diff --git a/README.md b/README.md
index c567758a..d3f49c99 100644
--- a/README.md
+++ b/README.md
@@ -11,6 +11,16 @@ The command to install PyTorch is as follows:
 
 ### Recent Updates
 
+Oct 11, 2024:
+- ControlNet training for SDXL has been implemented in this branch. Please use `sdxl_train_control_net.py`. 
+  - For details on defining the dataset, see [here](docs/train_lllite_README.md#creating-a-dataset-configuration-file).
+  - The learning rate for the copy part of the U-Net is specified by `--learning_rate`. The learning rate for the added modules in ControlNet is specified by `--control_net_lr`. The optimal value is still unknown, but try around U-Net `1e-5` and ControlNet `1e-4`.
+  - If you want to generate sample images, specify the control image as `--cn path/to/control/image`.
+  - The trained weights are automatically converted and saved in Diffusers format. It should be available in ComfyUI.
+- Weighting of prompts (captions) during training in SDXL is now supported (e.g., `(some text)`, `[some text]`, `(some text:1.4)`, etc.). The function is enabled by specifying `--weighted_captions`. 
+  - The default is `False`. It is same as before, and the parentheses are used as normal text.
+  - If `--weighted_captions` is specified, please use `\` to escape the parentheses in the prompt. For example, `\(some text:1.4\)`.
+
 Oct 6, 2024:
 - In FLUX.1 LoRA training and fine-tuning, the specified weight file (*.safetensors) is automatically determined to be dev or schnell. This allows schnell models to be loaded correctly. Note that LoRA training with schnell models and fine-tuning with schnell models are unverified.
 - FLUX.1 LoRA training and fine-tuning can now load weights in Diffusers format in addition to BFL format (a single *.safetensors file). Please specify the parent directory of `transformer` or `diffusion_pytorch_model-00001-of-00003.safetensors` with the full path. However, Diffusers format CLIP/T5XXL is not supported. Saving is supported only in BFL format.
diff --git a/docs/train_lllite_README.md b/docs/train_lllite_README.md
index a05f87f5..1bd8e4ae 100644
--- a/docs/train_lllite_README.md
+++ b/docs/train_lllite_README.md
@@ -185,7 +185,7 @@ for img_file in img_files:
 
 ### Creating a dataset configuration file
 
-You can use the command line arguments of `sdxl_train_control_net_lllite.py` to specify the conditioning image directory. However, if you want to use a `.toml` file, specify the conditioning image directory in `conditioning_data_dir`.
+You can use the command line argument `--conditioning_data_dir` of `sdxl_train_control_net_lllite.py` to specify the conditioning image directory. However, if you want to use a `.toml` file, specify the conditioning image directory in `conditioning_data_dir`.
 
 ```toml
 [general]
diff --git a/sdxl_train_control_net.py b/sdxl_train_control_net.py
index f6cc5a4f..67c8d52c 100644
--- a/sdxl_train_control_net.py
+++ b/sdxl_train_control_net.py
@@ -705,7 +705,7 @@ def setup_parser() -> argparse.ArgumentParser:
         "--control_net_lr",
         type=float,
         default=1e-4,
-        help="learning rate for controlnet / controlnetの学習率",
+        help="learning rate for controlnet modules / controlnetモジュールの学習率",
     )
     return parser