Update ReleaseNotes.md (#2837)

### Changes

- Added v2.12.0 template;

### Reason for changes

- Upcoming release;

### Related tickets

- 142565;

#### For the contributors:
Please add your changes (as the commit to the branch) to the list
according to the template and previous notes;
Do not add tests-related notes;
Provide the list of the PRs (for all your notes) in the comment for the
discussion;

---------

Co-authored-by: Liubov Talamanova <[email protected]>
Co-authored-by: Nikita Savelyev <[email protected]>
Co-authored-by: Aleksei Kashapov <[email protected]>
Co-authored-by: Alexander Kozlov <[email protected]>

ReleaseNotes.md

@@ -1,5 +1,47 @@
 # Release Notes
 
+## New in Release 2.12.0
+
+Post-training Quantization:
+
+- Features:
+  - (OpenVINO, PyTorch, ONNX) Excluded comparison operators from the quantization scope for `nncf.ModelType.TRANSFORMER`.
+  - (OpenVINO, PyTorch) Changed the representation of symmetrically quantized weights from an unsigned integer with a fixed zero-point to a signed data type without a zero-point in the `nncf.compress_weights()` method.
+  - (OpenVINO) Extended patterns support of the AWQ algorithm as part of `nncf.compress_weights()`. This allows apply AWQ for the wider scope of the models.
+  - (OpenVINO) Introduced `nncf.CompressWeightsMode.E2M1`  `mode` option of `nncf.compress_weights()` as the new MXFP4 precision (Experimental).
+  - (OpenVINO) Added support for models with BF16 precision in the `nncf.quantize()` method.
+  - (PyTorch) Added quantization support for the `torch.addmm`.
+  - (PyTorch) Added quantization support for the `torch.nn.functional.scaled_dot_product_attention`.
+- Fixes:
+  - (OpenVINO, PyTorch, ONNX) Fixed Fast-/BiasCorrection algorithms with correct support of transposed MatMul layers.
+  - (OpenVINO) Fixed `nncf.IgnoredScope()` functionality for models with If operation.
+  - (OpenVINO) Fixed patterns with PReLU operations.
+  - Fixed runtime error while importing NNCF without Matplotlib package.
+- Improvements:
+  - Reduced the amount of memory required for applying `nncf.compress_weights()` to OpenVINO models.
+  - Improved logging in case of the not empty `nncf.IgnoredScope()`.
+- Tutorials:
+  - [Post-Training Optimization of Stable Audio Open Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/stable-audio/stable-audio.ipynb)
+  - [Post-Training Optimization of Phi3-Vision Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/phi-3-vision/phi-3-vision.ipynb)
+  - [Post-Training Optimization of MiniCPM-V2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/minicpm-v-multimodal-chatbot/minicpm-v-multimodal-chatbot.ipynb)
+  - [Post-Training Optimization of Jina CLIP Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/jina-clip/jina-clip.ipynb)
+  - [Post-Training Optimization of Stable Diffusion v3 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/stable-diffusion-v3/stable-diffusion-v3.ipynb)
+  - [Post-Training Optimization of HunyuanDIT Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hunyuan-dit-image-generation/hunyuan-dit-image-generation.ipynb)
+  - [Post-Training Optimization of DDColor Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/ddcolor-image-colorization/ddcolor-image-colorization.ipynb)
+  - [Post-Training Optimization of DynamiCrafter Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/dynamicrafter-animating-images/dynamicrafter-animating-images.ipynb)
+  - [Post-Training Optimization of DepthAnythingV2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/depth-anything/depth-anything-v2.ipynb)
+  - [Post-Training Optimization of Kosmos-2 Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/kosmos2-multimodal-large-language-model/kosmos2-multimodal-large-language-model.ipynb)
+
+Compression-aware training:
+
+- Fixes:
+  - (PyTorch) Fixed issue with wrapping for operator without patched state.
+
+Requirements:
+
+- Updated Tensorflow (2.15) version. This version requires Python 3.9-3.11.
+- Added NumPy 2.0 support.
+
 ## New in Release 2.11.0
 
 Post-training Quantization: