LLM Moderation
Large Model Moderation
With deep language understanding from LLMs, this page delivers semantic moderation for text, images, web pages, and UGC to detect complex risks lightweight models may miss.
Core Capabilities
Six core capabilities covering moderation needs end to end
Context-aware Semantics
Correlated multi-part text review, composite risk detection, long-form and structured page analysis, and deep contextual understanding.
Multimodal Capability
Understands images and text together to detect hidden risks in image-text combinations.
Implicit Expression Detection
Detects homophones, transliteration, and evasive variants to prevent keyword-bypass violations.
Scenario Semantics
Adapts to social chats, roleplay fiction, comments, community, and web content with context-sensitive risk understanding.
Multilingual Moderation
Supports multilingual semantic understanding and cross-language risk detection under unified moderation standards.
Risk Ranking & Labeling
Applies priority policies, confidence ranking, and sentiment polarity to separate risky from discussive content.
Technical Advantages
A leading architecture that ensures moderation quality and efficiency
Joint Multimodal Understanding
Fuse vision and language models for cross-modal content understanding.
Deep Semantic Inference
Use contextual semantic analysis to precisely infer content intent.
Continuous Optimization
Continuously optimize models for emerging violation variants.
Lower False Positives/Negatives
Reduce false positives and misses to improve moderation accuracy.
Use Cases
Widely applicable to content platforms
Social Comments / DMs Content Communities E-commerce UGC AIGC Moderation Web Content Moderation
Collaboration Workflow
Collaborates with lightweight models and Agent for balanced efficiency and accuracy
1
Lightweight Pre-filter
Quickly filters obvious violations to reduce processing pressure.
2
LLM Deep Moderation
Deep semantic understanding to identify complex violation risks.
3
Agent Intelligent Decisioning
Automatically executes moderation strategies and outputs final actions.
LLM Moderation serves as the semantic understanding layer for deep risk reasoning and structured outputs, and can collaborate with lightweight models and Agent orchestration to balance efficiency with accuracy.
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