June 10, 2024, 4:42 a.m. | Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, Mohit Bansal, Jason Weston, Xian Li

cs.CL updates on arXiv.org arxiv.org

arXiv:2310.15123v2 Announce Type: replace
Abstract: Large Language Models (LLMs) are frequently used for multi-faceted language generation and evaluation tasks that involve satisfying intricate user constraints or taking into account multiple aspects and criteria. However, their performance can fall short, due to the model's lack of coherence and inability to plan and decompose the problem. We propose Branch-Solve-Merge (BSM), a Large Language Model program (Schlag et al., 2023) for tackling such challenging natural language tasks. It consists of branch, solve, and …

abstract arxiv constraints cs.ai cs.cl cs.lg evaluation however language language generation language model language model evaluation language models large language large language model large language models llms merge multiple performance replace solve tasks type

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