Update README.md

README.md

@@ -71,6 +71,10 @@ The proposed Q-Bench includes three realms for low-level vision: perception (A1)
 - We are open to **submission-based evaluation** for the two tasks. The details for submission is as follows.
 - For assessment (A3), as we use **public datasets**, we provide an abstract evaluation code for arbitrary MLLMs for anyone to test.
 
+## Release
+- [2/10] 🔥 We are releasing the extended [Q-bench+](https://github.com/Q-Future/Q-Bench/blob/master/Q_Bench%2B.pdf), which challenges MLLMs with both single images and image pairs on low-level vision. More details coming soon!
+- [1/16] 🔥 Our work "Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision" is accepted by **ICLR2024 as Spotlight Presentation**.
+
 ## Close-source MLLMs (GPT-4V-Turbo, Gemini, Qwen-VL-Plus, GPT-4V)
 
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