RST -Guarder: Enhancing Long-Context Robustness for Safeguards via RST Parsing and Probabilistic Inference
Xu Zhang · Xiaojun Wan
摘要
As large language models (LLMs) demonstrate remarkable capabilities across a wide range of tasks, ensuring the safety of their outputs is increasingly critical. To mitigate the risk of policy-violating responses, numerous guardrail models have been developed for harmful-content detection. While e...