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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 ·
Machine Learning

[D] Budget Machine Learning Hardware

Looking to get into machine learning and found this video on a piece of hardware for less than £500. Is it really possible to teach auton...

Reddit - Machine Learning · 1 min ·
Machine Learning

Your prompts aren’t the problem — something else is

I keep seeing people focus heavily on prompt optimization. But in practice, a lot of failures I’ve observed don’t come from the prompt it...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2603.23722] Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL
Machine Learning

[2603.23722] Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL

Abstract page for arXiv paper 2603.23722: Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL

arXiv - Machine Learning · 4 min ·
[2603.23736] Wasserstein Parallel Transport for Predicting the Dynamics of Statistical Systems
Machine Learning

[2603.23736] Wasserstein Parallel Transport for Predicting the Dynamics of Statistical Systems

Abstract page for arXiv paper 2603.23736: Wasserstein Parallel Transport for Predicting the Dynamics of Statistical Systems

arXiv - Machine Learning · 4 min ·
[2603.23685] The Economics of Builder Saturation in Digital Markets
Machine Learning

[2603.23685] The Economics of Builder Saturation in Digital Markets

Abstract page for arXiv paper 2603.23685: The Economics of Builder Saturation in Digital Markets

arXiv - Machine Learning · 4 min ·
[2603.23668] Energy Efficient Software Hardware CoDesign for Machine Learning: From TinyML to Large Language Models
Llms

[2603.23668] Energy Efficient Software Hardware CoDesign for Machine Learning: From TinyML to Large Language Models

Abstract page for arXiv paper 2603.23668: Energy Efficient Software Hardware CoDesign for Machine Learning: From TinyML to Large Language...

arXiv - Machine Learning · 3 min ·
[2603.23640] LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustained Load
Llms

[2603.23640] LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustained Load

Abstract page for arXiv paper 2603.23640: LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustain...

arXiv - Machine Learning · 4 min ·
[2603.23611] LLMORPH: Automated Metamorphic Testing of Large Language Models
Llms

[2603.23611] LLMORPH: Automated Metamorphic Testing of Large Language Models

Abstract page for arXiv paper 2603.23611: LLMORPH: Automated Metamorphic Testing of Large Language Models

arXiv - Machine Learning · 4 min ·
[2603.23576] Wafer-Level Etch Spatial Profiling for Process Monitoring from Time-Series with Time-LLM
Llms

[2603.23576] Wafer-Level Etch Spatial Profiling for Process Monitoring from Time-Series with Time-LLM

Abstract page for arXiv paper 2603.23576: Wafer-Level Etch Spatial Profiling for Process Monitoring from Time-Series with Time-LLM

arXiv - Machine Learning · 3 min ·
[2603.23547] PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA
Machine Learning

[2603.23547] PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA

Abstract page for arXiv paper 2603.23547: PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors ...

arXiv - Machine Learning · 4 min ·
[2603.23544] DeepOFW: Deep Learning-Driven OFDM-Flexible Waveform Modulation for Peak-to-Average Power Ratio Reduction
Machine Learning

[2603.23544] DeepOFW: Deep Learning-Driven OFDM-Flexible Waveform Modulation for Peak-to-Average Power Ratio Reduction

Abstract page for arXiv paper 2603.23544: DeepOFW: Deep Learning-Driven OFDM-Flexible Waveform Modulation for Peak-to-Average Power Ratio...

arXiv - Machine Learning · 4 min ·
[2603.23539] PLDR-LLMs Reason At Self-Organized Criticality
Llms

[2603.23539] PLDR-LLMs Reason At Self-Organized Criticality

Abstract page for arXiv paper 2603.23539: PLDR-LLMs Reason At Self-Organized Criticality

arXiv - Machine Learning · 3 min ·
[2603.23534] Not All Pretraining are Created Equal: Threshold Tuning and Class Weighting for Imbalanced Polarization Tasks in Low-Resource Settings
Machine Learning

[2603.23534] Not All Pretraining are Created Equal: Threshold Tuning and Class Weighting for Imbalanced Polarization Tasks in Low-Resource Settings

Abstract page for arXiv paper 2603.23534: Not All Pretraining are Created Equal: Threshold Tuning and Class Weighting for Imbalanced Pola...

arXiv - Machine Learning · 3 min ·
[2603.23530] Did You Forget What I Asked? Prospective Memory Failures in Large Language Models
Llms

[2603.23530] Did You Forget What I Asked? Prospective Memory Failures in Large Language Models

Abstract page for arXiv paper 2603.23530: Did You Forget What I Asked? Prospective Memory Failures in Large Language Models

arXiv - Machine Learning · 3 min ·
[2603.23514] DepthCharge: A Domain-Agnostic Framework for Measuring Depth-Dependent Knowledge in Large Language Models
Llms

[2603.23514] DepthCharge: A Domain-Agnostic Framework for Measuring Depth-Dependent Knowledge in Large Language Models

Abstract page for arXiv paper 2603.23514: DepthCharge: A Domain-Agnostic Framework for Measuring Depth-Dependent Knowledge in Large Langu...

arXiv - Machine Learning · 4 min ·
[2603.23507] Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes
Llms

[2603.23507] Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes

Abstract page for arXiv paper 2603.23507: Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes

arXiv - Machine Learning · 4 min ·
[2603.24594] Polynomial Speedup in Diffusion Models with the Multilevel Euler-Maruyama Method
Machine Learning

[2603.24594] Polynomial Speedup in Diffusion Models with the Multilevel Euler-Maruyama Method

Abstract page for arXiv paper 2603.24594: Polynomial Speedup in Diffusion Models with the Multilevel Euler-Maruyama Method

arXiv - Machine Learning · 4 min ·
[2603.24587] DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving
Machine Learning

[2603.24587] DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving

Abstract page for arXiv paper 2603.24587: DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving

arXiv - Machine Learning · 3 min ·
[2603.24562] Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction
Llms

[2603.24562] Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction

Abstract page for arXiv paper 2603.24562: Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction

arXiv - Machine Learning · 4 min ·
[2603.24533] UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience
Llms

[2603.24533] UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience

Abstract page for arXiv paper 2603.24533: UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience

arXiv - Machine Learning · 4 min ·
[2603.24524] No Single Metric Tells the Whole Story: A Multi-Dimensional Evaluation Framework for Uncertainty Attributions
Machine Learning

[2603.24524] No Single Metric Tells the Whole Story: A Multi-Dimensional Evaluation Framework for Uncertainty Attributions

Abstract page for arXiv paper 2603.24524: No Single Metric Tells the Whole Story: A Multi-Dimensional Evaluation Framework for Uncertaint...

arXiv - Machine Learning · 4 min ·
[2603.24518] TuneShift-KD: Knowledge Distillation and Transfer for Fine-tuned Models
Llms

[2603.24518] TuneShift-KD: Knowledge Distillation and Transfer for Fine-tuned Models

Abstract page for arXiv paper 2603.24518: TuneShift-KD: Knowledge Distillation and Transfer for Fine-tuned Models

arXiv - Machine Learning · 4 min ·
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