The field of efficient Large Language Model (LLM) inference is rapidly evolving, presenting a
unique blend of opportunities and challenges. Although the field has expanded and is …

Large Language Models (LLMs) have demonstrated remarkable capabilities across various
fields, from natural language understanding to text generation. Compared to non-generative …

Large foundation models, including large language models, vision transformers, diffusion,
and large language model based multimodal models, are revolutionizing the entire machine …

Large Language Models (LLMs) have attracted extensive attention due to their remarkable
performance across various tasks. However, the substantial computational and memory …

Large Language Models (LLMs) have revolutionized a wide range of applications with their
strong human-like understanding and creativity. Due to the continuously growing model size …

Large language models (LLMs) have demonstrated remarkable abilities in natural language
processing. However, their deployment on resource-constrained embedded devices …

To enhance the efficiency of language models, it would involve optimizing their training and
inference processes to reduce computational demands while maintaining high performance …

The rapid advancements in artificial intelligence (AI), particularly the Large Language
Models (LLMs), have profoundly affected our daily work and communication forms …

Small Language Models (SLMs) have become increasingly important due to their efficiency
and performance to perform various language tasks with minimal computational resources …

Transformer neural networks (TNNs) are being applied across a widening range of
application domains, including natural language processing (NLP), machine translation, and …