Remove citation block (paper under review)

README.md

@@ -150,21 +150,3 @@ Derivatives of `Wan2.2-I2V-A14B` (Apache-2.0) referenced in the companion paper
 
 The dataset is fully synthetic. There are no human subjects, no scraped media, and no personal or sensitive information. Known biases inherit from the deterministic generators — every task family covers a deliberately narrow conceptual slice, and visual style is controlled by a fixed renderer family (no demographic content). See [`croissant.json`](./croissant.json) for the complete RAI metadata.
 
-## Citation
-
-```bibtex
-@inproceedings{vbvr_multistep_2026,
-  title  = {Could Video Generation Models Solve Long-Horizon Multi-Step Reasoning Tasks?},
-  author = {Wang, Maijunxian and Zhou, Yifan and Zhang, Alvin and Ge, Jiahui and Wen, Shaoyue and Mei, Lantao and Guo, Lingzi and Wang, Ruisi and Cai, Zhongang and Luo, Dezhi and Lin, Juyi and Ma, Qianli and Huang, Lianyu and Hong, Zelong and Gao, Qingying and Zhao, Tianqi and Hou, Jianheng and Zhang, Danyang and Sun, Haoran and Wang, Runming and Xiao, Weihang and Xing, Hanwen and Jiao, Yizheng and Xu, Pengcheng and Tong, Jingqi and Uzunoglu, Arda and Yu, Fengyuan and Ji, Ran and Zhao, Zehong and Yang, Xue and Khashabi, Daniel and Deng, Hokin},
-  year   = {2026},
-  note   = {Under review at NeurIPS 2026 Datasets and Benchmarks Track}
-}
-
-@inproceedings{wang2026vbvr,
-  title     = {A Very Big Video Reasoning Suite},
-  author    = {Wang, Maijunxian and others},
-  booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
-  year      = {2026},
-  url       = {https://icml.cc/virtual/2026/poster/65709}
-}
-```