Unverified50% confidenceFactExact time
深度推理模式的技术基础是链式思维(Chain-of-Thought)推理与推理时计算扩展(Inference-time Compute Scaling)
1
Sources
50%
Confidence
Long-term
Relevance
8/8/2026
First Seen
Sources
Related Claims
UnverifiedLightweight models compress parameter scale through techniques such as knowledge distillation and quantization, optimizing for inference speed and cost, but make trade-offs in complex logical reasoning and long-context understanding.77% similarUnverifiedDify-Chat支持深度思考(Deep Thinking)展示,可呈现模型的推理过程76% similarUnverifiedTest-time compute scaling improves performance on complex reasoning tasks by investing more computation during the inference stage through methods such as extending the chain of thought, multi-path sampling with best-of-n selection, and self-verification reflection.75% similarUnverifiedThe core mechanism of the o1 series models is inference-time compute scaling, which performs deep reasoning by generating a long chain-of-thought process during the inference phase.75% similarUnverifiedThe core of the Extended Thinking mechanism is allocating a greater computational budget during the model's reasoning phase, allowing the model to analyze problems from multiple angles, self-correct, and compare solutions — a process the academic community calls Inference-Time Compute Scaling.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/705742API
curl https://kongchang.com/api/v1/knowledge/claims/705742MCP
get_claim(id=705742)