minor update on the wording

README.md

@@ -10,9 +10,12 @@ pipeline_tag: graph-ml
 <a href="https://arxiv.org/abs/2604.09130" style="color: #1a73e8; font-weight: bold; font-size: 20px;">Paper</a>
 </p>
 
-This repository contains the checkpoints for **EquiformerV3**, the third generation of the $SE(3)$-equivariant graph attention Transformer. EquiformerV3 is designed to advance efficiency, expressivity, and generality in 3D atomistic modeling.
-
-Building on EquiformerV2, this version introduces software optimizations achieving a $1.75\times$ speedup, structural improvements like equivariant merged layer normalization and smooth-cutoff attention, and SwiGLU-$S^2$ activations to incorporate many-body interactions while preserving strict equivariance. EquiformerV3 achieves state-of-the-art results on benchmarks including OC20, OMat24, and Matbench Discovery.
+This repository contains the checkpoints for **EquiformerV3**, the third generation of the SE(3)-equivariant graph attention Transformer. 
+EquiformerV3 is designed to advance efficiency, expressivity, and generality in 3D atomistic modeling.
+Building on [EquiformerV2](https://arxiv.org/abs/2306.12059), this version introduces (1) software optimizations, 
+(2) simple and effective modifications like equivariant merged layer normalization and attention with smooth cutoff, and 
+(3) SwiGLU-S^2 activations, which incorporate many-body interactions and preserve strict equivariance. 
+EquiformerV3 achieves state-of-the-art results on benchmarks including OC20, OMat24, and Matbench Discovery.
 
 Please refer to the [official GitHub repository](https://github.com/atomicarchitects/equiformer_v3) for detailed instructions on environment setup and usage.
 
@@ -96,7 +99,7 @@ Training consists of (1) direct pre-training on OMat24, (2) gradient fine-tuning
 
 ## Citation
 
-If you find this work helpful, please consider citing:
+Please consider citing this work below if it is helpful:
 
 ```bibtex
 @article{equiformer_v3,