Syed Mubashir

A Draft-Ground-Verify-Revise Framework for Reducing Hallucination in Large Language Models

Large language models (LLMs) often generate fluent but factually unsupported or logically invalid text: failure modes broadly referred to as hallucination. A variety of approaches have been proposed to mitigate hallucination, ranging from careful benchmark design, preference modeling, and fine-tuning (e.g., RLHF) to po...