This research introduces the Pragmatic Inference Chain (PIC) framework to improve large language models' ability to detect subtle, implicit toxic language that evades traditional detection methods.

• Creates a structured reasoning pathway that helps LLMs understand contextual implications
• Achieves 35% improvement in detecting implicit toxicity compared to baseline methods
• Demonstrates effectiveness across multiple LLM architectures including GPT and LLaMa models
• Provides a scalable approach to addressing sophisticated harmful content

For security professionals, this framework offers a significant advancement in identifying disguised harmful content that typically bypasses existing content moderation systems, helping create safer digital environments.

Pragmatic Inference Chain (PIC): Improving LLMs' Reasoning of Authentic Implicit Toxic Language