A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations
<|reference_start|>A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations: Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them in real-world applications to ensure they produce reliable performance. Despite the well-established importance of evaluating LLMs in the community, the complexity of the evaluation process has led to varied evaluation setups, causing inconsistencies in findings and interpretations. To address this, we systematically review the primary challenges and limitations causing these inconsistencies and unreliable evaluations in various steps of LLM evaluation. Based on our critical review, we present our perspectives and recommendations to ensure LLM evaluations are reproducible, reliable, and robust.<|reference_end|>
@article{laskar2024a,
    title={A Systematic Survey and Critical Review on Evaluating Large Language
  Models: Challenges, Limitations, and Recommendations},
    author={Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, Mizanur
  Rahman, Mohammad Abdullah Matin Khan, Haidar Khan, Israt Jahan, Amran
  Bhuiyan, Chee Wei Tan, Md Rizwan Parvez, Enamul Hoque, Shafiq Joty, Jimmy
  Huang},
    journal={arXiv preprint arXiv:2407.04069},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.04069},
    primaryClass={cs.CL cs.AI cs.LG}
}