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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. RESEARCH · arXiv cs.AI English(EN) · · [2 sources]

    A Unified Siamese Learning Framework for Zero-Day Anomaly Detection and Classification in Optical Networks

    Researchers have developed a novel Siamese neural network designed for optical networks. This framework enables zero-day anomaly detection and one-shot classification, meaning it can identify and categorize new types of anomalies without prior training. The system demonstrates over 99% accuracy and can adapt instantly to different lightpaths and previously unseen anomaly types. AI

    IMPACT This framework could significantly improve the reliability and security of optical networks by enabling rapid detection of novel threats.

  2. TOOL · arXiv cs.LG English(EN) ·

    Bridging the Gap Between Natural Language and Market Dynamics via High-Dimensional Representation Learning

    Researchers have developed a new method to improve financial forecasting by using high-dimensional embeddings from FinBERT instead of simple sentiment scores. Their Transformer-based architecture, which incorporates Siamese-optimized embeddings, demonstrated superior predictive accuracy for short-term stock price movements compared to traditional scalar baselines. This approach preserves the nuanced context found in financial news, leading to better performance. AI

    IMPACT This research could lead to more accurate short-term stock market predictions by better leveraging the information within financial news.