Update README.md

README.md

@@ -16,6 +16,13 @@ language:
 - en
 
 ---
+This is the repo for the paper [PromptCap: Prompt-Guided Image Captioning for VQA with GPT-3](https://arxiv.org/abs/2211.09699)
+
+We introduce PromptCap, a captioning model that can be controlled by natural language instruction. The instruction may contain a question that the user is interested in.
+For example, "what is the boy putting on?". PromptCap also supports generic caption, using the question "what does the image describe?"
+
+PromptCap can be served as a light-weight visual plug-in for LLM like GPT-3 and ChatGPT. It achieves SOTA performance on COCO captioning (150 CIDEr).
+When paired with GPT-3, and conditioned on user question, PromptCap get SOTA performance on knowledge-based VQA tasks (60.4% on OK-VQA and 59.6% on A-OKVQA)
 
 # QuickStart
 
@@ -112,7 +119,7 @@ print(vqa_model.vqa_multiple_choice(question, image, choices))
 ## Bibtex
 ```
 @article{hu2022promptcap,
-  title={PromptCap: Prompt-Guided Image Captioning for VQA with GPT-3},
+  title={PromptCap: Prompt-Guided Task-Aware Image Captioning},
   author={Hu, Yushi and Hua, Hang and Yang, Zhengyuan and Shi, Weijia and Smith, Noah A and Luo, Jiebo},
   journal={arXiv preprint arXiv:2211.09699},
   year={2022}