Research Paper
Beyond Real Weights
Progressive PHM reparameterization compresses multimodal language models by 35%, achieving 48% faster inference while preserving output quality — accepted at WACV 2026.
RobotTrader
Welcome to
RobotTrader
RobotTrader
Advanced AI-powered automated trading for crypto markets.
Trade smarter with machine learning algorithms, risk management,
and multi-exchange support - all in one powerful platform.
Trade smarter with machine learning algorithms, risk management,
and multi-exchange support - all in one powerful platform.
Experience the power of
trading
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AI-Powered
Advanced algorithms analyze
market trends 24/7.
Risk Management
Smart stop-loss and portfolio
protection built-in.
Multi-Exchange
Connect to all major exchanges
from one unified platform.
Backtesting
Test strategies on historical data
before deploying real capital.
LSTM
Short-term memory
xLSTM
Extended memory
Transformer
Parallel processing
Three AI Architectures, One Trading Brain
It starts simple
A basic neural network that connects market data to trading decisions. Information flows forward, layer by layer.
Processing:
Sequential, one direction
LSTM adds memory loops
Now the network remembers. Loops allow information to persist, catching patterns that unfold over hours of trading.
Memory span:
24-48 hours of market data
Best for:
Day trading patterns
xLSTM extends the memory
Extended LSTM stretches memory across weeks. It remembers major support levels, trend changes, and monthly cycles.
Memory span:
30+ days of context
Best for:
Swing trading patterns
Transformers see everything at once
No more sequential processing. Every piece of data connects to every other piece instantly. Like having 100 analysts working simultaneously.
Processing:
Parallel, all at once
Best for:
Complex correlations
All three work together
LSTM catches momentum. xLSTM tracks trends. Transformers spot hidden correlations. Together, they make decisions no single model could.
67
Data inputs analyzed
3
AI models voting
10ms
Decision speed
What's New
The latest updates and breakthroughs from RobotTrader
Research Paper
Bidirectional Reasoning
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.
Explore Research
Research Paper
Hybrid Decomposition
Revolutionary multi-scale decomposition combining wavelet transforms with neural attention mechanisms. Achieved 38.7% improvement in trend prediction accuracy.
Explore Research
Research Paper
Language Guided Forecasting
Revolutionary approach combining natural language semantics with time series analysis for 41.2% reduction in forecasting errors.
Explore Research