Update README.md

README.md

@@ -33,7 +33,7 @@ If you find this dataset helpful for your research, please cite our paper using
 Our dataset can be downloaded through [The CSIRO Data Access Portal](https://data.csiro.au/collection/csiro:56372?q=wild-places&_st=keyword&_str=1&_si=1). Detailed instructions for downloading the dataset can be found in the README file provided on the data access portal page. 
 
 ## Training and Benchmarking
-Here we provided pre-trained checkpoints and results for benchmarking several state-of-the-art LPR methods on the Wild-Places dataset.
+Here we provide pre-trained checkpoints and results for benchmarking several state-of-the-art LPR methods on the Wild-Places dataset.
 
 **Update Nov. 2025**:  With the release of Wild-Places v3.0, we have also re-run training for two state-of-the-art methods (LoGG3D-Net, MinkLoc3Dv2) on the Wild-Places dataset using expanded batch sizes to provide new training checkpoints which better reflect the capabilities of recent state-of-the-art GPUs.  We provide checkpoints and benchmarked results for both the recently trained models and the checkpoints released with the ICRA2023 paper.