Update README.md

README.md

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 ---
-license: cc-by-nc-4.0
+license: other
+language:
+- en
+- sk
+tags:
+- alignment
+- dpo
+- behavioral-reprogramming
+- open-weights
+- hpc
+- llm
+arxiv: 2608.13069
+pipeline_tag: text-generation
 ---
+
+# Behavioral Reprogramming & Persona Alignment in Open-Weight LLMs
+
+Official model card and research overview for the study:  
+**"Behavioral Modification Boundaries of Open-Weight Large Language Models Under Direct Preference Optimization"**
+
+* **Paper:** [arXiv:2608.13069](https://arxiv.org/abs/2608.13069)
+* **Experimental Logs & Code:** [GitHub Repository](https://github.com)
+
+---
+
+## Model & Research Overview
+
+This project provides an end-to-end framework for assertive behavioral reprogramming and persona alignment in open-weight models, executed on large-scale HPC infrastructure (EuroHPC Leonardo).
+
+### Key Technical Highlights:
+* **HPC Scalability:** Validated across tens of thousands of GPU hours with extensive parameter sweeps.
+* **6 Comprehensive Experiments:** Covering learning curves, base vs. instruct divergence, cross-lingual transfer resilience, and persona stress tests.
+* **Direct Preference Optimization (DPO):** Advanced behavioral steering designed for multimodal agents and industrial avatar pipelines.
+
+---
+
+## Access & Commercial Acquisition
+
+The technical reproduction logs, Slurm batch configurations, and verification metrics are open for academic audit on GitHub.
+
+The **fine-tuned model checkpoints, custom LoRA adapters, and proprietary multimodal avatar stack** are packaged for industrial deployment and full IP licensing.
+
+For commercial licensing, enterprise integration, or asset acquisition, please contact the author directly via LinkedIn or registered institutional email.