Update README.md

README.md

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 > This is a public version of the AutoCodeRover project. Check the latest results on our [website](https://autocoderover.dev/).
 
 ## 📣 Updates
-- [July 18, 2024] Added support for fix localization output mode and requirements.txt
-- [June 20, 2024] AutoCodeRover now achieves **30.67%** efficacy (pass@1) on SWE-bench-lite!
+- [August 14, 2024] On the SWE-bench Verified dataset released by OpenAI, AutoCodeRover(v20240620) achieves **38.40%** efficacy, and AutoCodeRover(v20240408) achieves 28.8% efficacy. More details in the [blog post](https://openai.com/index/introducing-swe-bench-verified/) from OpenAI and [SWE-bench leaderboard](https://www.swebench.com/).
+- [July 18, 2024] AutoCodeRover now supports a new mode that outputs the list of potential fix locations.
+- [June 20, 2024] AutoCodeRover(v20240620) now achieves **30.67%** efficacy (pass@1) on SWE-bench-lite!
 - [June 08, 2024] Added support for Gemini, Groq (thank you [KasaiHarcore](https://github.com/KasaiHarcore) for the contribution!) and Anthropic models through AWS Bedrock (thank you [JGalego](https://github.com/JGalego) for the contribution!).
 - [April 29, 2024] Added support for Claude and Llama models. Find the list of supported models [here](#using-a-different-model)! Support for more models coming soon.
 - [April 19, 2024] AutoCodeRover now supports running on [GitHub issues](#github-issue-mode-set-up-and-run-on-new-github-issues) and [local issues](#local-issue-mode-set-up-and-run-on-local-repositories-and-local-issues)! Feel free to try it out and we welcome your feedback!
@@ -38,14 +39,14 @@
 
 AutoCodeRover is a fully automated approach for resolving GitHub issues (bug fixing and feature addition) where LLMs are combined with analysis and debugging capabilities to prioritize patch locations ultimately leading to a patch.
 
-[Update on June 20, 2024] AutoCodeRover now resolves **30.67%** of issues (pass@1) in SWE-bench lite! AutoCodeRover achieved this efficacy while being economical - each task costs **less than $0.7** and is completed within **7 mins**!
+[Update on June 20, 2024] AutoCodeRover(v20240620) now resolves **30.67%** of issues (pass@1) in SWE-bench lite! AutoCodeRover achieved this efficacy while being economical - each task costs **less than $0.7** and is completed within **7 mins**!
 
 <p align="center">
 <img src=https://github.com/nus-apr/auto-code-rover/assets/16000056/78d184b2-f15c-4408-9eac-cfd3a11a503a width=500/>
 <img src=https://github.com/nus-apr/auto-code-rover/assets/16000056/83253ae9-8789-474e-942d-708495b5b310 width=500/>
 </p>
 
-[April 08, 2024] First release of AutoCodeRover resolves **19%** of issues in [SWE-bench lite](https://www.swebench.com/lite.html) (pass@1), improving over the current state-of-the-art efficacy of AI software engineers.
+[April 08, 2024] First release of AutoCodeRover(v20240408) resolves **19%** of issues in [SWE-bench lite](https://www.swebench.com/lite.html) (pass@1), improving over the current state-of-the-art efficacy of AI software engineers.
 
 
 AutoCodeRover works in two stages: