Update README.md

README.md

@@ -104,9 +104,9 @@ Otherwise, such an approach would result in excessive redundant computation and
 To simplify and relax the evaluation of synergy, we introduce a key assumption in the scoring algorithm:
 
 
-> _Theoretically, we posit that the stronger a model's synergy capability, the more likely it is to surpass the task performance of SoTA specialists when synergy is effectively employed._
-> _Then, we can simplify the synergy measurement as: if a generalist outperforms a SoTA specialist in a specific task, we consider it as evidence of a synergy effect, i.e.,_
-> _leveraging the knowledge learned from other tasks or modalities to enhance its performance in the targeted task._
+> Theoretically, we posit that the stronger a model's synergy capability, the more likely it is to surpass the task performance of SoTA specialists when synergy is effectively employed.
+> Then, we can simplify the synergy measurement as: if a generalist outperforms a SoTA specialist in a specific task, we consider it as evidence of a synergy effect, i.e.,
+> leveraging the knowledge learned from other tasks or modalities to enhance its performance in the targeted task.
 
 By making this assumption, we avoid the need for direct pairwise measurements between `task-task', `comprehension-generation', or `modality-modality', which would otherwise require complex and computationally intensive algorithms.