Tackling Hallucination in Large Language Models: A Survey of Cutting-Edge Techniques

Large language models (LLMs) like GPT-4, PaLM, and Llama have unlocked remarkable advances in natural language generation capabilities. However, a persistent challenge limiting their reliability and safe deployment is their tendency to hallucinate – generating content that seems coherent but is factually incorrect or ungrounded from the input context. As LLMs continue to grow more […]

The post Tackling Hallucination in Large Language Models: A Survey of Cutting-Edge Techniques appeared first on Unite.AI.

advances capabilities challenge context deployment edge gpt gpt-4 hallucination language language generation language models large language large language models llama llm llms natural natural language natural language generation palm prompt-engineering prompt tuning reliability retrieval augmented generation survey unlocked