formatting fixes

Author: ga58lar

docs/paper.bib

@@ -114,7 +114,7 @@ @INPROCEEDINGS{Foote2013
 }
 
 @misc{Kulmer2025-2,
-	author = {Kulmer, Dominik and  Tahiraj, Ilir and  Lienkamp, Markus},
+	author = {Kulmer, Dominik and Tahiraj, Ilir and Lienkamp, Markus},
 	title = {{Autonomous Driver Licence (ADL) dataset}},
 	type = {Dataset},
 	year = {2025},
@@ -124,7 +124,7 @@ @misc{Kulmer2025-2
 }
 
 @conference{Leitenstern2025,
-author={Maximilian Leitenstern and Marko Alten and Christian Bolea{-}Schaser and Dominik Kulmer and Marcel Weinmann and Markus Lienkamp},
+author={Leitenstern, Maximilian and Alten, Marko and Bolea{-}Schaser, Christian and Kulmer, Dominik and Weinmann, Marcel and Lienkamp, Markus},
 title={FlexCloud: Direct, Modular Georeferencing and Drift-Correction of Point Cloud Maps},
 booktitle={Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
 year={2025},
@@ -148,4 +148,3 @@ @conference{Kulmer2025-1
   isbn={978-989-758-745-0},
   issn={2184-495X},
 }
-

docs/paper.md

@@ -58,6 +58,7 @@ All processing steps are fully parameterized via command-line options, enabling
 A comprehensive overview of the functions and the parameterization can be found at \url{https://tumftm.github.io/PointCloudCrafter/usage.html}
 
 A typical use case is the extraction of LiDAR scans from ROS2 bag recordings, transformation into a global reference frame using an externally estimated trajectory, and aggregation into a static map for offline evaluation. This workflow can be executed in a single batch process while preserving sensor-specific scalar fields required for subsequent analysis.
+
 Early versions of PointCloudCrafter have been used in diverse student research projects, scientific publications [@Leitenstern2025; @Kulmer2025-2], and the creation of datasets [@Kulmer2025-1].
 
 # Acknowledgements