Verified65% confidenceFactExact time
Human-in-the-Loop (HITL) originated in the field of machine learning, initially referring to the introduction of human annotation and feedback during model training to improve model quality.
3
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65%
Confidence
Long-term
Relevance
7/15/2026
First Seen
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Related Claims
UnverifiedHuman-in-the-loop (HITL) was first widely applied in the active learning domain of machine learning, where the model actively requests human annotation on samples it is uncertain about.78% similarUnverifiedHuman-in-the-Loop（HITL）设计模式起源于控制系统理论，后被引入机器学习领域，其实现通常依赖置信度阈值将低置信度决策转入人工审核76% similarUnverifiedThe hybrid model of machine processing and human intervention is academically referred to as Human-in-the-Loop (HITL) or selective prediction / learning to abstain, with the core idea being to grant the model the right to decline to answer.71% similarUnverifiedTraditional machine learning engineering focuses on model training, feature engineering, and algorithm optimization, while modern LLM application development revolves around API calls, prompt engineering, retrieval-augmented generation (RAG), and agent orchestration.69% similarUnverifiedHITL机制早期主要用于主动学习的数据标注，随后在RLHF中被大规模应用，成为ChatGPT等模型对齐的核心方法68% similar
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