Update README.md

README.md

@@ -8,13 +8,27 @@ tags:
 - Manipulation
 - IA
 ---
-### GOAG -- Checkpoints and Data
+# **GOAG: Generative and Object-Agnostic Grasp Planner for Dexterous Robotic Manipulation** 
 
-See https://github.com/CEA-LIST/GOAG for full code and instructions.
+[Julien Mérand](https://julienmerand.github.io/portfolio/)<sup>1</sup>, &nbsp;&nbsp; [Boris Meden](https://scholar.google.com/citations?user=knXPf8oAAAAJ&hl=fr)<sup>1</sup>, &nbsp;&nbsp; [Mathieu Grossard](mailto:mathieu.grossard@cea.fr)<sup>1</sup>, &nbsp;&nbsp; [Liming Chen](https://scholar.google.com/citations?user=VOPW5YYAAAAJ&hl=fr)<sup>2</sup>
 
+<sup>1</sup>Université Paris-Saclay, CEA-List &nbsp;&nbsp; <sup>2</sup>École Centrale de Lyon, CNRS, LIRIS, UMR5205, Institut Universitaire de France (IUF)
 
 
-Extract the files `ckpts.zip` and `GOAG_DATA.zip`. Your directory tree should strictly follow this structure:
+## 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
+
+[**Project Page**](https://cea-list.github.io/goagweb/) &nbsp;&nbsp;|&nbsp;&nbsp; [**arXiv**](https://arxiv.org/abs/2608.19759)
+
+
+**GOAG** is novel deep generative model that learns a compact latent representation of a specific gripper's contact surface distribution, enabling the efficient sampling of valid grasp configurations without relying on object-specific training data. 
+By introducing object features only at inference time, GOAG can effectively retrieve admissible contact areas that are compatible with the gripper’s capabilities.
+
+
+
+See [https://github.com/CEA-LIST/GOAG](https://github.com/CEA-LIST/GOAG) for full code and instructions.
+
+
+Your directory tree should strictly follow this structure:
 ```bash
 # Model Checkpoints
 GOAG                        # Main folder