SelfCheckGPT for LLM Evaluation
Detecting hallucinations in language models is challenging. There are three general approaches: Measuring token-level probability distributions for indications that a…
LLM Hallucination Detection in App Development
Even ChatGPT knows it’s not always right. When prompted, “Are large language models (LLMs) always accurate?” ChatGPT says no and…
LLM Evaluation Frameworks: Head-to-Head Comparison
As teams work on complex AI agents and expand what LLM-powered applications can achieve, a variety of LLM evaluation frameworks…
LLM Juries for Evaluation
Evaluating the correctness of generated responses is an inherently challenging task. LLM-as-a-Judge evaluators have gained popularity for their ability to…
A Simple Recipe for LLM Observability
So, you’re building an AI application on top of an LLM, and you’re planning on setting it live in production.…
LLM Monitoring & Maintenance in Production Applications
Generative AI has become a transformative force, revolutionizing how businesses engage with users through chatbots, content creation, and personalized recommendations.…
Building Opik: A Scalable Open-Source LLM Observability Platform
Opik is an open-source platform for evaluating, testing, and monitoring LLM applications, created by Comet. When teams integrate language models…
