Trace as Teacher: Distilling Reasoning into Small Models
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A training method where a large model leaves a trace of its reasoning, and a small model learns from these traces, enabling the transfer of logical reasoning capability to compact neural networks.
The Sequence Knowledge #898 issue discusses a method called "The Trace Is the Teacher." The essence of the approach is that a large language model, when solving a problem, generates not only an answer but also a chain of intermediate reasoning steps—a trace. This trace is then used as a training signal for a small model, which learns not just to reproduce the final answer but the entire thought process. In this way, a compact neural network acquires the reasoning ability that is typically inherent only in large models. The method belongs to the field of knowledge distillation and allows for a significant reduction in model size without sacrificing the quality of logical inference.
Source: Meta AI (GNews) —
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