## 5 Experimental Procedure
### Up-to-Data Knowledge Update  
We collected abstracts of preprints published on arXiv from June to September 2022 as the most up-to-date knowledge dataset. We partitioned the dataset into a training dataset, validation dataset, and testing dataset with a split ratio of 7:1:2. In the conventional methodology, the generator model is directly subjected to fine-tuning. In contrast, our methodology as shown in Section 3.6 entails solely fine-tuning the discriminator model, followed by EvoText training. To ensure equitable experimental outcomes, we employ the identical epoch across all trials. \begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{**LAMBADA**} & \multicolumn{2}{c}{**CST**} & \multicolumn{2}{c}{**WikiText**} & \multicolumn{2}{c}{**PTB**} & **enwikist** & **texts** & **1 BW** \\ \cline{2-11}  & **PPL \(\downarrow\)** & **ACC \(\uparrow\)** & **ACC \(\uparrow\)** & **ACC \(\uparrow\)** & **(NE)** & **PPL \(\downarrow\)** & **(WikiText103)** & **PPL \(\downarrow\)** & **BPC \(\downarrow\)** & **BPC \(\downarrow\)** & **PPL \(\downarrow\)** \\ \hline
**Baseline** & & & & & & & & & & \\ GPT-2\({}_{null}\) & 35.13 & 45.99 & 87.65 & 83.4 & 29.41 & 37.50 & 65.85 & 1.16 & 1,17 & 75.20 \\ GPT-2\({}_{medium}\) & 15.60 & 55.84 & 92.35 & 87.1 & 22.76 & 26.37 & 47.33 & 1.01 & 1.06 & 55.72 \\ GPT-2\({}_{large}\) & 10.87 & 60.12 & 93.45 & 88.0 & 19.93 & 22.05 & 40.31 & 0.97 & 1.02 & 44.57 \\ GPT-2\({}_{all}\) & 8.63 & 63.24 & 93.0 & 89.05 & 18.34 & 17.48 & 35.76 & 0.93 & 0.98 & 42.16 \\ GPT-Ne01\({}_{33}\) & 7.50 & 57.2 & - & - & 13.10 & - & - & - & - \\ GPT-2\({}_{\rm SNd}\) & 32.93 & 47.2 & 88.24 & 86.81 & 28.14 & 38.23 & 60.15 & 1.17 & 1.16 & 72.89 \\ GPT-1\({}_{\rm SNd}\) & 13.29 & 56.99 & 92.25 & 87.31 & 20.99 & 25.01 & **46.23** & 1.00 & 1.06 & 50.72 \\ Transformer-XL & - & - & - & - & - & - & 54.5 & 0.99 & 1.08 & - \\ \hline
**RLHF by Chatgpt** & & & & & & & & & \\ GPT-2\({}_{null}\) & 30.43 & 45.79 & 88.36 & 84.44 & 29.20 & 37.48 & 64.91 & 1.16 & 1.16 & 74.99 \\ GPT-2\({}_{medium}\) & 15.29 & 55.01 & 92.41 & **87.80** & 22.66 & 26.28 & 47.30 & 1.01 & 1.06 & 55.69 \\ GPT-2\({}_{large}\) & 10.88 & 60.13 & 93.39 & 88.09 & **19.23** & **22.05** & 39.91 & 0.97 & 1.02 & 44.50 \\ GPT-2\({}_{cl}\) & 8.57 & **62.84** & 93.87 & 89.07 & 18.21 & **17.47** & 35.75 & 0.93 & 0.98 & 42.11 \\ GPT-Ne01\({}_{38}\) & 7.52 & 57.18 & - & - & 15.37 & 13.00 & - & - & - & - \\ GPT-2\({}_{\rm SNd}\) & 30.71 & 47.29 & 88.17 & **86.99** & 28.12 & 37.03 & 60.24 & 1.16 & 1.16 & 70.99 \\ GPT-1\({}_{\rm SNd}\) & 13.01 & 57.09 & 92.55 & 87.43 & **20.81** & 25.01 & 46.28 & 1.00 & 1.06 & 50.54 \\ Transformer-XL & - & - & - & - & - & - & 54.25 & 0.99 & 1.08 & - \\ \hline
**Ours01s** & & & & & & & & & & \\
**ROBERAT-2\({}_{null}\)** & **28.42** & **46.29** & **89.23** & **84.48** & **28.31** & **35.72** & **62.48** & **1.14** & **1.16** & **73.82** \\ EvoText GPT-2\({}_{null}\) & **14.21** & **57.20** & **92.85** & 87.0 & **21.94** & **25.12** & **45.93** & **1.00** & **1.06** & **55.01** \\ EvoText GPT-2\({}_{low}\) & **10.57** & **60.14** & **93.80** & **88.32** & 19.93 & 22.06 & **38.20** & **0.96** & **1.02** & **44.41** \\ EvoText GPT-2\({}_{cl}\) & **8.09** & 63.23 & **93.90** & **89.15** & **17.92** & 17.50 & **34.91** & **0.92** & **0.98** & **42.09** \\ EvoText GPT-Ne01\({}_{38}\) & **7.41** & **57.19** & - & - & 15.29 & **12.81** & - & - & - \\ EvoText GPT-2\({}_{\rm SNd}\) & **27.51** & **80.09** & **91.01** & 85.24 & **28.00** & **35.89** & **55.99** & **1.14** & **1.15** & **70.21** \\ EvoText OPT-2\({}_{\rm SNd}\) & **12.10** & **57.41** & **92.69** & **88.91** & 21.99 & **25.00** & 46.33 & **1.00** & **1.06** & **50.02** \\ EvoText & & **-** & - & - & - & - & - & **53.21** & **0.99** & **1.07** & **-** \\ Transformer-XL & - & - & - & - & - & - & - & **53.21** & **0.99** & **1.07** & **-** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: **ZERO-SHOT** performance of the model on 7 natural language processing tasks after 156 minibatch-sized EvoText sessions.