2508.13881v2 Announce Type: replace Abstract: Existing driving style recognition systems largely depend on low-level sensor-derived features for training, neglecting the rich semantic reasoning

applicationsarxiv-cs-ro

Free Decompression with Algebraic Spectral Curves

arXiv:2605.03634v1 Announce Type: cross Abstract: Tools from random matrix theory have become central to deep learning theory, using spectral information to provide mechanisms for modeling generalizat

From Data Lifting to Continuous Risk Estimation: A Process-Aware Pipeline for Predictive Monitoring of Clinical Pathways

arXiv:2605.03895v1 Announce Type: new Abstract: This paper presents a reproducible and process-aware pipeline for predictive monitoring of clinical pathways. The approach integrates data lifting, temp

Hybrid Models for Natural Language Reasoning: The Case of Syllogistic Logic

model-releasesarxiv-cs-cl

arXiv:2510.09472v2 Announce Type: replace Abstract: Despite the remarkable progress in neural models, their ability to generalize, a cornerstone for applications such as logical reasoning, remains a c

KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation

arXiv:2605.01582v1 Announce Type: cross Abstract: Authoritative competency frameworks such as ESCO, ROME, and O*NET are essential for aligning education with labor market needs, yet their technical co

MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs

model-releasesarxiv-cs-ai

arXiv:2505.20740v3 Announce Type: replace Abstract: The rapid advancement of multimodal large language models (MLLMs) offers new opportunities for complex scientific challenges, yet their application

PAMNet: Cycle-aware Phase-Amplitude Modulation Network for Multivariate Time Series Forecasting

arXiv:2605.02938v1 Announce Type: new Abstract: Reliable periodic patterns serve as a fundamental basis for accurate multivariate time series forecasting. However, existing methods either implicitly e

Personalized Digital Health Modeling with Adaptive Support Users

arXiv:2605.02004v1 Announce Type: new Abstract: Personalized models are essential in digital health because individuals exhibit substantial physiological and behavioral heterogeneity. Yet personalizat

Agents

Practical Limits of Autonomous Test Repair: A Multi-Agent Case Study with LLM-Driven Discovery and Self-Correction

arXiv:2605.01471v1 Announce Type: cross Abstract: Maintaining reliable UI test suites in large-scale enterprise applications is a persistent and costly challenge. We present an industrial case study o

agentsarxiv-cs-ai

Rational Communication Shapes Morphological Composition

arXiv:2605.03510v1 Announce Type: new Abstract: Human languages expand vocabularies by combining existing morphemes rather than inventing arbitrary forms. Communicative efficiency shapes lexical syste

Re-Key-Free, Risky-Free: Adaptable Model Usage Control

arXiv:2511.18772v2 Announce Type: replace-cross Abstract: Deep neural networks (DNNs) have become valuable intellectual property of model owners, due to the substantial resources required for their de

Robustness and Transferability of Pix2Geomodel for Bidirectional Facies Property Translation in a Complex Reservoir

arXiv:2605.03919v1 Announce Type: cross Abstract: Reservoir geomodeling is central to subsurface characterization, but it remains challenging because conditioning data are sparse, geological heterogen

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning

arXiv:2601.04809v5 Announce Type: replace Abstract: Reinforcement learning (RL) offers a principled way to enhance the reasoning capabilities of large language models, yet its effectiveness hinges on

Strategy-Aware Optimization Modeling with Reasoning LLMs

arXiv:2605.02545v1 Announce Type: new Abstract: Large language models (LLMs) can generate syntactically valid optimization programs, yet often struggle to reliably choose an effective modeling strateg

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

The Manokhin Probability Matrix: A Diagnostic Framework for Classifier Probability Quality

arXiv:2605.03816v1 Announce Type: cross Abstract: The Brier score conflates two distinct properties of probabilistic predictions: reliability (calibration error) and resolution (discriminatory power).

Agents

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 High-Fidelity Digital Twin for Robotic Manipulation Based on 3D Gaussian Splatting

arXiv:2601.03200v2 Announce Type: replace Abstract: Developing high-fidelity, interactive digital twins is crucial for enabling closed-loop motion planning and reliable real-world robot execution, whi

applicationsarxiv-cs-ro

Tutorials

Adaptation of AI-accelerated CFD Simulations to the IPU platform

arXiv:2605.00462v1 Announce Type: cross Abstract: Intelligence Processing Units (IPU) have proven useful for many AI applications. In this paper, we evaluate them within the emerging field of AI for s

tutorialsarxiv-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

Arbitrarily Conditioned Hierarchical Flows for Spatiotemporal Events

arXiv:2605.01226v1 Announce Type: new Abstract: Events in spatiotemporal systems are ubiquitous, yet modeling their complex distributions remains challenging. Existing point process models often rely

ARMOR 2025: A Military-Aligned Benchmark for Evaluating Large Language Model Safety Beyond Civilian Contexts

model-releasesarxiv-cs-ai

arXiv:2605.00245v1 Announce Type: new Abstract: Large language models (LLMs) are now being explored for defense applications that require reliable and legally compliant decision support. They also hol

Automatic Reflection Level Classification in Hungarian Student Essays

arXiv:2605.02402v1 Announce Type: new Abstract: Reflective thinking is a key competency in education, but assessing reflective writing remains a time-consuming and subjective task for education expert

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

CADFS: A Big CAD Program Dataset and Framework for Computer-Aided Design with Large Language Models

arXiv:2605.01925v1 Announce Type: new Abstract: We introduce CADFS, a data-centric framework that enables large vision-language models to generate complex CAD design histories. Existing generative CAD

Can Causal Discovery Algorithms Help in Generating Legal Arguments?

arXiv:2605.02318v1 Announce Type: cross Abstract: In 2011, Judea Pearl received the Turing Award, considered the Nobel Prize in Computing, for fundamental contributions to artificial intelligence thro

CLEAR: Revealing How Noise and Ambiguity Degrade Reliability in LLMs for Medicine

arXiv:2605.01011v1 Announce Type: new Abstract: Medical large language model (LLM) evaluations rely on simplified, exam-style benchmarks that rarely reflect the ambiguity of real-world medical inquiri

CleverCatch: A Knowledge-Guided Weak Supervision Model for Fraud Detection

arXiv:2510.13205v3 Announce Type: replace Abstract: Healthcare fraud detection remains a critical challenge due to limited availability of labeled data, constantly evolving fraud tactics, and the high

Closed-Loop CO2 Storage Control With History-Based Reinforcement Learning and Latent Model-Based Adaptation

arXiv:2605.02405v1 Announce Type: new Abstract: Closed-loop management of geological CO2 storage requires control policies that adapt to uncertain reservoir behavior while relying on observations that

Complex Diffusion Maps with omega-Parameterized Kernels Revealing Inherent Harmonic Representations

arXiv:2605.01691v1 Announce Type: new Abstract: In this paper, we propose Complex Diffusion Maps (CDM), a novel diffusion mapping framework that aims to reveal the dominant complex harmonics of high-d

Compositional Multi-hop Factual Error Correction via Decomposition-and-Injection

arXiv:2605.02277v1 Announce Type: new Abstract: Factual Error Correction (FEC) aims to revise inaccurate text into statements that are factually consistent with external evidence. Although recent meth

CoRAL: Contact-Rich Adaptive LLM-based Control for Robotic Manipulation

arXiv:2605.02600v1 Announce Type: new Abstract: While Large Language Models (LLMs) and Vision-Language Models (VLMs) demonstrate remarkable capabilities in high-level reasoning and semantic understand

applicationsarxiv-cs-ro