Unverified50% confidenceFactExact time
Context-dependent representations are dynamically generated by the model according to the current sentence, so the same word gets different vectors in different contexts.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedBERT and its successor models produce context-aware dynamic vectors, where the same word receives different vector representations in different sentences.75% similarUnverifiedExact repetition versus aligned paraphrasing leads to distinctly different contextual usage patterns in the model, depending on the target relationship and the prediction window setting.75% similarUnverifiedIn the LLM context, framing effects manifest as the tone, order, labels, and implicit expectations in the prompt systematically influencing the model's output tendencies.72% similarUnverifiedContext refers to all content passed to the model during the current model call, and is only valid for that single call.72% similarUnverifiedSince behavioral structure is primarily determined by the framework, optimization experience accumulated at the framework level can theoretically be transferred and reused across different underlying models.71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1058509API
curl https://kongchang.com/api/v1/knowledge/claims/1058509MCP
get_claim(id=1058509)