Summary of Sibyl: Simple Yet Effective Agent Framework For Complex Real-world Reasoning, by Yulong Wang et al.
Sibyl: Simple yet Effective Agent Framework for Complex Real-world Reasoning
by Yulong Wang, Tianhao Shen, Lifeng Liu, Jian Xie
First submitted to arxiv on: 15 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 This paper introduces Sibyl, a simple yet powerful large language model (LLM)-based agent framework designed to tackle complex reasoning tasks by efficiently leveraging a minimal set of tools. Building on existing agents that integrate LLMs’ inherent knowledge and zero-shot capabilities with human-designed invocation workflows, Sibyl incorporates a global workspace to manage and share knowledge and conversation history. Additionally, it implements a multi-agent debate-based jury to self-refine answers, promoting a comprehensive and balanced approach. The framework aims to reduce system complexity while expanding the scope of problems solvable-from simple tasks to complex ones requiring hours or days. Experimental results on the GAIA benchmark test set reveal that Sibyl instantiated with GPT-4 achieves state-of-the-art performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Sibyl is a new way to use big language models to solve hard problems. Right now, these models are good at answering simple questions, but they can struggle when faced with more complex tasks that require reasoning and thinking. The researchers designed Sibyl to be better at this kind of problem-solving. It does this by using a special kind of “workspace” to store information and by having multiple agents work together to come up with the best answer. This helps Sibyl be more like how humans think, by considering different ideas and weighing the pros and cons. The goal is to make it easier for people to use big language models to solve complex problems. |
Keywords
» Artificial intelligence » Gpt » Large language model » Zero shot
