MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning

One-line Summary

MemCast introduces a memory-driven framework for time series forecasting that leverages past experiences to improve prediction accuracy and adaptability over time.

Plain-language Overview

Time series forecasting is crucial for making informed decisions in various fields. MemCast is a new approach that uses a memory-based system to improve how we forecast future events by learning from past predictions. This method organizes past experiences into a structured memory, helping the system make better predictions by using historical patterns and reasoning strategies. The system can also adapt over time, improving its accuracy as it accumulates more experiences.

Technical Details