Research Publications
Explore our cutting-edge research contributions to artificial intelligence, quantum computing, and neural network architectures.
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Quantum Tensor Conversion for Enhanced Efficiency
Detailed exploration of quantum language model architectures with practical implementation strategies for quantum tensor conversion.
Enhancing Multi-Modal Alignment Through Progressive Difficulty
Novel curriculum learning approach for improving multi-modal alignment using contrastive learning with progressive difficulty.
A comprehensive study on integrating quantum computing principles with neural networks to develop conscious AI systems.
Transforming Raw Attention into Human-Readable Explanations
A comprehensive framework for visualizing and interpreting attention mechanisms in transformer models.
Exploring the creative capabilities and independence of Large Language Models in various applications and scenarios.