Unverified50% confidenceFactExact time
When predicting the Token at position t, a causal language model can only see the input at positions 1 to t, and cannot see future Tokens, which is usually implemented via a causal mask.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedWhen a prompt is entered, the model predicts the most likely next token based on context, rather than truly understanding the semantics.71% similarUnverifiedThe autoregressive generation mechanism of language models is essentially predicting the next token based on local context, lacking a persistently effective explicit goal representation that spans multiple rounds of interaction.69% similarUnverified推理 Token（Reasoning Token）概念源自 OpenAI o 系列模型，模型在输出可见答案前会先消耗 Token 进行内部推导，这些中间步骤对用户不可见但消耗真实算力63% similarUnverified对于大语言模型推理，吞吐通常以 token 数为单位衡量，即 tokens/s 是评估 LLM 推理框架性能的核心指标62% similarUnverifiedLook-ahead bias is when a model in a quantitative backtest uses information unavailable at time T when making a decision at time T; the solution is bitemporal modeling, allowing only queries for versions whose record time precedes the decision point.62% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1049156API
curl https://kongchang.com/api/v1/knowledge/claims/1049156MCP
get_claim(id=1049156)