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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 ·
Ai Infrastructure

Most people are using AI wrong—and it’s capping what they can do

1 is a fluke. 2 is a coincidence. 3 is a pattern. Lately I’ve been noticing something. The problems I’m solving are getting more complex…...

Reddit - Artificial Intelligence · 1 min ·
Ai Infrastructure

Most people are using AI wrong—and it’s capping what they can do

1 is a fluke. 2 is a coincidence. 3 is a pattern. Lately I’ve been noticing something. The problems I’m solving are getting more complex…...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2602.21116] Attention-Based SINR Estimation in User-Centric Non-Terrestrial Networks
Machine Learning

[2602.21116] Attention-Based SINR Estimation in User-Centric Non-Terrestrial Networks

This paper presents a novel low-complexity framework for estimating the signal-to-interference-plus-noise ratio (SINR) in user-centric no...

arXiv - AI · 4 min ·
[2602.21054] VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation
Llms

[2602.21054] VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation

The paper introduces VAUQ, a framework for vision-aware uncertainty quantification in large vision-language models (LVLMs), enhancing sel...

arXiv - AI · 3 min ·
[2602.20980] CrystaL: Spontaneous Emergence of Visual Latents in MLLMs
Llms

[2602.20980] CrystaL: Spontaneous Emergence of Visual Latents in MLLMs

The paper presents CrystaL, a novel framework for Multimodal Large Language Models (MLLMs) that enhances visual understanding by crystall...

arXiv - AI · 3 min ·
[2602.20979] Toward an Agentic Infused Software Ecosystem
Nlp

[2602.20979] Toward an Agentic Infused Software Ecosystem

This article discusses the concept of an Agentic Infused Software Ecosystem (AISE), emphasizing the need for a holistic approach to integ...

arXiv - AI · 3 min ·
[2602.20924] Airavat: An Agentic Framework for Internet Measurement
Computer Vision

[2602.20924] Airavat: An Agentic Framework for Internet Measurement

Airavat introduces an innovative framework for automating Internet measurement workflows, ensuring both generation and verification again...

arXiv - AI · 3 min ·
[2602.20751] SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing
Machine Learning

[2602.20751] SibylSense: Adaptive Rubric Learning via Memory Tuning and Adversarial Probing

The paper presents SibylSense, a novel approach to adaptive rubric learning that enhances reward mechanisms in reinforcement learning thr...

arXiv - Machine Learning · 3 min ·
[2602.20677] UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
Llms

[2602.20677] UrbanFM: Scaling Urban Spatio-Temporal Foundation Models

The paper presents UrbanFM, a novel framework for scaling urban spatio-temporal foundation models, addressing challenges in generalizabil...

arXiv - Machine Learning · 4 min ·
[2602.20676] PRECTR-V2:Unified Relevance-CTR Framework with Cross-User Preference Mining, Exposure Bias Correction, and LLM-Distilled Encoder Optimization
Llms

[2602.20676] PRECTR-V2:Unified Relevance-CTR Framework with Cross-User Preference Mining, Exposure Bias Correction, and LLM-Distilled Encoder Optimization

The paper presents PRECTR-V2, an advanced framework for improving search relevance and click-through rate (CTR) prediction by addressing ...

arXiv - AI · 4 min ·
[2602.20684] Agile V: A Compliance-Ready Framework for AI-Augmented Engineering -- From Concept to Audit-Ready Delivery
Machine Learning

[2602.20684] Agile V: A Compliance-Ready Framework for AI-Augmented Engineering -- From Concept to Audit-Ready Delivery

The paper presents Agile V, a framework integrating AI in engineering workflows to ensure compliance and verification at machine-speed de...

arXiv - AI · 4 min ·
[2602.20650] Dataset Color Quantization: A Training-Oriented Framework for Dataset-Level Compression
Machine Learning

[2602.20650] Dataset Color Quantization: A Training-Oriented Framework for Dataset-Level Compression

The paper presents Dataset Color Quantization (DCQ), a framework designed to compress large-scale image datasets by reducing color-space ...

arXiv - AI · 3 min ·
[2602.20595] OptiLeak: Efficient Prompt Reconstruction via Reinforcement Learning in Multi-tenant LLM Services
Llms

[2602.20595] OptiLeak: Efficient Prompt Reconstruction via Reinforcement Learning in Multi-tenant LLM Services

The paper presents OptiLeak, a framework utilizing reinforcement learning to enhance prompt reconstruction efficiency in multi-tenant LLM...

arXiv - AI · 4 min ·
[2602.20497] LESA: Learnable Stage-Aware Predictors for Diffusion Model Acceleration
Machine Learning

[2602.20497] LESA: Learnable Stage-Aware Predictors for Diffusion Model Acceleration

The paper introduces LESA, a framework for accelerating diffusion models using learnable stage-aware predictors, achieving significant sp...

arXiv - AI · 4 min ·
[2602.20467] Elimination-compensation pruning for fully-connected neural networks
Machine Learning

[2602.20467] Elimination-compensation pruning for fully-connected neural networks

This paper introduces a novel pruning method for fully-connected neural networks, which compensates for the removal of weights by adjusti...

arXiv - Machine Learning · 4 min ·
[2602.20449] Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference
Llms

[2602.20449] Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference

This article explores the differences between protein language models (PLMs) and natural language models, highlighting how these distinct...

arXiv - Machine Learning · 4 min ·
[2602.20442] Imputation of Unknown Missingness in Sparse Electronic Health Records
Machine Learning

[2602.20442] Imputation of Unknown Missingness in Sparse Electronic Health Records

The paper presents a novel algorithm for imputing unknown missing values in sparse electronic health records (EHRs) using a transformer-b...

arXiv - Machine Learning · 4 min ·
[2602.20400] Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation
Llms

[2602.20400] Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation

This article discusses three significant challenges and two potential solutions for improving the safety of unsupervised elicitation in l...

arXiv - Machine Learning · 4 min ·
[2602.20361] Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
Machine Learning

[2602.20361] Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS

This paper presents a continual learning framework for neural OFDM receivers that allows for real-time adaptation to changing communicati...

arXiv - Machine Learning · 3 min ·
[2602.20332] No One Size Fits All: QueryBandits for Hallucination Mitigation
Llms

[2602.20332] No One Size Fits All: QueryBandits for Hallucination Mitigation

The paper introduces QueryBandits, a model-agnostic framework designed to mitigate hallucinations in large language models (LLMs) by opti...

arXiv - Machine Learning · 4 min ·
[2602.20292] Quantifying the Expectation-Realisation Gap for Agentic AI Systems
Ai Infrastructure

[2602.20292] Quantifying the Expectation-Realisation Gap for Agentic AI Systems

This article examines the expectation-realisation gap in agentic AI systems, revealing discrepancies between anticipated productivity gai...

arXiv - AI · 3 min ·
[2602.20271] Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning
Machine Learning

[2602.20271] Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning

This paper presents a multi-task deep learning model for predicting delivery delay durations in logistics, addressing challenges posed by...

arXiv - Machine Learning · 4 min ·
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Related Topics

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

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