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

Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …

The rapid advancement of chat-based language models has led to remarkable progress in
complex task-solving. However, their success heavily relies on human input to guide the …

Software engineering is a domain characterized by intricate decision-making processes,
often relying on nuanced intuition and consultation. Recent advancements in deep learning …

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 …

As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …

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 …

We present DRESS a large vision language model (LVLM) that innovatively exploits Natural
Language feedback (NLF) from Large Language Models to enhance its alignment and …

To solve complex tasks, large language models (LLMs) often require multiple rounds of
interactions with the user, sometimes assisted by external tools. However, current evaluation …

The recent development on large multimodal models (LMMs), especially GPT-4V (ision) and
Gemini, has been quickly expanding the capability boundaries of multimodal models …