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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

ML/AI Engineer laid off from big tech, need your help!

I recently left a very toxic company that was taking a serious toll on my mental and physical health. I gave everything I had and it cost...

Reddit - ML Jobs · 1 min ·
Machine Learning

Trials and tribulations fine-tuning & deploying Gemma-4 [P]

Hey all, Our ML team spent some time this week getting training and deployments working for Gemma-4, and wanted to document all the thing...

Reddit - Machine Learning · 1 min ·

All Content

[2602.12866] Model-Aware Rate-Distortion Limits for Task-Oriented Source Coding
Machine Learning

[2602.12866] Model-Aware Rate-Distortion Limits for Task-Oriented Source Coding

This paper explores Model-Aware Rate-Distortion Limits for Task-Oriented Source Coding, focusing on optimizing bitrate, latency, and task...

arXiv - Machine Learning · 3 min ·
[2602.12684] Xiaomi-Robotics-0: An Open-Sourced Vision-Language-Action Model with Real-Time Execution
Machine Learning

[2602.12684] Xiaomi-Robotics-0: An Open-Sourced Vision-Language-Action Model with Real-Time Execution

Xiaomi-Robotics-0 is an advanced open-sourced vision-language-action model designed for real-time execution, showcasing state-of-the-art ...

arXiv - Machine Learning · 4 min ·
[2602.12510] Visual RAG Toolkit: Scaling Multi-Vector Visual Retrieval with Training-Free Pooling and Multi-Stage Search
Machine Learning

[2602.12510] Visual RAG Toolkit: Scaling Multi-Vector Visual Retrieval with Training-Free Pooling and Multi-Stage Search

The Visual RAG Toolkit enhances multi-vector visual retrieval by introducing a training-free pooling method and a multi-stage search proc...

arXiv - Machine Learning · 4 min ·
[2602.12681] Fool Me If You Can: On the Robustness of Binary Code Similarity Detection Models against Semantics-preserving Transformations
Machine Learning

[2602.12681] Fool Me If You Can: On the Robustness of Binary Code Similarity Detection Models against Semantics-preserving Transformations

This paper evaluates the robustness of binary code similarity detection models against semantics-preserving transformations, introducing ...

arXiv - Machine Learning · 4 min ·
[2602.12487] Gradient-Enhanced Partitioned Gaussian Processes for Real-Time Quadrotor Dynamics Modeling
Machine Learning

[2602.12487] Gradient-Enhanced Partitioned Gaussian Processes for Real-Time Quadrotor Dynamics Modeling

This paper introduces a novel Gaussian Process model for quadrotor dynamics that integrates gradient information, enabling real-time infe...

arXiv - Machine Learning · 4 min ·
[2602.12478] Task- and Metric-Specific Signal Quality Indices for Medical Time Series
Ai Infrastructure

[2602.12478] Task- and Metric-Specific Signal Quality Indices for Medical Time Series

The paper introduces a new perturbation-based signal quality index (pSQI) for medical time series, addressing the limitations of existing...

arXiv - Machine Learning · 4 min ·
[2602.12426] Interference-Robust Non-Coherent Over-the-Air Computation for Decentralized Optimization
Nlp

[2602.12426] Interference-Robust Non-Coherent Over-the-Air Computation for Decentralized Optimization

This paper presents an interference-robust non-coherent over-the-air computation (IR-NCOTA) method for decentralized optimization, enhanc...

arXiv - Machine Learning · 3 min ·
[2602.12418] Sparse Autoencoders are Capable LLM Jailbreak Mitigators
Llms

[2602.12418] Sparse Autoencoders are Capable LLM Jailbreak Mitigators

The paper presents Context-Conditioned Delta Steering (CC-Delta), a defense mechanism using Sparse Autoencoders (SAEs) to mitigate jailbr...

arXiv - Machine Learning · 3 min ·
[2602.12289] String-Level Ground Fault Localization for TN-Earthed Three-Phase Photovoltaic Systems
Machine Learning

[2602.12289] String-Level Ground Fault Localization for TN-Earthed Three-Phase Photovoltaic Systems

This article presents a novel edge-AI approach for localizing ground faults in TN-earthed three-phase photovoltaic systems, enhancing eff...

arXiv - Machine Learning · 3 min ·
[2602.13151] Quantization-Robust LLM Unlearning via Low-Rank Adaptation
Llms

[2602.13151] Quantization-Robust LLM Unlearning via Low-Rank Adaptation

The paper presents a method for unlearning knowledge in large language models (LLMs) while maintaining performance after quantization, us...

arXiv - Machine Learning · 4 min ·
[2602.13140] FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics
Machine Learning

[2602.13140] FlashSchNet: Fast and Accurate Coarse-Grained Neural Network Molecular Dynamics

FlashSchNet presents a novel framework for molecular dynamics simulations, enhancing speed and accuracy through innovative techniques in ...

arXiv - Machine Learning · 4 min ·
[2602.13128] Eventizing Traditionally Opaque Binary Neural Networks as 1-safe Petri net Models
Machine Learning

[2602.13128] Eventizing Traditionally Opaque Binary Neural Networks as 1-safe Petri net Models

This article presents a framework for enhancing the transparency of Binary Neural Networks (BNNs) by modeling their operations as event-d...

arXiv - Machine Learning · 4 min ·
[2602.13073] LCSB: Layer-Cyclic Selective Backpropagation for Memory-Efficient On-Device LLM Fine-Tuning
Llms

[2602.13073] LCSB: Layer-Cyclic Selective Backpropagation for Memory-Efficient On-Device LLM Fine-Tuning

The paper presents Layer-Cyclic Selective Backpropagation (LCSB), a method for memory-efficient fine-tuning of large language models (LLM...

arXiv - Machine Learning · 3 min ·
[2602.13062] Backdoor Attacks on Contrastive Continual Learning for IoT Systems
Machine Learning

[2602.13062] Backdoor Attacks on Contrastive Continual Learning for IoT Systems

This paper analyzes backdoor attacks on contrastive continual learning (CCL) in IoT systems, highlighting vulnerabilities and proposing d...

arXiv - Machine Learning · 4 min ·
[2602.13069] Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning
Llms

[2602.13069] Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning

The paper presents Memory-Efficient Structured Backpropagation (MeSP), a novel approach for on-device fine-tuning of large language model...

arXiv - Machine Learning · 3 min ·
[2602.13052] Quantization-Aware Collaborative Inference for Large Embodied AI Models
Machine Learning

[2602.13052] Quantization-Aware Collaborative Inference for Large Embodied AI Models

This paper explores quantization-aware collaborative inference for large embodied AI models, addressing challenges in resource-limited en...

arXiv - Machine Learning · 3 min ·
[2602.13030] Resource-Efficient Gesture Recognition through Convexified Attention
Machine Learning

[2602.13030] Resource-Efficient Gesture Recognition through Convexified Attention

This paper presents a novel convexified attention mechanism for resource-efficient gesture recognition in wearable e-textile interfaces, ...

arXiv - Machine Learning · 4 min ·
[2602.12744] Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification
Machine Learning

[2602.12744] Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification

This article presents Dynamic Structured Pruning (DSP), an innovative method for optimizing convolutional neural networks in time series ...

arXiv - Machine Learning · 4 min ·
[2602.12756] Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs
Llms

[2602.12756] Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs

This paper introduces F-LLM, a control-theoretic framework for stable time series forecasting using large language models, addressing iss...

arXiv - Machine Learning · 4 min ·
[2602.12622] Efficient Personalized Federated PCA with Manifold Optimization for IoT Anomaly Detection
Ai Infrastructure

[2602.12622] Efficient Personalized Federated PCA with Manifold Optimization for IoT Anomaly Detection

This article presents a novel method for anomaly detection in IoT networks using Efficient Personalized Federated PCA, addressing the cha...

arXiv - Machine Learning · 3 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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