Why and How to Achieve Longer Context Windows for LLMs

Language models (LLMs) have revolutionized the field of natural language processing (NLP) over the last few years, achieving state-of-the-art results on a wide range of tasks. However, a key challenge in developing and improving these models lies in extending the length of their context. This is very important since it determines how much information is available to the model when generating an output.

However, increasing the context window of a LLM isn’t so simple. In fact, it comes at the …

art artificial intelligence challenge context context windows however interpretability key language language models language processing lies llms machine learning natural natural language natural language processing nlp positional encoding processing results state tasks transformers windows