With the bomb ignited by ChatGPT, Transformer-based Large Language Models (LLMs)
have paved a revolutionary path toward Artificial General Intelligence (AGI) and have been …

Large language models (LLMs) have demonstrated great success in various fields,
benefiting from their huge amount of parameters that store knowledge. However, LLMs still …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …

We propose a method to fuse frozen text-only large language models (LLMs) with pre-
trained image encoder and decoder models, by mapping between their embedding spaces …

Large Language Models (LLMs) have demonstrated remarkable capabilities in important
tasks such as natural language understanding and language generation, and thus have the …

A major limitation for the broader scope of problems solvable by transformers is the
quadratic scaling of computational complexity with input size. In this study, we investigate …

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 …

Why do large language models sometimes output factual inaccuracies and exhibit
erroneous reasoning? The brittleness of these models, particularly when executing long …

Autonomous agents capable of planning, reasoning, and executing actions on the web offer
a promising avenue for automating computer tasks. However, the majority of existing …