Update README.md

README.md

@@ -11,10 +11,11 @@ pipeline_tag: image-to-text
 <sup>1</sup>[ICT-CAS](http://english.ict.cas.cn/), &nbsp; <sup>2</sup>[BAAI](https://www.baai.ac.cn/english.html)<br>
 <sup>*</sup> Equal Contribution, <sup>¶</sup>Project Lead
 
+[[`Paper`](https://arxiv.org/pdf/2312.09128.pdf)] [[`🤗 Demo`](https://huggingface.co/spaces/BAAI/tokenize-anything)]
+
 </div>
 
-We present **T**okenize **A**nything via **P**rompting, a unified and promptable model capable of simultaneously segmenting, recognizing, and captioning objects within arbitrary regions, only relaying on visual prompts (point, box and sketch). The model is trained with exhaustive segmentation
-masks sourced from SA-1B, coupled with semantic priors from a pre-trained EVA-CLIP with 5 billion parameters.
+We present **T**okenize **A**nything via **P**rompting, a unified and promptable model capable of simultaneously segmenting, recognizing, and captioning arbitrary regions, with flexible visual prompts (point, box and sketch). The model is trained with exhaustive segmentation masks sourced from SA-1B, coupled with semantic priors from a pre-trained EVA-CLIP with 5 billion parameters.
 
 ## Installation
 
@@ -50,11 +51,11 @@ Two versions of the model are available with different image encoders.
 @article{pan2023tap,
   title={Tokenize Anything via Prompting},
   author={Pan, Ting and Tang, Lulu and Wang, Xinlong and Shan, Shiguang},
-  journal={arXiv preprint arXiv:2312.yyyyy},
+  journal={arXiv preprint arXiv:2312.09128},
   year={2023}
 }
 ```
 
 ## Acknowledgement
 
-We thank the repositories: [SAM](https://github.com/facebookresearch/segment-anything), [EVA](https://github.com/baaivision/EVA), [LLaMA](https://github.com/facebookresearch/llama), [FlashAttention](https://github.com/Dao-AILab/flash-attention), [Gradio](https://github.com/gradio-app/gradio), [Detectron2](https://github.com/facebookresearch/detectron2) and [CodeWithGPU](https://github.com/seetacloud/codewithgpu).
+We thank the repositories: [SAM](https://github.com/facebookresearch/segment-anything), [EVA](https://github.com/baaivision/EVA), [LLaMA](https://github.com/facebookresearch/llama), [FlashAttention](https://github.com/Dao-AILab/flash-attention), [Gradio](https://github.com/gradio-app/gradio), [Detectron2](https://github.com/facebookresearch/detectron2) and [CodeWithGPU](https://github.com/seetacloud/codewithgpu).