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White-collar workers are quietly rebelling against AI as 80% outright refuse adoption mandates

submitted by /u/Effective-Trick-5795 [link] [comments]

Reddit - Artificial Intelligence · 1 min ·
Llms

[R] Forced Depth Consideration Reduces Type II Errors in LLM Self-Classification: Evidence from an Exploration Prompting Ablation Study - (200 trap prompts, 4 models, 8 Step-0 variants) [R]

LLM-Based task classifier tend to misroute prompts that look simple at first glance, but require deeper understanding - I call it "Type I...

Reddit - Machine Learning · 1 min ·
Machine Learning

Anyone have an S3-compatible store that actually saturates H100s without the AWS egress tax? [R]

We’re training on a cluster in Lambda Labs, but our main dataset ( over 40TB) is sitting in AWS S3. The egress fees are high, so we tried...

Reddit - Machine Learning · 1 min ·

All Content

[2602.10016] Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design
Llms

[2602.10016] Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design

The paper 'Kunlun' presents a unified architecture for massive-scale recommendation systems, addressing scaling laws and resource allocat...

arXiv - AI · 4 min ·
[2602.06797] Optimal Learning-Rate Schedules under Functional Scaling Laws: Power Decay and Warmup-Stable-Decay
Llms

[2602.06797] Optimal Learning-Rate Schedules under Functional Scaling Laws: Power Decay and Warmup-Stable-Decay

This paper explores optimal learning-rate schedules (LRSs) within the functional scaling law framework, revealing distinct behaviors in e...

arXiv - Machine Learning · 4 min ·
[2602.09572] Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases
Machine Learning

[2602.09572] Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases

The paper introduces Predictive Query Language (PQL), a domain-specific language designed to streamline predictive modeling on relational...

arXiv - AI · 4 min ·
[2602.06374] A Multiplicative Neural Network Architecture: Locality and Regularity of Approximation
Machine Learning

[2602.06374] A Multiplicative Neural Network Architecture: Locality and Regularity of Approximation

This paper presents a novel multiplicative neural network architecture that emphasizes multiplicative interactions for function approxima...

arXiv - Machine Learning · 3 min ·
[2602.06320] High-Dimensional Limit of Stochastic Gradient Flow via Dynamical Mean-Field Theory
Machine Learning

[2602.06320] High-Dimensional Limit of Stochastic Gradient Flow via Dynamical Mean-Field Theory

This paper explores the high-dimensional dynamics of stochastic gradient flow (SGF) in machine learning, providing a closed system of equ...

arXiv - Machine Learning · 4 min ·
[2602.01427] Robust Generalization with Adaptive Optimal Transport Priors for Decision-Focused Learning
Machine Learning

[2602.01427] Robust Generalization with Adaptive Optimal Transport Priors for Decision-Focused Learning

This paper presents a Prototype-Guided Distributionally Robust Optimization (PG-DRO) framework that enhances few-shot learning by integra...

arXiv - Machine Learning · 3 min ·
[2602.07294] Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings
Llms

[2602.07294] Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings

The paper introduces Fin-RATE, a benchmark for evaluating Large Language Models (LLMs) on SEC filings, addressing the limitations of exis...

arXiv - AI · 4 min ·
[2601.20336] Do Whitepaper Claims Predict Market Behavior? Evidence from Cryptocurrency Factor Analysis
Nlp

[2601.20336] Do Whitepaper Claims Predict Market Behavior? Evidence from Cryptocurrency Factor Analysis

This study examines the relationship between cryptocurrency whitepaper claims and actual market behavior, revealing weak predictive power...

arXiv - Machine Learning · 3 min ·
[2601.15518] DS@GT at TREC TOT 2025: Bridging Vague Recollection with Fusion Retrieval and Learned Reranking
Llms

[2601.15518] DS@GT at TREC TOT 2025: Bridging Vague Recollection with Fusion Retrieval and Learned Reranking

This paper presents a two-stage retrieval system designed for the TREC Tip-of-the-Tongue task, integrating multiple retrieval methods wit...

arXiv - Machine Learning · 3 min ·
[2601.02241] From Mice to Trains: Amortized Bayesian Inference on Graph Data
Machine Learning

[2601.02241] From Mice to Trains: Amortized Bayesian Inference on Graph Data

This article presents a novel approach to Amortized Bayesian Inference (ABI) tailored for graph data, addressing challenges in posterior ...

arXiv - Machine Learning · 4 min ·
[2602.01696] Cross-Modal Purification and Fusion for Small-Object RGB-D Transmission-Line Defect Detection
Ai Safety

[2602.01696] Cross-Modal Purification and Fusion for Small-Object RGB-D Transmission-Line Defect Detection

This paper presents CMAFNet, a novel network for detecting small defects in transmission lines using RGB-D data, achieving significant pe...

arXiv - AI · 4 min ·
[2512.19131] Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT
Machine Learning

[2512.19131] Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT

The paper presents Murmura, a framework for trust-aware model personalization in decentralized federated learning (DFL) for wearable IoT ...

arXiv - Machine Learning · 4 min ·
[2602.01023] Unifying Ranking and Generation in Query Auto-Completion via Retrieval-Augmented Generation and Multi-Objective Alignment
Nlp

[2602.01023] Unifying Ranking and Generation in Query Auto-Completion via Retrieval-Augmented Generation and Multi-Objective Alignment

This paper presents a unified framework for Query Auto-Completion (QAC) that integrates Retrieval-Augmented Generation (RAG) and multi-ob...

arXiv - AI · 4 min ·
[2512.16051] Graph Neural Networks for Interferometer Simulations
Machine Learning

[2512.16051] Graph Neural Networks for Interferometer Simulations

This article presents a novel application of Graph Neural Networks (GNNs) for simulating interferometer designs, specifically for the LIG...

arXiv - Machine Learning · 3 min ·
[2601.21812] A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting
Machine Learning

[2601.21812] A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting

This paper presents a novel forward diffusion process for time-series forecasting that effectively decomposes signals into spectral compo...

arXiv - Machine Learning · 3 min ·
[2601.20538] Interpreting Emergent Extreme Events in Multi-Agent Systems
Llms

[2601.20538] Interpreting Emergent Extreme Events in Multi-Agent Systems

This paper presents a framework for interpreting emergent extreme events in multi-agent systems, focusing on the origins and drivers of t...

arXiv - AI · 4 min ·
[2512.07425] Seismic event classification with a lightweight Fourier Neural Operator model
Machine Learning

[2512.07425] Seismic event classification with a lightweight Fourier Neural Operator model

This article presents a lightweight Fourier Neural Operator model for real-time seismic event classification, demonstrating high accuracy...

arXiv - Machine Learning · 4 min ·
[2511.19628] Optimization and Regularization Under Arbitrary Objectives
Machine Learning

[2511.19628] Optimization and Regularization Under Arbitrary Objectives

This article explores the limitations of Markov Chain Monte Carlo (MCMC) methods in optimization and regularization under arbitrary objec...

arXiv - Machine Learning · 4 min ·
[2601.15109] An Agentic Operationalization of DISARM for FIMI Investigation on Social Media
Robotics

[2601.15109] An Agentic Operationalization of DISARM for FIMI Investigation on Social Media

This article presents a framework-agnostic, agent-based operationalization of the DISARM framework to investigate Foreign Information Man...

arXiv - AI · 4 min ·
[2511.07270] High-Dimensional Asymptotics of Differentially Private PCA
Data Science

[2511.07270] High-Dimensional Asymptotics of Differentially Private PCA

This paper investigates the high-dimensional asymptotics of differentially private PCA, focusing on optimal noise levels for privacy guar...

arXiv - Machine Learning · 4 min ·
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