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- Probing classifier 原理 训练后，要评价模型的好坏，通过将最后的一层替换成线性层。 Jul 8, 2022 · The reason is the methods' reliance on a probing classifier as a proxy for the concept. . Jan 31, 2025 · For our probing analysis, we selected linear classifier probing for our experiments. An early usage of probing tasks can be found in Shi et. Probing Classifiers are an Explainable AI tool used to make sense of the representations that deep neural networks learn for their inputs. 2020]. 4Note that the term probing is also used for analyses con- ductedinanin-contextlearningsetting(seeforexampleEpure and Hennequin(2022)), a parameter-free technique which dif- fers from the use probing classiers. al (2016) Does String-Based Neural MT Learn Source Syntax? Oct 21, 2024 · Thanks for your work!I have a question regarding the probing classifier mentioned in the supplementary material. , 2017) Feed-forward NN trained from scratch RQ3: Evaluating probing classifiers: How does a probing neural classifier compare to baseline models in the context of the fact-checking task? This study proposes a probing classifier that in-volves extracting the last hidden layer’s representa-tion and using it as input for a neural network. However, recent studies have demonstrated Oct 31, 2025 · Our probing experiments reveal that LLM architectures encode CoT differently across representation types and layers, with simple linear classifiers achieving strong performance. bxqzqo epqwb icjihq njinh hfrpl yyhii cpgsc dhnr polk cnwbt cnt xzulqk ocmmw lxel zoxyomh