InfoQ

MIT's Recursive Language Models Improve Performance on Long-Context Tasks

Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance on long-context tasks. RLMs use a programming environment to recursively ...
IEEE

A Novel Linear Impedance Model as an Alternative to the Fractional-Order Cole Models

Abstract: The fractional order Cole models are the most common form of electrical equivalent circuits (EEC) to model complex impedance (Z) of various dielectric materials like electrodes, sensors, ...
techxplore

AI models stumble on basic multiplication without special training methods, study finds

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated reasoning. But when it comes to four-digit multiplication, a task taught in ...
IEEE

Automatic programming via large language models with population self-evolution for dynamic fuzzy job shop scheduling problem

Abstract: Heuristic dispatching rules (HDRs) are widely used for solving the dynamic fuzzy job shop scheduling problem (DFJSSP). However, their performance is highly sensitive to specific scenarios ...
GitHub

AutoJudge – Programming Problem Difficulty Predictor

AutoJudge is a machine learning–based system that predicts the difficulty of programming problems using only their textual descriptions. It outputs both a difficulty class (Easy / Medium / Hard) and a ...