Model card: NeurIPS 2026 E&D acceptance, authors, citation; set library_name/pipeline_tag/base_model

README.md

@@ -1,6 +1,8 @@
 ---
 license: apache-2.0
-pipeline_tag: text-to-video
+library_name: diffsynth
+pipeline_tag: video-to-video
+base_model: Wan-AI/Wan2.1-VACE-14B
 tags:
   - video-editing
   - text-editing
@@ -12,13 +14,15 @@ tags:
 
 🌐 [Project page](https://vitex-bench.github.io/)  · 
 📊 [Dataset](https://huggingface.co/datasets/ViTeX-Bench/ViTeX-Dataset)  · 
-🧪 [Benchmark code](https://huggingface.co/ViTeX-Bench/ViTeX-Bench)  · 
+🧪 [Benchmark code](https://github.com/ViTeX-Bench/ViTeX-Bench)  · 
 🤖 Model & Inference code  · 
-🏆 [Leaderboard](https://huggingface.co/spaces/ViTeX-Bench/ViTeX-Bench-Leaderboard)
+🏆 [Leaderboard](https://vitex-bench.github.io/ViTeX-Bench-Leaderboard/)
 
 Open reference model for **video scene text editing**. Augments Wan2.1-VACE-14B with a glyph-video conditioning pathway that supplies temporally aligned target-text structure to the editing backbone, fine-tuned on the [ViTeX-Dataset](https://huggingface.co/datasets/ViTeX-Bench/ViTeX-Dataset) 230-clip training split. Replaces the masked scene text in a video while preserving font, color, stroke, shadow, perspective, and the surrounding scene.
 
-> Anonymous release under double-blind review at NeurIPS 2026 Datasets and Benchmarks Track. Author list and DOI updated after deanonymization.
+> Accepted to NeurIPS 2026 E&D Track.
+
+**Authors:** Xinghao Chen, Xiangbo Gao, Jiongze Yu, Yuheng Wu, Zhengzhong Tu ([TACO Group](https://taco-group.github.io/), Texas A&M University)
 
 
 ## Repository
@@ -79,10 +83,11 @@ Apache-2.0 (this code and adapter weights). See `base_model/LICENSE.txt` for the
 ## Citation
 
 ```bibtex
-@misc{vitex2026,
-  title  = {ViTeX-Bench: Benchmarking High Fidelity Video Scene Text Editing},
-  author = {Anonymous},
-  year   = {2026},
-  note   = {Submitted to NeurIPS 2026 Datasets and Benchmarks Track. Author list and DOI updated after deanonymization.},
+@inproceedings{chen2026vitexbench,
+  title     = {ViTeX-Bench: Benchmarking High Fidelity Video Scene Text Editing},
+  author    = {Chen, Xinghao and Gao, Xiangbo and Yu, Jiongze and Wu, Yuheng and Tu, Zhengzhong},
+  booktitle = {Advances in Neural Information Processing Systems (NeurIPS), Track on Evaluations and Datasets},
+  year      = {2026},
+  url       = {https://vitex-bench.github.io/}
 }
 ```