MIT’s new ‘recursive’ framework lets LLMs process 10 million tokens without context rot

While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...
Unite.AI

When AI Agents Start Building AI: The Recursive Intelligence Explosion Nobody’s Prepared For

For decades, artificial intelligence advanced in careful, mostly linear steps. Researchers built models. Engineers improved performance. Organizations deployed systems to automate specific tasks. Each ...
IEEE

Recursive Neural Network POS Tagger

This project explores the application of recursive neural networks (RNNs) in natural language processing, specifically for part-of-speech (POS) tagging. Drawing on foundational work by Socher et al.
Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Phys.org

Self-learning neural network cracks iconic black holes

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Scientific Research Publishing

Hornik, K., Stinchcombe, M. and White, H. (1989) Multilayer Feedforward Networks Are Universal Approximators. Neural Networks, 2, 359-366.

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
IEEE

Adaptive Recursive Terminal Sliding Mode Control for MEMS Gyros Using Improved Neural Network With Constrained Input Mapping

Abstract: To drive the gyroscope into a command vibration mode, and to simultaneously estimate the angular velocity, this paper proposes an improved fully adjusted neural network-based adaptive ...
Scientific Research Publishing

Kamp, Y, Hasler M. (1990) Recursive Neural Networks for Associative Memory. John Wiley and Sons, Inc.

ABSTRACT: This paper discusses the general decay synchronization problem for a class of fuzzy competitive neural networks with time-varying delays and discontinuous activation functions. Firstly, ...