Unverified50% confidenceFactExact time
大语言模型可通过Zero-shot方式同时完成意图识别与槽位提取,并直接输出为JSON等结构化格式
1
Sources
50%
Confidence
Long-term
Relevance
7/10/2026
First Seen
Sources
Using Skills to Let AI Automatically Manage LLM API Gateway Stations
bilibili小傅哥の码场7/2/2026
Related Claims
Unverified大语言模型可通过上下文学习在无显式词典的情况下实现zero-shot领域适应来推断专有名词70% similarUnverifiedOutlines 通过将正则表达式和 JSON Schema 编译为有限状态机(FSM),再映射到 LLM 分词器的词表空间来实现约束67% similarUnverifiedConstrained Decoding guarantees at the sampling level that outputs will conform to a specified JSON Schema or regular expression; typical open-source implementations include Outlines, Guidance, and LM Format Enforcer.66% similarUnverifiedLarge language models can perform high-quality tone conversion in a zero-shot setting through instruction fine-tuning and RLHF, requiring only a description of the target tone in the prompt66% similarUnverifiedThe natural language event-creation feature of this mini-program uses a large language model (LLM) for intent recognition and structured extraction, completing entity extraction, default value completion, and formatted output.65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/458170API
curl https://kongchang.com/api/v1/knowledge/claims/458170MCP
get_claim(id=458170)