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Llms

[D] The Bitter Lesson of Optimization: Why training Neural Networks to update themselves is mathematically brutal (but probably inevitable)

Are we still stuck in the "feature engineering" era of optimization? We trust neural networks to learn unimaginably complex patterns from...

Reddit - Machine Learning · 1 min ·
Google quietly launched an AI dictation app that works offline
Machine Learning

Google quietly launched an AI dictation app that works offline

Google's new offline-first dictation app uses Gemma AI models to take on the apps like Wispr Flow.

TechCrunch - AI · 4 min ·
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 ·

All Content

[2602.16194] Temporal Panel Selection in Ongoing Citizens' Assemblies
Machine Learning

[2602.16194] Temporal Panel Selection in Ongoing Citizens' Assemblies

This paper presents a framework for temporal panel selection in ongoing citizens' assemblies, ensuring proportional representation and in...

arXiv - AI · 4 min ·
[2602.16062] Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets
Ai Agents

[2602.16062] Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets

This paper presents a framework for decentralized local energy markets using implicit cooperation among agents, optimizing coordination w...

arXiv - Machine Learning · 4 min ·
[2602.16061] Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
Machine Learning

[2602.16061] Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models

This paper presents a novel framework for partial identification of population quantities under missing data, utilizing weak shadow varia...

arXiv - Machine Learning · 4 min ·
[2602.16177] Conjugate Learning Theory: Uncovering the Mechanisms of Trainability and Generalization in Deep Neural Networks
Machine Learning

[2602.16177] Conjugate Learning Theory: Uncovering the Mechanisms of Trainability and Generalization in Deep Neural Networks

This paper introduces Conjugate Learning Theory, exploring trainability and generalization in deep neural networks through a novel theore...

arXiv - AI · 4 min ·
[2602.16174] Edge Learning via Federated Split Decision Transformers for Metaverse Resource Allocation
Machine Learning

[2602.16174] Edge Learning via Federated Split Decision Transformers for Metaverse Resource Allocation

The paper presents Federated Split Decision Transformers (FSDT) for optimizing resource allocation in mobile edge computing for the metav...

arXiv - AI · 4 min ·
[2602.16000] Imaging-Derived Coronary Fractional Flow Reserve: Advances in Physics-Based, Machine-Learning, and Physics-Informed Methods
Machine Learning

[2602.16000] Imaging-Derived Coronary Fractional Flow Reserve: Advances in Physics-Based, Machine-Learning, and Physics-Informed Methods

This article reviews advances in imaging-derived fractional flow reserve (FFR) methods, focusing on machine learning and physics-informed...

arXiv - Machine Learning · 4 min ·
[2602.15996] Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation
Machine Learning

[2602.15996] Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation

This paper explores saddle point reformulation in Vertical Federated Learning (VFL), presenting methods for efficient model training acro...

arXiv - Machine Learning · 3 min ·
[2602.16124] Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System
Nlp

[2602.16124] Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System

The paper presents a novel approach called MultiFaceted Learnable Index (MFLI) for enhancing ANN-based retrieval in large-scale recommend...

arXiv - Machine Learning · 4 min ·
[2602.15951] MadEvolve: Evolutionary Optimization of Cosmological Algorithms with Large Language Models
Llms

[2602.15951] MadEvolve: Evolutionary Optimization of Cosmological Algorithms with Large Language Models

The paper presents MadEvolve, a framework for optimizing cosmological algorithms using large language models, demonstrating significant i...

arXiv - Machine Learning · 3 min ·
[2602.16111] Surrogate-Based Prevalence Measurement for Large-Scale A/B Testing
Llms

[2602.16111] Surrogate-Based Prevalence Measurement for Large-Scale A/B Testing

The paper presents a scalable framework for measuring content prevalence in large-scale A/B testing, decoupling expensive labeling from e...

arXiv - AI · 4 min ·
[2602.16110] OmniCT: Towards a Unified Slice-Volume LVLM for Comprehensive CT Analysis
Computer Vision

[2602.16110] OmniCT: Towards a Unified Slice-Volume LVLM for Comprehensive CT Analysis

The paper presents OmniCT, a unified slice-volume large vision-language model (LVLM) designed for comprehensive CT analysis, addressing l...

arXiv - AI · 4 min ·
[2602.16109] Federated Graph AGI for Cross-Border Insider Threat Intelligence in Government Financial Schemes
Ai Agents

[2602.16109] Federated Graph AGI for Cross-Border Insider Threat Intelligence in Government Financial Schemes

The paper presents FedGraph-AGI, a federated learning framework designed to enhance cross-border insider threat detection in government f...

arXiv - AI · 4 min ·
[2602.15925] Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation
Machine Learning

[2602.15925] Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation

The paper presents a novel method, Stochastic Gradient Lattice Random Walk (SGLRW), to enhance Bayesian posterior sampling by improving r...

arXiv - Machine Learning · 3 min ·
[2602.16085] Language Statistics and False Belief Reasoning: Evidence from 41 Open-Weight LMs
Llms

[2602.16085] Language Statistics and False Belief Reasoning: Evidence from 41 Open-Weight LMs

This article investigates the mental state reasoning of language models (LMs) using 41 open-weight models, revealing insights into their ...

arXiv - AI · 4 min ·
[2602.15920] Including Node Textual Metadata in Laplacian-constrained Gaussian Graphical Models
Machine Learning

[2602.15920] Including Node Textual Metadata in Laplacian-constrained Gaussian Graphical Models

This paper presents a novel approach to graph learning in Gaussian Graphical Models (GGMs) by incorporating node textual metadata, enhanc...

arXiv - Machine Learning · 3 min ·
[2602.15914] Steering Dynamical Regimes of Diffusion Models by Breaking Detailed Balance
Machine Learning

[2602.15914] Steering Dynamical Regimes of Diffusion Models by Breaking Detailed Balance

This paper explores how breaking detailed balance in generative diffusion processes can enhance reverse processes while maintaining stati...

arXiv - Machine Learning · 3 min ·
[2602.16008] MAEB: Massive Audio Embedding Benchmark
Machine Learning

[2602.16008] MAEB: Massive Audio Embedding Benchmark

The MAEB paper introduces a comprehensive benchmark for evaluating audio models across 30 tasks in over 100 languages, highlighting perfo...

arXiv - Machine Learning · 4 min ·
[2602.15983] ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization
Llms

[2602.15983] ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization

ReLoop introduces a structured approach to improve the reliability of LLM-generated optimization code by addressing silent failures throu...

arXiv - Machine Learning · 4 min ·
[2602.15968] From Reflection to Repair: A Scoping Review of Dataset Documentation Tools
Data Science

[2602.15968] From Reflection to Repair: A Scoping Review of Dataset Documentation Tools

This article presents a scoping review of dataset documentation tools, analyzing motivations behind their design and factors affecting th...

arXiv - AI · 4 min ·
[2602.15958] DocSplit: A Comprehensive Benchmark Dataset and Evaluation Approach for Document Packet Recognition and Splitting
Data Science

[2602.15958] DocSplit: A Comprehensive Benchmark Dataset and Evaluation Approach for Document Packet Recognition and Splitting

The paper introduces DocSplit, a benchmark dataset and evaluation framework for document packet recognition and splitting, addressing cha...

arXiv - AI · 4 min ·
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