Add CVPR 2026 acceptance + authors/affiliation + updated citation

README.md

@@ -13,6 +13,9 @@ tags:
 
 # SemanticVLA · LIBERO
 
+> :tada: **Accepted to CVPR 2026.**
+> :black_nib: Fei Ni¹, Zhuo Chen², Yifu Yuan³, Zibin Dong³, Xianze Yao³, Shan Luo², Jianye Hao³, Jiankang Deng¹†, Stefanos Zafeiriou¹†     :school: ¹Imperial College London   ²King's College London   ³Tianjin University     :e-mail: [f.ni@imperial.ac.uk](mailto:f.ni@imperial.ac.uk)
+
 [SemanticVLA](https://github.com/Fei-Ni/SemanticVLA_Offcial) finetuned on the [LIBERO](https://github.com/Lifelong-Robot-Learning/LIBERO) benchmark. The unified OXE LAM is used as the latent-action tokenizer, and the trace + latent-action auxiliary heads are supervised in the VLM's language stream.
 
 ## Headline result
@@ -77,18 +80,11 @@ To run a full LIBERO evaluation, see [`examples/LIBERO/`](https://github.com/Fei
 ## Citation
 
 ```bibtex
-@misc{semanticvla2026,
-  title  = {SemanticVLA: Semantic Vision-Language-Action Models with Trace-Conditioned Latent Action Tokens},
-  author = {SemanticVLA Authors},
-  year   = {2026},
-  url    = {https://github.com/Fei-Ni/SemanticVLA_Offcial}
-}
-
-@inproceedings{liu2023libero,
-  title     = {LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning},
-  author    = {Liu, Bo and Zhu, Yifeng and others},
-  booktitle = {NeurIPS Datasets and Benchmarks},
-  year      = {2023}
+@inproceedings{ni2026semanticvla,
+  title     = {SemanticVLA: Towards Semantic Reasoning over Action Memorization via Synergistic Explicit Trace and Latent Action Planning},
+  author    = {Ni, Fei and Chen, Zhuo and Yuan, Yifu and Dong, Zibin and Yao, Xianze and Luo, Shan and Hao, Jianye and Deng, Jiankang and Zafeiriou, Stefanos},
+  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year      = {2026}
 }
 ```