Paper Review: Kronos – A Temporal Foundation Model for Financial Market Language

This article reviews Kronos, a unified and scalable pre‑training framework designed for financial K‑line data, detailing its tokenization approach, autoregressive architecture, large‑scale pre‑training on 12 billion records, and experimental results that show substantial gains in price prediction, volatility forecasting, synthetic data generation, and investment simulation.

Foundation ModelKronosautoregressive pretraining

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Paper Review: Kronos – A Temporal Foundation Model for Financial Market Language

AI Frontier Lectures

Apr 13, 2025 · Artificial Intelligence

How SICOG Enables Self‑Evolving Multimodal Models with Zero‑Label Data

The paper introduces SICOG, a three‑stage collaborative framework that combines post‑training enhancement, inference optimization, and re‑pretraining with a self‑generated data loop, allowing large multimodal models to continuously improve without massive human‑annotated datasets, and demonstrates consistent gains across dozens of benchmarks.

Lifelong LearningModel Scalingchain‑of‑thought

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How SICOG Enables Self‑Evolving Multimodal Models with Zero‑Label Data