Unverified50% confidenceTradeoffExact time
针对有限意图集合的轻量分类器在延迟和资源消耗上远优于通用LLM调用
1
Sources
50%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
Related Claims
Unverified使用轻量意图分类器可完全规避LLM幻觉问题，因为分类器输出空间被硬约束为预定义意图集合70% similarUnverifiedThe advantage of Dense models lies in their simple architecture, more controllable inference latency, and lower deployment threshold, making them especially suitable for local deployment, while MoE requires more VRAM but delivers stronger capabilities under equivalent computational overhead.69% similarUnverified路由分类器需同时满足轻量（推理耗时毫秒级）和准确两个要求，误判会导致质量下降或资源浪费68% similar
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