LLM Collaboration

Research on Large Language Model (LLM) collaboration explores methods for combining the strengths of multiple LLMs to overcome individual limitations and achieve enhanced performance. Current efforts focus on three main approaches: merging model parameters, ensembling outputs, and designing cooperative frameworks where LLMs specialize in different aspects of a task. This research is significant because it addresses the inherent biases and limitations of individual LLMs, leading to more robust, versatile, and potentially less biased results across diverse applications, including scientific writing, qualitative analysis, and creative tasks like story generation.