Artificial Intelligence

Large Language Models (LLMs) have made significant strides in addressing various reasoning tasks, such as math problems, code generation, and planning. However, as these tasks become more complex, LLMs struggle with inconsistencies, hallucinations, and errors. This is especially true for tasks requiring multiple reasoning steps, which often operate on a "System 1" level of thinking…

Natural Language Processing (NLP), a field within artificial intelligence, is focused on creating ways for computers and human language to interact. It's used in many technology sectors such as machine translation, sentiment analysis, and information retrieval. The challenge presently faced is the evaluation of long-context language models, which are necessary for understanding and generating text…

Large language models (LLMs), despite their significant advancements, often struggle in situations where information is spread across long stretches of text. This issue, referred to as the "lost-in-the-middle" problem, results in a diminished ability for LLMs to accurately find and use information that isn't located near the start or end of the text. Consequently, LLMs…

Large language models (LLMs), despite their advancements, often face difficulties in managing long contexts where information is scattered across the entire text. This phenomenon is referred to as the ‘lost-in-the-middle’ problem, where LLMs struggle to accurately identify and utilize information within such contexts, especially as it becomes distant from the beginning or end. Researchers from…