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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 ·
Google quietly launched an AI dictation app that works offline
Machine Learning

Google quietly launched an AI dictation app that works offline

Google's new offline-first dictation app uses Gemma AI models to take on the apps like Wispr Flow.

TechCrunch - AI · 4 min ·
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 ·

All Content

[2602.16876] ML-driven detection and reduction of ballast information in multi-modal datasets
Machine Learning

[2602.16876] ML-driven detection and reduction of ballast information in multi-modal datasets

This paper presents a framework for detecting and reducing ballast information in multi-modal datasets, enhancing machine learning effici...

arXiv - Machine Learning · 3 min ·
[2602.16842] What is the Value of Censored Data? An Exact Analysis for the Data-driven Newsvendor
Data Science

[2602.16842] What is the Value of Censored Data? An Exact Analysis for the Data-driven Newsvendor

This paper analyzes the impact of censored demand data on inventory management, presenting a method to compute worst-case regret for data...

arXiv - Machine Learning · 4 min ·
[2602.16821] TopoFlow: Physics-guided Neural Networks for high-resolution air quality prediction
Machine Learning

[2602.16821] TopoFlow: Physics-guided Neural Networks for high-resolution air quality prediction

TopoFlow introduces a physics-guided neural network for high-resolution air quality prediction, significantly improving accuracy over exi...

arXiv - Machine Learning · 4 min ·
[2602.16796] Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
Machine Learning

[2602.16796] Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning

This article presents Tail-aware Flow Fine-Tuning (TFFT), a novel algorithm that optimizes generative models by controlling tail behavior...

arXiv - Machine Learning · 4 min ·
[2602.16793] Escaping the Cognitive Well: Efficient Competition Math with Off-the-Shelf Models
Machine Learning

[2602.16793] Escaping the Cognitive Well: Efficient Competition Math with Off-the-Shelf Models

The paper presents a novel inference pipeline that leverages off-the-shelf models to solve International Mathematical Olympiad problems e...

arXiv - Machine Learning · 4 min ·
[2602.16764] Machine Learning Argument of Latitude Error Model for LEO Satellite Orbit and Covariance Correction
Machine Learning

[2602.16764] Machine Learning Argument of Latitude Error Model for LEO Satellite Orbit and Covariance Correction

This article presents a machine learning model designed to correct latitude error in Low Earth Orbit (LEO) satellite propagation, enhanci...

arXiv - Machine Learning · 4 min ·
[2602.16730] MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior
Machine Learning

[2602.16730] MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior

The MMCAformer paper presents a novel transformer model that integrates macro and micro traffic data for improved traffic speed predictio...

arXiv - Machine Learning · 4 min ·
[2602.16735] A Few-Shot LLM Framework for Extreme Day Classification in Electricity Markets
Llms

[2602.16735] A Few-Shot LLM Framework for Extreme Day Classification in Electricity Markets

This paper presents a few-shot classification framework utilizing Large Language Models (LLMs) to predict spikes in electricity prices, d...

arXiv - Machine Learning · 3 min ·
[2602.16739] Real-time Secondary Crash Likelihood Prediction Excluding Post Primary Crash Features
Machine Learning

[2602.16739] Real-time Secondary Crash Likelihood Prediction Excluding Post Primary Crash Features

This article presents a novel framework for predicting secondary crash likelihood in real-time, focusing on traffic conditions without re...

arXiv - Machine Learning · 4 min ·
[2602.10117] Biases in the Blind Spot: Detecting What LLMs Fail to Mention
Llms

[2602.10117] Biases in the Blind Spot: Detecting What LLMs Fail to Mention

The paper discusses a novel automated pipeline for detecting unverbalized biases in Large Language Models (LLMs), highlighting its effect...

arXiv - Machine Learning · 4 min ·
[2602.09437] Diffusion-Guided Pretraining for Brain Graph Foundation Models
Llms

[2602.09437] Diffusion-Guided Pretraining for Brain Graph Foundation Models

The paper presents a diffusion-guided pretraining framework for brain graph models, addressing limitations in existing methods for learni...

arXiv - AI · 4 min ·
[2601.22454] Temporal Graph Pattern Machine
Machine Learning

[2601.22454] Temporal Graph Pattern Machine

The Temporal Graph Pattern Machine (TGPM) proposes a novel framework for temporal graph learning, focusing on generalized evolving patter...

arXiv - AI · 4 min ·
[2601.06932] Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching
Nlp

[2601.06932] Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching

The paper presents Symphonym, a neural embedding system designed for cross-script name matching, mapping names into a unified phonetic sp...

arXiv - AI · 4 min ·
[2601.01224] Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment
Machine Learning

[2601.01224] Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment

This paper presents Contrastive Object-centric Diffusion Alignment (CODA), an enhancement to object-centric learning that reduces slot en...

arXiv - AI · 4 min ·
[2512.07984] Restrictive Hierarchical Semantic Segmentation for Stratified Tooth Layer Detection
Machine Learning

[2512.07984] Restrictive Hierarchical Semantic Segmentation for Stratified Tooth Layer Detection

This article presents a novel framework for hierarchical semantic segmentation aimed at improving the detection of stratified tooth layer...

arXiv - AI · 4 min ·
[2512.05556] Beyond Linear Surrogates: High-Fidelity Local Explanations for Black-Box Models
Machine Learning

[2512.05556] Beyond Linear Surrogates: High-Fidelity Local Explanations for Black-Box Models

The paper presents a novel method for generating high-fidelity local explanations for black-box machine learning models using multivariat...

arXiv - Machine Learning · 4 min ·
[2511.14654] Improving segmentation of retinal arteries and veins using cardiac signal in doppler holograms
Computer Vision

[2511.14654] Improving segmentation of retinal arteries and veins using cardiac signal in doppler holograms

This article presents a novel approach to segmenting retinal arteries and veins using cardiac signals in Doppler holograms, enhancing tra...

arXiv - AI · 3 min ·
[2510.25015] VeriStruct: AI-assisted Automated Verification of Data-Structure Modules in Verus
Llms

[2510.25015] VeriStruct: AI-assisted Automated Verification of Data-Structure Modules in Verus

VeriStruct is a novel framework for AI-assisted automated verification of complex data structure modules in Verus, achieving a high succe...

arXiv - AI · 3 min ·
[2509.19877] Advancing Universal Deep Learning for Electronic-Structure Hamiltonian Prediction of Materials
Machine Learning

[2509.19877] Advancing Universal Deep Learning for Electronic-Structure Hamiltonian Prediction of Materials

This article presents advancements in deep learning techniques for predicting electronic-structure Hamiltonians in materials, addressing ...

arXiv - Machine Learning · 4 min ·
[2506.20555] DeepQuark: A Deep-Neural-Network Approach to Multiquark Bound States
Machine Learning

[2506.20555] DeepQuark: A Deep-Neural-Network Approach to Multiquark Bound States

The paper presents DeepQuark, a novel deep-neural-network approach for analyzing multiquark bound states, demonstrating superior performa...

arXiv - AI · 4 min ·
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