Summary of Middleware For Llms: Tools Are Instrumental For Language Agents in Complex Environments, by Yu Gu et al.
Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments
by Yu Gu, Yiheng Shu, Hao Yu, Xiao Liu, Yuxiao Dong, Jie Tang, Jayanth Srinivasa, Hugo Latapie, Yu Su
First submitted to arxiv on: 22 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Recent advancements in large language models (LLMs) have enabled them to operate beyond text processing, transforming into generalist agents capable of navigating complex environments. However, these environments often exceed LLMs’ short-term memory capacity, necessitating the development of tools to augment their capabilities. Our research introduces a novel class of tools, middleware, which serves as a shielding layer for LLMs, facilitating proactive exploration within massive environments. In two representative complex environments – knowledge bases (KBs) and databases – we demonstrate the significant potential of tool-augmented language agents, with GPT-4 achieving 2.8X the performance of the best baseline in database tasks and 2.2X in KB tasks. Our findings pave the way for advancing language agents in real-world applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models (LLMs) are becoming super smart computers that can do lots of things, not just understand text. But sometimes they get overwhelmed by too much information. To help them handle this complexity, we’ve developed a new type of tool called middleware. This tool acts like a shield around the LLM, helping it explore and find what it needs in big databases or knowledge bases. We tested this idea with GPT-4, a very good language model, and found that it performed much better when using the middleware tool. This breakthrough could lead to even more powerful language models that can help us in many ways. |
Keywords
» Artificial intelligence » Gpt » Language model
