6 papers
AgentBench: Evaluating LLMs as Agents
Xiao Liu, Hao Yu, Hanchen Zhang +19
The potential of Large Language Model (LLM) as agents has been widely acknowledged recently. Thus, there is an urgent need to quantitatively \textit{evaluate LLMs as agents} on cha…
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Bang Liu, Xinfeng Li, Jiayi Zhang +45
The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…
SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skills
Boyuan Zheng, Michael Y. Fatemi, Xiaolong Jin +8
To survive and thrive in complex environments, humans have evolved sophisticated self-improvement mechanisms through environment exploration, hierarchical abstraction of experience…
Is Your LLM Secretly a World Model of the Internet? Model-Based Planning for Web Agents
Yu Gu, Kai Zhang, Yuting Ning +9
Language agents based on large language models (LLMs) have demonstrated great promise in automating web-based tasks. Recent work has shown that incorporating advanced planning algo…
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu +2
In order to thrive in hostile and ever-changing natural environments, mammalian brains evolved to store large amounts of knowledge about the world and continually integrate new inf…
Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments
Yu Gu, Yiheng Shu, Hao Yu +6
The applications of large language models (LLMs) have expanded well beyond the confines of text processing, signaling a new era where LLMs are envisioned as generalist agents capab…