Update README.md

README.md

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 # DarkUnitLab
 
 Research and engineering for reliable, efficient AI systems.
-
 We focus on the path from model experimentation to practical deployment:
 training, evaluation, quantization, inference, and the systems that connect them.
 
@@ -19,35 +18,13 @@ training, evaluation, quantization, inference, and the systems that connect them
 - **Model Training and Adaptation**
   Parameter-efficient fine-tuning, data preparation, reproducible experiments,
   and language and speech model adaptation.
-
 - **Inference and AI Infrastructure**
   Quantization, model serving, runtime compatibility, and deployment across
   GPUs and Ascend NPUs.
-
 - **Multimodal Intelligence**
   Vision-language models, video understanding, evidence-grounded reasoning,
   and retrieval-augmented generation.
-
 - **Language and Speech**
   Cantonese and multilingual language modeling, automatic speech recognition,
   and evaluations that reflect real-world usage.
 
-## Research Practices
-
-We aim to make experimental results inspectable and reproducible through:
-
-- Clear model provenance and attribution to upstream work.
-- Documented evaluation settings, limitations, and failure cases.
-- Explicit distinctions between research prototypes and validated releases.
-- Repository-specific documentation of hardware and runtime requirements.
-
-## Resources
-
-This organization hosts selected research and engineering artifacts.
-
-[Models](https://huggingface.co/models?author=DarkUnitLab) ·
-[Datasets](https://huggingface.co/datasets?author=DarkUnitLab) ·
-[Spaces](https://huggingface.co/spaces?search=DarkUnitLab)
-
-Please consult individual repository cards for availability, access conditions,
-licensing, and intended use.