Unverified50% confidenceFactExact time
The context boundary refers to all the input visible to the model in a single inference; if not explicitly constrained, the system prompt, conversation history, and irrelevant retrieved fragments get spliced into the context, and small models are easily distracted into hallucinating.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWhen constraining output format through prompts, the model may forget these constraints in long conversations or complex reasoning scenarios.78% similarUnverifiedLatent space reasoning allows the model to complete thinking in a continuous vector space composed of hidden states, only decoding the result into text at the final stage.76% similarUnverified分词特征差异发生在推理链路底层，难以通过提示工程掩盖，可作为模型识别手段75% similarUnverifiedThe scenario embedding naturally lies in the model's own semantic space, requires no additional external encoder, and shares the same set of representations as the model's generation process.75% similarUnverifiedInductive bias refers to the inherent tendency of a learning model to generalize on unseen data, arising from the constraints that model architecture, hypothesis space or prior knowledge place on solutions.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1069291API
curl https://kongchang.com/api/v1/knowledge/claims/1069291MCP
get_claim(id=1069291)