Generative language models face persistent challenges when transitioning from training to practical application. One significant difficulty lies in aligning these models to perform optimally during ...

Generative language models face persistent challenges when transitioning from training to practical application. One significant difficulty lies in aligning these models to perform optimally during ...

FineWeb2 significantly advances multilingual pretraining datasets, covering over 1000 languages with high-quality data. The dataset uses approximately 8 terabytes of compressed text data and contains ...

Generative language models face persistent challenges when transitioning from training to practical application. One significant difficulty lies in aligning these models to perform optimally during ...

The self-attention mechanism is a building block of transformer architectures that faces huge challenges both in the theoretical foundations and practical implementation. Despite such successes in ...

Designing neuromorphic sensory processing units (NSPUs) based on Temporal Neural Networks (TNNs) is a highly challenging task due to the reliance on manual, labor-intensive hardware development ...

Text-to-audio generation has transformed how audio content is created, automating processes that traditionally required significant expertise and time. This ...

Retrieval-augmented generation (RAG) enhances the output of Large Language Models (LLMs) using external knowledge bases. These systems work by retrieving relevant information linked to the input and ...

Generative language models face persistent challenges when transitioning from training to practical application. One significant difficulty lies in aligning these models to perform optimally during ...

Federated learning has emerged as an approach for collaborative training among medical institutions while preserving data privacy. However, the non-IID nature of data, stemming from differences in ...

Designing neuromorphic sensory processing units (NSPUs) based on Temporal Neural Networks (TNNs) is a highly challenging task due to the reliance on manual, labor-intensive hardware development ...

Generative language models face persistent challenges when transitioning from training to practical application. One significant difficulty lies in aligning these models to perform optimally during ...