Evaluating LLM Trustworthiness: Insights from Harmoniticity Analysis Research from VISA Team

Practical AI Solutions for Evaluating LLM Trustworthiness Assessing Response Reliability Large Language Models (LLMs) often give confident answers, but it's hard to know if they're reliable for factual questions. We're working to make LLMs more trustworthy, so users don't have to verify answers as much. Evaluating LLM Robustness Methods like FLASK and PromptBench check how consistent and resilient LLMs are to different inputs, addressing worries about their performance with rephrased instructions. Researchers from VISA have a new way to test any black-box LLM's real-time robustness, which works for any model. Correlating γ with Human Annotations Researchers are measuring how well γ values match up with trustworthiness across different LLMs and question-answer sets. This gives a practical way to see if an LLM is reliable. Human ratings show that GPT-4, ChatGPT, and Smaug-72B are among the least reliable models. AI for Business Transformation If you want to use AI to transform your business and stay ahead, check out the insights from Evaluating LLM Trustworthiness: Insights from Harmoniticity Analysis Research from VISA Team. AI can change the way you work by finding tasks to automate, setting goals, choosing AI solutions, and gradually putting them into action. Spotlight on a Practical AI Solution Check out the AI Sales Bot from itinai.com/aisalesbot. It's designed to handle customer interactions 24/7 and guide them through every step of their journey. List of Useful Links: AI Lab in Telegram @itinai – free consultation Twitter – @itinaicom