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Top 10 AI certifications and courses for 2026
Ai Startups

Top 10 AI certifications and courses for 2026

This article reviews the top 10 AI certifications and courses for 2026, highlighting their significance in a rapidly evolving field and t...

AI Events · 15 min ·
[2603.18109] Discovery of Bimodal Drift Rate Structure in FRB 20240114A: Evidence for Dual Emission Regions
Machine Learning

[2603.18109] Discovery of Bimodal Drift Rate Structure in FRB 20240114A: Evidence for Dual Emission Regions

Abstract page for arXiv paper 2603.18109: Discovery of Bimodal Drift Rate Structure in FRB 20240114A: Evidence for Dual Emission Regions

arXiv - AI · 4 min ·
[2509.22367] What Is The Political Content in LLMs' Pre- and Post-Training Data?
Llms

[2509.22367] What Is The Political Content in LLMs' Pre- and Post-Training Data?

Abstract page for arXiv paper 2509.22367: What Is The Political Content in LLMs' Pre- and Post-Training Data?

arXiv - AI · 4 min ·

All Content

[2502.05114] SpecTUS: Spectral Translator for Unknown Structures annotation from EI-MS spectra
Machine Learning

[2502.05114] SpecTUS: Spectral Translator for Unknown Structures annotation from EI-MS spectra

The article presents SpecTUS, a deep neural model designed for the structural annotation of small molecules from low-resolution gas chrom...

arXiv - Machine Learning · 4 min ·
[2412.13897] Data-Efficient Inference of Neural Fluid Fields via SciML Foundation Model
Llms

[2412.13897] Data-Efficient Inference of Neural Fluid Fields via SciML Foundation Model

This article presents a novel approach to data-efficient inference of neural fluid fields using SciML foundation models, demonstrating si...

arXiv - Machine Learning · 4 min ·
[2402.08621] A Unified Framework for Analyzing Meta-algorithms in Online Convex Optimization
Machine Learning

[2402.08621] A Unified Framework for Analyzing Meta-algorithms in Online Convex Optimization

This paper presents a unified framework for analyzing meta-algorithms in online convex optimization, addressing various feedback types an...

arXiv - Machine Learning · 4 min ·
[2602.18313] Clapeyron Neural Networks for Single-Species Vapor-Liquid Equilibria
Machine Learning

[2602.18313] Clapeyron Neural Networks for Single-Species Vapor-Liquid Equilibria

The paper presents a novel approach using thermodynamics-informed graph neural networks to predict vapor-liquid equilibrium properties, i...

arXiv - Machine Learning · 3 min ·
[2602.18213] Machine-learning force-field models for dynamical simulations of metallic magnets
Machine Learning

[2602.18213] Machine-learning force-field models for dynamical simulations of metallic magnets

This article reviews advancements in machine learning force-field models for simulating spin dynamics in metallic magnets, emphasizing sc...

arXiv - Machine Learning · 3 min ·
[2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players
Machine Learning

[2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players

The paper presents Robo-Saber, a motion generation system designed for playtesting virtual reality games, specifically focusing on genera...

arXiv - Machine Learning · 3 min ·
[2602.18186] Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
Ai Startups

[2602.18186] Box Thirding: Anytime Best Arm Identification under Insufficient Sampling

The paper introduces Box Thirding (B3), an innovative algorithm for Best Arm Identification (BAI) that operates efficiently under budget ...

arXiv - Machine Learning · 3 min ·
[2602.18151] Rethinking Beam Management: Generalization Limits Under Hardware Heterogeneity
Machine Learning

[2602.18151] Rethinking Beam Management: Generalization Limits Under Hardware Heterogeneity

This article discusses the challenges posed by hardware heterogeneity in beam-based communication systems for 5G and beyond, emphasizing ...

arXiv - Machine Learning · 3 min ·
[2602.18283] HyTRec: A Hybrid Temporal-Aware Attention Architecture for Long Behavior Sequential Recommendation
Machine Learning

[2602.18283] HyTRec: A Hybrid Temporal-Aware Attention Architecture for Long Behavior Sequential Recommendation

HyTRec introduces a Hybrid Temporal-Aware Attention architecture designed to enhance long behavior sequential recommendations, improving ...

arXiv - AI · 3 min ·
[2602.18083] Comparative Assessment of Multimodal Earth Observation Data for Soil Moisture Estimation
Machine Learning

[2602.18083] Comparative Assessment of Multimodal Earth Observation Data for Soil Moisture Estimation

This article presents a high-resolution framework for soil moisture estimation using multimodal Earth observation data, highlighting the ...

arXiv - Machine Learning · 4 min ·
[2602.18053] On the Generalization and Robustness in Conditional Value-at-Risk
Nlp

[2602.18053] On the Generalization and Robustness in Conditional Value-at-Risk

This paper explores the generalization and robustness of Conditional Value-at-Risk (CVaR) in the context of heavy-tailed data, providing ...

arXiv - Machine Learning · 4 min ·
[2602.18047] CityGuard: Graph-Aware Private Descriptors for Bias-Resilient Identity Search Across Urban Cameras
Machine Learning

[2602.18047] CityGuard: Graph-Aware Private Descriptors for Bias-Resilient Identity Search Across Urban Cameras

CityGuard introduces a novel framework for privacy-preserving identity retrieval across urban surveillance cameras, addressing challenges...

arXiv - Machine Learning · 4 min ·
[2602.18154] FENCE: A Financial and Multimodal Jailbreak Detection Dataset
Llms

[2602.18154] FENCE: A Financial and Multimodal Jailbreak Detection Dataset

The paper presents FENCE, a bilingual multimodal dataset designed for detecting jailbreaks in financial applications, highlighting vulner...

arXiv - AI · 3 min ·
[2602.17917] Interactions that reshape the interfaces of the interacting parties
Machine Learning

[2602.17917] Interactions that reshape the interfaces of the interacting parties

This paper introduces polynomial trees to model dynamic systems where interactions reshape interfaces, enhancing understanding of state-d...

arXiv - Machine Learning · 4 min ·
[2602.17894] Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget
Machine Learning

[2602.17894] Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget

This paper explores optimal data collection strategies from biased and costly sources, focusing on maximizing effective sample size under...

arXiv - Machine Learning · 4 min ·
[2602.18119] RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis
Machine Learning

[2602.18119] RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis

The paper presents RamanSeg, an interpretable deep learning model for analyzing Raman spectra in cancer diagnosis, achieving significant ...

arXiv - Machine Learning · 3 min ·
[2602.17876] Interactive Learning of Single-Index Models via Stochastic Gradient Descent
Machine Learning

[2602.17876] Interactive Learning of Single-Index Models via Stochastic Gradient Descent

This article discusses the application of Stochastic Gradient Descent (SGD) in learning single-index models, revealing its effectiveness ...

arXiv - Machine Learning · 3 min ·
[2602.17855] TopoGate: Quality-Aware Topology-Stabilized Gated Fusion for Longitudinal Low-Dose CT New-Lesion Prediction
Machine Learning

[2602.17855] TopoGate: Quality-Aware Topology-Stabilized Gated Fusion for Longitudinal Low-Dose CT New-Lesion Prediction

The paper presents TopoGate, a model designed to enhance new-lesion prediction in longitudinal low-dose CT scans by integrating quality-a...

arXiv - Machine Learning · 3 min ·
[2602.18094] OODBench: Out-of-Distribution Benchmark for Large Vision-Language Models
Llms

[2602.18094] OODBench: Out-of-Distribution Benchmark for Large Vision-Language Models

The paper introduces OODBench, a benchmark for evaluating large vision-language models' performance on out-of-distribution (OOD) data, hi...

arXiv - AI · 4 min ·
[2602.17830] Drift Estimation for Stochastic Differential Equations with Denoising Diffusion Models
Machine Learning

[2602.17830] Drift Estimation for Stochastic Differential Equations with Denoising Diffusion Models

This paper explores drift estimation in multivariate stochastic differential equations using denoising diffusion models, proposing a new ...

arXiv - Machine Learning · 3 min ·
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