From fde509a9a830d890eab6c7b6c73d48ce942cf56b Mon Sep 17 00:00:00 2001
From: daquexian <daquexian566@gmail.com>
Date: Tue, 8 Oct 2019 15:45:08 +0800
Subject: [PATCH] Update README about related works using dabnn

---
 README.md    | 8 ++++++++
 README_CN.md | 9 +++++++++
 2 files changed, 17 insertions(+)

diff --git a/README.md b/README.md
index d776440..4802f0b 100644
--- a/README.md
+++ b/README.md
@@ -80,6 +80,14 @@ For more details please read [our ACM MM paper](https://arxiv.org/abs/1908.05858
 
 Android app demo: https://github.com/JDAI-CV/dabnn-example
 
+## Related works using dabnn
+
+The following two papers use dabnn to measure the latency of their binary networks on real devices:
+
+[IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788)
+
+[Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117)
+
 ## License and Citation
 
 [BSD 3 Clause](LICENSE)
diff --git a/README_CN.md b/README_CN.md
index b90bbc6..236f113 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -82,6 +82,15 @@ dabnn_bireal18_imagenet_stem   43294019 ns   41401923 ns         14     <--- 带
 
 Android app demo: https://github.com/JDAI-CV/dabnn-example
 
+## 使用了 dabnn 的相关工作
+
+这两篇二值网络方向的相关工作引用了 dabnn 并使用 dabnn 测试二值网络在真实设备上的速度：
+
+[IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks](https://arxiv.org/abs/1909.10788)
+
+[Balanced Binary Neural Networks with Gated Residual](https://arxiv.org/abs/1909.12117)
+
+
 ## 开源许可和引用
 
 [BSD 3 Clause](LICENSE)