Democratizing LLMs: An Exploration of Cost-Performance Trade-offs in Self-Refined Open-Source Models

This paper explores cost-performance trade-offs in self-refined open-source language models, contributing to the democratization of LLMs.

Citation

```bibtex @inproceedings{shashidhar2023democratizing, title={Democratizing {LLM}s: An Exploration of Cost-Performance Trade-offs in Self-Refined Open-Source Models}, author={Shashidhar, Sumuk and Chinta, Abhinav and Sahai, Vaibhav and Wang, Zhenhailong and Ji, Heng}, booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023}, pages={9070–9084}, year={2023}, address={Singapore}, publisher={Association for Computational Linguistics} }