March 14, 2024, 4:43 a.m. | Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin

cs.LG updates on arXiv.org arxiv.org

arXiv:2311.05657v2 Announce Type: replace-cross
Abstract: Closed-source agents suffer from several issues such as a lack of affordability, transparency, and reproducibility, particularly on complex interactive tasks. This motivates the development of open-source alternatives. We introduce LUMOS, one of the first frameworks for training open-source LLM-based agents. LUMOS features a learnable, unified, and modular architecture with a planning module that learns high-level subgoal generation, and a grounding module trained to translate these into actions using various tools in the execution module. The …

abstract agent agents arxiv cs.ai cs.cl cs.lg development features frameworks interactive language llm modular reproducibility tasks training transparency type

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