Beyond BLEU and ROUGE - Evaluating LLMs and AI Systems

Explore advanced evaluation methodologies for large language models and AI systems in this 46-minute conference talk from Conf42 ML 2025. Discover why traditional metrics like BLEU and ROUGE fall short in assessing modern AI capabilities and learn about comprehensive evaluation frameworks that address factual accuracy, toxicity, bias, and human-centric considerations. Examine the limitations of n-gram overlap methods through real-world examples and understand how these flaws impact AI system assessment. Delve into modern evaluation approaches including fact scoring, automated evaluation technologies, and the OpenAI Evolve framework. Master generative evaluation techniques and learn to assess Retrieval-Augmented Generation (RAG) systems effectively. Compare human judgment against automated metrics and understand when each approach is most appropriate. Build knowledge of robust evaluation ecosystems and apply these concepts through practical scenarios like customer service AI evaluation. Gain insights into the future of AI evaluation and how to implement comprehensive assessment strategies that go beyond surface-level metrics to truly measure AI system performance and reliability.