Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

The human ability to learn, generalize, and control complex manipulation tasks through multi-
modality feedback suggests a unique capability, which we refer to as dexterity intelligence …

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 …

Large Language Models (LLMs) have drawn a lot of attention due to their strong
performance on a wide range of natural language tasks, since the release of ChatGPT in …

Recent efforts have incorporated large language models (LLMs) with external resources (eg,
the Internet) or internal control flows (eg, prompt chaining) for tasks requiring grounding or …

Language agents show potential in being capable of utilizing natural language for varied
and intricate tasks in diverse environments, particularly when built upon large language …

The massive successes of large language models (LLMs) encourage the emerging
exploration of LLM-augmented Autonomous Agents (LAAs). An LAA is able to generate …

Large language models (LLMs) have dramatically enhanced the field of language
intelligence, as demonstrably evidenced by their formidable empirical performance across a …

We introduce Lumos, a novel framework for training language agents that employs a unified
data format and a modular architecture based on open-source large language models …

Autonomous interaction with the computer has been a longstanding challenge with great
potential, and the recent proliferation of large language models (LLMs) has markedly …