Enhancing the General Agent Capabilities of Low-Parameter LLMs through Tuning and Multi-Branch Reasoning

arXiv:2403.19962v1 Announce Type: cross
Abstract: Open-source pre-trained Large Language Models (LLMs) exhibit strong language understanding and generation capabilities, making them highly successful in a variety of tasks. However, when used as agents for dealing with complex problems in the real world, their performance is far inferior to large commercial models such as ChatGPT and GPT-4. As intelligent agents, LLMs need to have the capabilities of task planning, long-term memory, and the ability to leverage external tools to achieve satisfactory performance. …

abstract agent agents arxiv capabilities cs.ai cs.cl cs.lg general however language language models language understanding large language large language models llms low making performance reasoning tasks them through type understanding world