diff --git a/README.md b/README.md
index 83640750..2fb18c17 100644
--- a/README.md
+++ b/README.md
@@ -12,6 +12,7 @@
 > *It is built on the excellent work of [llama.cpp](https://github.com/ggerganov/llama.cpp), [bitsandbytes](https://github.com/TimDettmers/bitsandbytes), [qlora](https://github.com/artidoro/qlora), [gptq](https://github.com/IST-DASLab/gptq), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [awq](https://github.com/mit-han-lab/llm-awq), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [vLLM](https://github.com/vllm-project/vllm), [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), [gptq_for_llama](https://github.com/qwopqwop200/GPTQ-for-LLaMa), [chatglm.cpp](https://github.com/li-plus/chatglm.cpp), [redpajama.cpp](https://github.com/togethercomputer/redpajama.cpp), [gptneox.cpp](https://github.com/byroneverson/gptneox.cpp), [bloomz.cpp](https://github.com/NouamaneTazi/bloomz.cpp/), etc.*
 
 ### Latest update
+- [2023/12]`bigdl-llm` now supports [QA-LoRA](python/llm/example/GPU/QLoRA-FineTuning/alpaca-qlora#qa-lora) (see *["QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models"](https://arxiv.org/abs/2309.14717)*)
 - [2023/12] `bigdl-llm` now supports [FP8 and FP4 inference](python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types) on Intel ***GPU***.
 - [2023/11] Initial support for directly loading [GGUF](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF), [AWQ](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/AWQ) and [GPTQ](python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GPTQ) models in to `bigdl-llm` is available.
 - [2023/11] Initial support for [vLLM continuous batching](python/llm/example/CPU/vLLM-Serving) is availabe on Intel ***CPU***.
@@ -161,7 +162,6 @@ Over 20 models have been optimized/verified on `bigdl-llm`, including *LLaMA/LLa
 | Whisper    | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/whisper)   | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/whisper)    |
 | Phi-1_5    | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/phi-1_5)   | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/phi-1_5)    |
 | Flan-t5    | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/flan-t5)   | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/flan-t5)    |
-| Qwen-VL    | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/qwen-vl)   |    |
 | LLaVA      | [link](python/llm/example/CPU/PyTorch-Models/Model/llava)                 | [link](python/llm/example/GPU/PyTorch-Models/Model/llava)                  |
 | CodeLlama  | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/codellama) | [link](python/llm/example/GPU/HF-Transformers-AutoModels/Model/codellama)  |
 | Skywork      | [link](python/llm/example/CPU/HF-Transformers-AutoModels/Model/skywork)                 |    |
diff --git a/docs/readthedocs/source/index.rst b/docs/readthedocs/source/index.rst
index 560905fe..8ebdfbae 100644
--- a/docs/readthedocs/source/index.rst
+++ b/docs/readthedocs/source/index.rst
@@ -24,11 +24,13 @@ BigDL-LLM: low-Bit LLM library
 ============================================
 Latest update
 ============================================
-- [2023/11] Initial support for directly loading `GGUF <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/CPU/GGUF-Models/llama2>`_, `AWQ <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/AWQ>`_ and `GPTQ <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GPTQ>`_ models in to ``bigdl-llm`` is available.
+- [2023/12] ``bigdl-llm`` now supports `QA-LoRA <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/QLoRA-FineTuning/alpaca-qlora#qa-lora>`_ (see `"QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models" <https://arxiv.org/abs/2309.14717>`_).
+- [2023/12] ``bigdl-llm`` now supports `FP8 and FP4 inference <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/More-Data-Types>`_ on Intel **GPU**.
+- [2023/11] Initial support for directly loading `GGUF <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GGUF>`_, `AWQ <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/AWQ>`_ and `GPTQ <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/HF-Transformers-AutoModels/Advanced-Quantizations/GPTQ>`_ models in to ``bigdl-llm`` is available.
 - [2023/11] Initial support for `vLLM continuous batching <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/CPU/vLLM-Serving>`_ is availabe on Intel **CPU**.
 - [2023/11] Initial support for `vLLM continuous batching <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/vLLM-Serving>`_ is availabe on Intel **GPU**.
-- [2023/10] `QLoRA finetuning <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/CPU/QLoRA-FineTuning>`_ on Intel **CPU** is available.
-- [2023/10] `QLoRA finetuning <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/QLoRA-FineTuning>`_ on Intel **GPU** is available.
+- [2023/10] ``bigdl-llm`` now supports `QLoRA finetuning <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/CPU/QLoRA-FineTuning>`_ on Intel **CPU**.
+- [2023/10] ``bigdl-llm`` now supports `QLoRA finetuning <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU/QLoRA-FineTuning>`_ on Intel **GPU**.
 - [2023/09] ``bigdl-llm`` now supports `Intel GPU <https://github.com/intel-analytics/BigDL/tree/main/python/llm/example/GPU>`_ (including Arc, Flex and MAX)
 - [2023/09] ``bigdl-llm`` `tutorial <https://github.com/intel-analytics/bigdl-llm-tutorial>`_ is released.
 - Over 30 models have been verified on ``bigdl-llm``, including *LLaMA/LLaMA2, ChatGLM2/ChatGLM3, Mistral, Falcon, MPT, LLaVA, WizardCoder, Dolly, Whisper, Baichuan/Baichuan2, InternLM, Skywork, QWen/Qwen-VL, Aquila, MOSS* and more; see the complete list `here <https://github.com/intel-analytics/bigdl#verified-models>`_.