---
license: other
language:
- en
- sk
tags:
- Llama-3-8B
- Qwen3-14B
- Mistral-7B
- 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/lucia-malickova/Behavioral-Reprogramming-of-Open-Weights-Models)

---

## 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.