Unverified50% confidenceOpinionExact time
Models trained mainly on web text are better at single-turn Q&A or long-form generation but may exhibit problems such as answering off-topic or over-generating in multi-turn chit-chat.
1
Sources
50%
Confidence
Long-term
Relevance
10/23/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedPolite and detailed questions tend to correspond to high-quality answers in training data; during generation, the model implicitly matches the distribution of similar contexts in the training data, so tone and format can influence output quality.73% similarUnverified这种基于前答案生成追问的技术在用户研究中被称为"半结构化访谈",传统上需要受过训练的访谈者执行70% similarUnverifiedThe vast majority of large model training data comes from human publicly available knowledge such as web text, books, code, and forum discussions.67% similarUnverifiedFor structured tasks such as classification, sentiment analysis, specific-format generation, and in-domain question answering, carefully trained small models may have a comprehensive advantage in latency, cost, and controllability.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1091520API
curl https://kongchang.com/api/v1/knowledge/claims/1091520MCP
get_claim(id=1091520)