AI RESEARCH
Towards Lightweight Reliability: Using Soft Prompts for Hallucination Mitigation in Large Language Models
arXiv CS.LG
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ArXi:2606.00919v1 Announce Type: cross Large language models (LLMs) have seen widespread adoption across various domains, yet their reliability is frequently undermined by hallucinations - responses that are plausible-sounding but factually incorrect. In high-stakes domains, these errors can reduce trust and Our method, called Responsible Contrastive Soft Prompting (RCSP), uses a composite loss to train soft prompts that balance three goals: suppressing hallucinatory content, encouraging abstention under uncertainty, and preserving or improving factual recall.