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WHO/Europe launches Technical Advisory Group on Artificial Intelligence for Health
Ai Startups

WHO/Europe launches Technical Advisory Group on Artificial Intelligence for Health

WHO/Europe has established the Technical Advisory Group on Artificial Intelligence for Health to ensure the ethical use of AI in health a...

AI News - General · 3 min ·
[2603.10202] Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Approach with Jump-Diffusion
Machine Learning

[2603.10202] Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Approach with Jump-Diffusion

Abstract page for arXiv paper 2603.10202: Hybrid Hidden Markov Model for Modeling Equity Excess Growth Rate Dynamics: A Discrete-State Ap...

arXiv - Machine Learning · 4 min ·
[2511.09204] Resource-Efficient Variational Quantum Classifier
Ai Startups

[2511.09204] Resource-Efficient Variational Quantum Classifier

Abstract page for arXiv paper 2511.09204: Resource-Efficient Variational Quantum Classifier

arXiv - Machine Learning · 3 min ·

All Content

[2602.19619] Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
Llms

[2602.19619] Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models

This article evaluates the accuracy of discrete diffusion language models (dLLMs) through a sampler-centric framework, revealing signific...

arXiv - Machine Learning · 3 min ·
[2602.19591] Detecting High-Potential SMEs with Heterogeneous Graph Neural Networks
Machine Learning

[2602.19591] Detecting High-Potential SMEs with Heterogeneous Graph Neural Networks

This article presents SME-HGT, a Heterogeneous Graph Transformer framework designed to identify high-potential small and medium enterpris...

arXiv - Machine Learning · 3 min ·
[2602.18583] Luna-2: Scalable Single-Token Evaluation with Small Language Models
Llms

[2602.18583] Luna-2: Scalable Single-Token Evaluation with Small Language Models

Luna-2 introduces a scalable architecture for single-token evaluation using small language models, enhancing accuracy and reducing costs ...

arXiv - Machine Learning · 4 min ·
[2602.19531] A Statistical Approach for Modeling Irregular Multivariate Time Series with Missing Observations
Machine Learning

[2602.19531] A Statistical Approach for Modeling Irregular Multivariate Time Series with Missing Observations

This paper presents a novel statistical method for modeling irregular multivariate time series with missing data, demonstrating superior ...

arXiv - AI · 4 min ·
[2602.18548] 1D-Bench: A Benchmark for Iterative UI Code Generation with Visual Feedback in Real-World
Data Science

[2602.18548] 1D-Bench: A Benchmark for Iterative UI Code Generation with Visual Feedback in Real-World

The paper introduces 1D-Bench, a benchmark for evaluating iterative UI code generation with visual feedback, aimed at improving design-to...

arXiv - AI · 4 min ·
[2602.18532] VLANeXt: Recipes for Building Strong VLA Models
Llms

[2602.18532] VLANeXt: Recipes for Building Strong VLA Models

The paper presents VLANeXt, a framework for building effective Vision-Language-Action (VLA) models, addressing inconsistencies in trainin...

arXiv - AI · 4 min ·
[2602.19455] SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning
Llms

[2602.19455] SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning

The paper introduces SenTSR-Bench, a framework that enhances time-series reasoning by integrating insights from specialized time-series l...

arXiv - AI · 4 min ·
[2602.18483] Red Teaming LLMs as Socio-Technical Practice: From Exploration and Data Creation to Evaluation
Llms

[2602.18483] Red Teaming LLMs as Socio-Technical Practice: From Exploration and Data Creation to Evaluation

The article examines red teaming as a socio-technical practice in evaluating large language models (LLMs), highlighting the importance of...

arXiv - AI · 4 min ·
[2602.18481] AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models
Llms

[2602.18481] AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models

The paper introduces AlphaForgeBench, a framework for evaluating trading strategies using Large Language Models (LLMs), addressing issues...

arXiv - AI · 4 min ·
[2602.19237] Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data
Llms

[2602.19237] Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data

This article evaluates SAP's RPT-1 model for enterprise business process prediction, comparing its performance against traditional machin...

arXiv - AI · 4 min ·
[2602.18458] The Story is Not the Science: Execution-Grounded Evaluation of Mechanistic Interpretability Research
Robotics

[2602.18458] The Story is Not the Science: Execution-Grounded Evaluation of Mechanistic Interpretability Research

The article presents a novel evaluation framework for mechanistic interpretability research, utilizing AI agents to enhance research rigo...

arXiv - Machine Learning · 3 min ·
[2602.18443] From "Help" to Helpful: A Hierarchical Assessment of LLMs in Mental e-Health Applications
Llms

[2602.18443] From "Help" to Helpful: A Hierarchical Assessment of LLMs in Mental e-Health Applications

This study evaluates the effectiveness of large language models (LLMs) in generating subject lines for mental health counseling emails, h...

arXiv - AI · 3 min ·
[2602.19068] TimeRadar: A Domain-Rotatable Foundation Model for Time Series Anomaly Detection
Llms

[2602.19068] TimeRadar: A Domain-Rotatable Foundation Model for Time Series Anomaly Detection

TimeRadar introduces a novel approach to time series anomaly detection using a domain-rotatable foundation model that enhances the differ...

arXiv - Machine Learning · 4 min ·
[2602.19367] Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces
Machine Learning

[2602.19367] Time Series, Vision, and Language: Exploring the Limits of Alignment in Contrastive Representation Spaces

This paper investigates the alignment of representations from time series, vision, and language modalities, revealing insights into their...

arXiv - AI · 4 min ·
[2602.18645] Adaptive Time Series Reasoning via Segment Selection
Machine Learning

[2602.18645] Adaptive Time Series Reasoning via Segment Selection

The paper presents ARTIST, a novel approach to time series reasoning that utilizes adaptive segment selection to improve accuracy in answ...

arXiv - Machine Learning · 4 min ·
[2602.19006] Evaluating Large Language Models on Quantum Mechanics: A Comparative Study Across Diverse Models and Tasks
Llms

[2602.19006] Evaluating Large Language Models on Quantum Mechanics: A Comparative Study Across Diverse Models and Tasks

This article evaluates 15 large language models on quantum mechanics problem-solving across diverse tasks, revealing performance stratifi...

arXiv - AI · 4 min ·
[2602.18613] Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools
Llms

[2602.18613] Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools

This paper presents a diagnostic method for evaluating LLM reranker behavior using fixed evidence pools, isolating ranking policies from ...

arXiv - Machine Learning · 3 min ·
[2602.18600] MapTab: Can MLLMs Master Constrained Route Planning?
Llms

[2602.18600] MapTab: Can MLLMs Master Constrained Route Planning?

The paper introduces MapTab, a benchmark for evaluating Multimodal Large Language Models (MLLMs) on constrained route planning tasks, hig...

arXiv - Machine Learning · 3 min ·
[2602.18581] Learning Beyond Optimization: Stress-Gated Dynamical Regime Regulation in Autonomous Systems
Machine Learning

[2602.18581] Learning Beyond Optimization: Stress-Gated Dynamical Regime Regulation in Autonomous Systems

The paper explores a novel framework for autonomous systems that enables learning without explicit objectives, focusing on self-regulatio...

arXiv - Machine Learning · 4 min ·
[2602.18521] AdaptStress: Online Adaptive Learning for Interpretable and Personalized Stress Prediction Using Multivariate and Sparse Physiological Signals
Machine Learning

[2602.18521] AdaptStress: Online Adaptive Learning for Interpretable and Personalized Stress Prediction Using Multivariate and Sparse Physiological Signals

The paper presents AdaptStress, a novel model for predicting stress levels using physiological data from wearables, achieving superior ac...

arXiv - AI · 4 min ·
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