Recent advances in AI and NLP have led to the development of KwaiAgents, an information-seeking agent system based on Large Language Models (LLMs). It comprises KAgentSys, KAgentLMs, and KAgentBench, demonstrating improved performance compared to existing open-source systems. Additionally, the Meta-Agent Tuning framework ensures effective performance with less sophisticated LLMs.
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Meet KwaiAgents: A Generalized Information Seeking Agent System based on Large Language Models LLMs
Recent advances in Artificial Intelligence (AI) and Natural Language Processing (NLP) have led to the introduction of Large Language Models (LLMs). KwaiAgents, an information-seeking agent system based on LLMs, is composed of three primary parts:
KAgentSys
This includes a special hybrid search browse and time-aware toolset together with a planning-concluding approach, allowing efficient management of data from multiple sources.
KAgentLMs
It includes a number of sizable language models with agent features, such as tool usage, planning, and reflection. The system explores the possibility of obtaining generalized agent capabilities for information-seeking tasks through smaller, open-sourced LLMs.
Meta-Agent Tuning (MAT) Framework
This framework guarantees effective performance, even with less sophisticated LLMs. It ensures that 7B or 13B open-source models can perform well in a variety of agent systems.
The team has validated these capabilities using both human assessments and benchmark evaluations. KwaiAgents perform better than a number of open-sourced agent systems when they follow MAT.
If you want to evolve your company with AI, stay competitive, and use Meet KwaiAgents for your advantage. Discover how AI can redefine your way of work by:
- Identifying Automation Opportunities
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