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Ai Infrastructure

I built an AI content engine that turns one piece of content into posts for 9 platforms — fully automated with n8n

What it does: You give it any input — a blog URL, a YouTube video, raw text, or just a topic — and it generates optimized posts for 9 pla...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

mining hardware doing AI training - is the output actually useful

there's this network that launched recently routing crypto mining hardware toward AI training workloads. miners seem happy with the econo...

Reddit - Artificial Intelligence · 1 min ·
[2604.01989] Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation
Llms

[2604.01989] Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation

Abstract page for arXiv paper 2604.01989: Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation

arXiv - AI · 4 min ·

All Content

[2602.18690] Neural Fields as World Models
Machine Learning

[2602.18690] Neural Fields as World Models

The paper explores how neural fields can serve as world models, preserving sensory topology for better prediction of physical outcomes, w...

arXiv - Machine Learning · 3 min ·
[2602.18603] Enhancing Goal Inference via Correction Timing
Machine Learning

[2602.18603] Enhancing Goal Inference via Correction Timing

This article explores how the timing of human corrections can enhance robot learning by providing insights into task objectives and impro...

arXiv - Machine Learning · 4 min ·
[2602.18627] Federated Learning-Assisted Optimization of Mobile Transmission with Digital Twins
Machine Learning

[2602.18627] Federated Learning-Assisted Optimization of Mobile Transmission with Digital Twins

This paper presents a novel framework for optimizing mobile transmission using federated learning and digital twins, ensuring privacy whi...

arXiv - Machine Learning · 4 min ·
[2602.20102] BarrierSteer: LLM Safety via Learning Barrier Steering
Llms

[2602.20102] BarrierSteer: LLM Safety via Learning Barrier Steering

The article presents BarrierSteer, a framework designed to enhance the safety of large language models (LLMs) by embedding learned safety...

arXiv - AI · 3 min ·
[2602.18891] Orchestrating LLM Agents for Scientific Research: A Pilot Study of Multiple Choice Question (MCQ) Generation and Evaluation
Llms

[2602.18891] Orchestrating LLM Agents for Scientific Research: A Pilot Study of Multiple Choice Question (MCQ) Generation and Evaluation

This pilot study explores the orchestration of LLM agents in scientific research, focusing on the generation and evaluation of multiple-c...

arXiv - AI · 4 min ·
[2602.19982] A Computationally Efficient Multidimensional Vision Transformer
Machine Learning

[2602.19982] A Computationally Efficient Multidimensional Vision Transformer

This paper presents a novel tensor-based framework for Vision Transformers, enhancing computational efficiency while maintaining competit...

arXiv - Machine Learning · 3 min ·
[2602.19964] On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference
Machine Learning

[2602.19964] On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference

This paper establishes theoretical connections between Random Network Distillation (RND), Deep Ensembles, and Bayesian Inference, enhanci...

arXiv - Machine Learning · 4 min ·
[2602.18850] When the Inference Meets the Explicitness or Why Multimodality Can Make Us Forget About the Perfect Predictor
Machine Learning

[2602.18850] When the Inference Meets the Explicitness or Why Multimodality Can Make Us Forget About the Perfect Predictor

This paper explores the effectiveness of multimodal communication systems in human-robot collaboration, analyzing how explicit communicat...

arXiv - AI · 4 min ·
[2602.18846] DUET-VLM: Dual stage Unified Efficient Token reduction for VLM Training and Inference
Llms

[2602.18846] DUET-VLM: Dual stage Unified Efficient Token reduction for VLM Training and Inference

DUET-VLM introduces a dual-stage token reduction framework for vision-language models, enhancing efficiency without sacrificing accuracy ...

arXiv - AI · 4 min ·
[2602.19938] A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs
Llms

[2602.19938] A Replicate-and-Quantize Strategy for Plug-and-Play Load Balancing of Sparse Mixture-of-Experts LLMs

The paper presents a Replicate-and-Quantize strategy for improving load balancing in Sparse Mixture-of-Experts (SMoE) models, enhancing i...

arXiv - Machine Learning · 4 min ·
[2602.18844] When Agda met Vampire
Ai Infrastructure

[2602.18844] When Agda met Vampire

The paper discusses integrating proof assistants like Agda with automated theorem provers (ATPs) to enhance automation in mechanized math...

arXiv - AI · 3 min ·
[2602.19926] Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models
Llms

[2602.19926] Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models

The paper presents LA-LoRA, a novel approach for fine-tuning large models in privacy-preserving federated learning, addressing key challe...

arXiv - AI · 4 min ·
[2602.18797] Carbon-aware decentralized dynamic task offloading in MIMO-MEC networks via multi-agent reinforcement learning
Ai Agents

[2602.18797] Carbon-aware decentralized dynamic task offloading in MIMO-MEC networks via multi-agent reinforcement learning

This paper presents CADDTO-PPO, a carbon-aware decentralized task offloading framework for MIMO-MEC networks using multi-agent reinforcem...

arXiv - Machine Learning · 4 min ·
[2602.18782] MANATEE: Inference-Time Lightweight Diffusion Based Safety Defense for LLMs
Llms

[2602.18782] MANATEE: Inference-Time Lightweight Diffusion Based Safety Defense for LLMs

The paper presents MANATEE, a novel defense mechanism for large language models (LLMs) against adversarial attacks, utilizing a lightweig...

arXiv - Machine Learning · 3 min ·
[2602.19845] I Dropped a Neural Net
Machine Learning

[2602.19845] I Dropped a Neural Net

The paper 'I Dropped a Neural Net' explores a unique challenge in machine learning, where a neural network's layers are shuffled and need...

arXiv - Machine Learning · 3 min ·
[2602.18758] UFO: Unlocking Ultra-Efficient Quantized Private Inference with Protocol and Algorithm Co-Optimization
Machine Learning

[2602.18758] UFO: Unlocking Ultra-Efficient Quantized Private Inference with Protocol and Algorithm Co-Optimization

The paper presents UFO, a quantized two-party computation framework that optimizes private CNN inference by combining efficient protocols...

arXiv - AI · 4 min ·
[2602.18745] Synthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code
Llms

[2602.18745] Synthesizing Multimodal Geometry Datasets from Scratch and Enabling Visual Alignment via Plotting Code

The paper presents a novel pipeline for synthesizing multimodal geometry datasets, introducing the GeoCode dataset which enhances visual-...

arXiv - AI · 3 min ·
[2602.18705] EDU-MATRIX: A Society-Centric Generative Cognitive Digital Twin Architecture for Secondary Education
Ai Agents

[2602.18705] EDU-MATRIX: A Society-Centric Generative Cognitive Digital Twin Architecture for Secondary Education

The EDU-MATRIX paper presents a novel generative cognitive digital twin architecture aimed at enhancing secondary education through a soc...

arXiv - AI · 3 min ·
[2602.18678] Heterogeneity-agnostic AI/ML-assisted beam selection for multi-panel arrays
Machine Learning

[2602.18678] Heterogeneity-agnostic AI/ML-assisted beam selection for multi-panel arrays

This paper presents a novel AI/ML-based beam selection algorithm that addresses the challenges posed by heterogeneous antenna configurati...

arXiv - Machine Learning · 3 min ·
[2602.19622] VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention
Machine Learning

[2602.19622] VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention

VecFormer introduces a novel Graph Transformer model that enhances efficiency and generalization in node classification, addressing compu...

arXiv - AI · 4 min ·
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