Unverified50% confidenceFactExact time
General-purpose models (chat models) use single-pass generation, outputting token by token without additional internal deliberation or self-checking.
1
Sources
50%
Confidence
Long-term
Relevance
10/24/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedGeneral-purpose models (chat models) are optimized for everyday conversation scenarios, pursuing response speed and language fluency, outputting token by token, and not performing additional internal reasoning or self-checking.80% similarUnverifiedThe model is stateless, and the entire conversation is resent with each call, so understanding the mechanism helps save tokens.78% similarVerifiedLarge models are essentially stateless, and multi-turn conversations are implemented by sending the historical conversation records together with each request to the model.77% similarUnverifiedMulti-turn dialogue is implemented by re-inputting all previous conversation history to the model with each request, rather than the model having genuine memory capability.75% similarUnverifiedThe autoregressive generation mode means the model must generate tokens one by one and cannot output an entire response in parallel.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1092417API
curl https://kongchang.com/api/v1/knowledge/claims/1092417MCP
get_claim(id=1092417)