[1] Hashemi, H., Eisner, J., Rosset, C., Van Durme, B., & Kedzie, C. (2024). LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts. Association for Computational Linguistics (ACL), 13806-13834. https://doi.org/10.18653/v1/2024.acl-long.745
[2] Yehuda, Y., Malkiel, I., Barkan, O., Weill, J., Ronen, R., & Koenigstein, N. (2024, March 5). InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers. arXiv.org. https://arxiv.org/abs/2403.02889
https://www.anthropic.com/engineering/building-effective-agents
https://openai.com/index/new-tools-for-building-agents
https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders
https://cloud.google.com/discover/what-are-ai-agents