Research & Insights
Latest Research Papers
Deep dive into our comprehensive research on AI-driven trading strategies and breakthrough technologies
Beyond Real Weights
Beyond Real Weights: Hypercomplex Representations for Stable Quantization
Progressive PHM reparameterization compresses multimodal language models by 35%, achieving 48% faster inference while preserving output quality — accepted at WACV 2026.
Bidirectional Reasoning
Bidirectional Reasoning Supervision for Multilingual Financial Decision Making
Novel bidirectional fine-tuning method integrating positive and negative rationales with PEFT, enabling 3B models to surpass label-only 70B models on multilingual financial sustainability classification.
Hybrid Decomposition
Hybrid Decomposition-Ensemble Framework: A New Era in Multi-Asset Cryptocurrency Forecasting
Revolutionary multi-scale decomposition combining wavelet transforms with neural attention mechanisms. Achieved 38.7% improvement in trend prediction accuracy.
Language Guided Forecasting
Language Guided Multivariant Feature Semantics for Time Series Forecasting
Revolutionary approach combining natural language semantics with time series analysis for 41.2% reduction in forecasting errors.
LAET Framework
LAET: Layer-wise Adaptive Ensemble Tuning Framework
Layer-wise adaptive ensemble tuning achieving 73% reduction in computational requirements while maintaining state-of-the-art performance.
Temporal Window Smoothing
Temporal Window Smoothing for Advanced Time Series Prediction
Advanced sliding window techniques for noise reduction in volatile crypto markets, improving prediction accuracy by up to 35%.
xLSTM Tensorflow
Breaking Through the Memory Wall: xLSTM Revolutionizes Cryptocurrency Forecasting
Extended Long Short-Term Memory (xLSTM) achieves unprecedented accuracy in cryptocurrency price prediction with 99.98% accuracy.