Data Science

Data analysis, statistics, and data engineering

This Week's Best | Monthly Best | Guide | Trending

Top This Week

UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·
[2601.21463] Unifying Speech Editing Detection and Content Localization via Prior-Enhanced Audio LLMs
Llms

[2601.21463] Unifying Speech Editing Detection and Content Localization via Prior-Enhanced Audio LLMs

Abstract page for arXiv paper 2601.21463: Unifying Speech Editing Detection and Content Localization via Prior-Enhanced Audio LLMs

arXiv - AI · 4 min ·
[2601.02627] Improved Evidence Extraction and Metrics for Document Inconsistency Detection with LLMs
Llms

[2601.02627] Improved Evidence Extraction and Metrics for Document Inconsistency Detection with LLMs

Abstract page for arXiv paper 2601.02627: Improved Evidence Extraction and Metrics for Document Inconsistency Detection with LLMs

arXiv - AI · 3 min ·

All Content

[2504.14696] Reveal-or-Obscure: A Differentially Private Sampling Algorithm for Discrete Distributions
Machine Learning

[2504.14696] Reveal-or-Obscure: A Differentially Private Sampling Algorithm for Discrete Distributions

The paper presents a differentially private sampling algorithm, Reveal-or-Obscure (ROO), for generating samples from discrete distributio...

arXiv - Machine Learning · 4 min ·
[2504.05654] Curved representational Bregman divergences and their applications
Data Science

[2504.05654] Curved representational Bregman divergences and their applications

This article introduces curved representational Bregman divergences, exploring their mathematical foundations and applications in informa...

arXiv - Machine Learning · 4 min ·
[2502.17812] Can Multimodal LLMs Perform Time Series Anomaly Detection?
Llms

[2502.17812] Can Multimodal LLMs Perform Time Series Anomaly Detection?

The paper explores the potential of multimodal large language models (MLLMs) for time series anomaly detection (TSAD), introducing a new ...

arXiv - Machine Learning · 4 min ·
[2502.07397] Linear Bandits beyond Inner Product Spaces, the case of Bandit Optimal Transport
Machine Learning

[2502.07397] Linear Bandits beyond Inner Product Spaces, the case of Bandit Optimal Transport

This paper explores linear bandits beyond traditional inner product spaces, focusing on optimal transport problems. It proposes a refined...

arXiv - Machine Learning · 4 min ·
[2602.15600] The geometry of online conversations and the causal antecedents of conflictual discourse
Llms

[2602.15600] The geometry of online conversations and the causal antecedents of conflictual discourse

This article explores the dynamics of conflictual discourse in online conversations, particularly focusing on climate change discussions....

arXiv - AI · 4 min ·
[2602.15579] Intracoronary Optical Coherence Tomography Image Processing and Vessel Classification Using Machine Learning
Machine Learning

[2602.15579] Intracoronary Optical Coherence Tomography Image Processing and Vessel Classification Using Machine Learning

This paper presents a machine learning-based pipeline for automated segmentation and classification of vessels in Intracoronary Optical C...

arXiv - AI · 3 min ·
[2405.20178] Non-intrusive data-driven model order reduction for circuits based on Hammerstein architectures
Machine Learning

[2405.20178] Non-intrusive data-driven model order reduction for circuits based on Hammerstein architectures

This paper presents a non-intrusive data-driven model order reduction method for circuits using Hammerstein architectures, demonstrating ...

arXiv - Machine Learning · 4 min ·
[2602.11618] How Well Do Large-Scale Chemical Language Models Transfer to Downstream Tasks?
Llms

[2602.11618] How Well Do Large-Scale Chemical Language Models Transfer to Downstream Tasks?

This paper evaluates the effectiveness of large-scale Chemical Language Models (CLMs) in transferring knowledge to downstream molecular p...

arXiv - Machine Learning · 4 min ·
[2602.10706] Reducing Estimation Uncertainty Using Normalizing Flows and Stratification
Machine Learning

[2602.10706] Reducing Estimation Uncertainty Using Normalizing Flows and Stratification

This paper presents a novel approach to reducing estimation uncertainty in statistical analysis using normalizing flows and stratified sa...

arXiv - Machine Learning · 3 min ·
[2602.05999] On the Role of Iterative Computation in Reinforcement Learning
Machine Learning

[2602.05999] On the Role of Iterative Computation in Reinforcement Learning

This paper explores how the amount of compute available to reinforcement learning (RL) policies influences their learning capabilities an...

arXiv - Machine Learning · 4 min ·
[2602.00834] Don't Forget Its Variance! The Minimum Path Variance Principle for Accurate and Stable Score-Based Models
Machine Learning

[2602.00834] Don't Forget Its Variance! The Minimum Path Variance Principle for Accurate and Stable Score-Based Models

This paper introduces the Minimum Path Variance (MinPV) Principle, addressing the paradox of score-based methods in machine learning by m...

arXiv - Machine Learning · 3 min ·
[2602.00240] Green-NAS: A Global-Scale Multi-Objective Neural Architecture Search for Robust and Efficient Edge-Native Weather Forecasting
Machine Learning

[2602.00240] Green-NAS: A Global-Scale Multi-Objective Neural Architecture Search for Robust and Efficient Edge-Native Weather Forecasting

Green-NAS presents a multi-objective neural architecture search framework aimed at optimizing weather forecasting models for low-resource...

arXiv - Machine Learning · 4 min ·
[2601.19720] Improving Policy Exploitation in Online Reinforcement Learning with Instant Retrospect Action
Machine Learning

[2601.19720] Improving Policy Exploitation in Online Reinforcement Learning with Instant Retrospect Action

The paper presents a novel algorithm, Instant Retrospect Action (IRA), aimed at enhancing policy exploitation in online reinforcement lea...

arXiv - Machine Learning · 4 min ·
[2601.11440] GenDA: Generative Data Assimilation on Complex Urban Areas via Classifier-Free Diffusion Guidance
Machine Learning

[2601.11440] GenDA: Generative Data Assimilation on Complex Urban Areas via Classifier-Free Diffusion Guidance

The paper presents GenDA, a generative data assimilation framework for reconstructing urban wind fields from sparse sensor data, enhancin...

arXiv - AI · 4 min ·
[2601.02799] Stratified Hazard Sampling: Minimal-Variance Event Scheduling for CTMC/DTMC Discrete Diffusion and Flow Models
Machine Learning

[2601.02799] Stratified Hazard Sampling: Minimal-Variance Event Scheduling for CTMC/DTMC Discrete Diffusion and Flow Models

This article presents Stratified Hazard Sampling (SHS), a novel method for improving event scheduling in discrete diffusion and flow mode...

arXiv - Machine Learning · 4 min ·
[2601.01297] ARGUS: Adaptive Rotation-Invariant Geometric Unsupervised System
Data Science

[2601.01297] ARGUS: Adaptive Rotation-Invariant Geometric Unsupervised System

The paper introduces ARGUS, a novel framework for detecting distributional drift in high-dimensional data streams, emphasizing geometric ...

arXiv - AI · 4 min ·
[2602.15376] A Unified Evaluation of Learning-Based Similarity Techniques for Malware Detection
Ai Startups

[2602.15376] A Unified Evaluation of Learning-Based Similarity Techniques for Malware Detection

This paper presents a systematic evaluation of learning-based similarity techniques for malware detection, comparing various methods unde...

arXiv - AI · 4 min ·
[2601.01016] Improving Variational Autoencoder using Random Fourier Transformation: An Aviation Safety Anomaly Detection Case-Study
Machine Learning

[2601.01016] Improving Variational Autoencoder using Random Fourier Transformation: An Aviation Safety Anomaly Detection Case-Study

This study explores enhancements to Variational Autoencoders (VAEs) using Random Fourier Transformation (RFT) for anomaly detection in av...

arXiv - Machine Learning · 4 min ·
[2602.15373] Far Out: Evaluating Language Models on Slang in Australian and Indian English
Llms

[2602.15373] Far Out: Evaluating Language Models on Slang in Australian and Indian English

This paper evaluates the performance of language models on slang in Australian and Indian English, revealing significant gaps in understa...

arXiv - AI · 4 min ·
[2512.19057] Efficient Personalization of Generative Models via Optimal Experimental Design
Machine Learning

[2512.19057] Efficient Personalization of Generative Models via Optimal Experimental Design

This paper presents a novel method for efficiently personalizing generative models using optimal experimental design to select preference...

arXiv - Machine Learning · 3 min ·
Previous Page 121 Next

Related Topics

Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Subscribe to Newsletter

Daily or weekly digest • Unsubscribe anytime