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README.md

@@ -82,11 +82,13 @@ The evaluation results on the above benchmarks demonstrate the advantage of ProS
 
 - **Code Generation**: We compute the average pass@1 scores on HumanEval (0-shot) and MBPP (3-shot).
 
-- **Commonsense Reasoning**: We report the average 0-shot perplexity (PPL) on PIQA, SIQA, HellaSwag, WinoGrande, and COPA.
+- **Commonsense Reasoning**: We report the average 0-shot accuracies on PIQA, SIQA, HellaSwag, WinoGrande, and COPA.
 
-- **Reading Comprehension**: We compute the average 0-shot PPL on BoolQ, 0-shot accuracy on LAMBADA and TyDi QA.
+- **Reading Comprehension**: We compute the average 0-shot accuracies on BoolQ, 0-shot accuracy on LAMBADA and TyDi QA.
 
-- **Other Popular Benchmarks**: We report the average accuracies on GSM8K (8-shot), MMLU (5-shot), Big Bench Hard (BBH) (3-shot), and the average PPL on AGI-Eval (0-shot).
+- **Other Popular Benchmarks**: We report the average accuracies on GSM8K (8-shot), MMLU (5-shot), Big Bench Hard (BBH) (3-shot), and AGI-Eval (0-shot). Refer to Appendix~\ref{sec:eval-details} for more details.
+
+Note: For PIQA, SIQA, HellaSwag, WinoGrande, COPA, BoolQ, LAMBADA, TyDi QA, and AGI-Eval, we obtain the predicted answers based on maximized perplexity. For GSM8K, MMLU, and BBH, the predicted answers are directly generated.
 
 |        Setting        | Average<br>Sparsity | Code<br>Generation | Commonsense<br>Reasoning | Reading<br>Comprehension | GSM8K | MMLU  |  BBH  | AGI Eval | Average |
 | :-------------------: | :-----------------: | :----------------: | :----------------------: | :----------------------: | :---: | :---: | :---: | :---------: | :-----: |