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mkorob/README.md

👋 Hi, I’m a Computational Linguist

🎓 Graduate in Computational Linguistics from the University of Zurich
🤖 Working at the intersection of NLP, Large Language Models, and Accessibility

I specialize in fine-tuning and evaluating large language models, with a particular focus on making language technologies more accessible, robust, and meaningful.


🧠 Research & Contributions

🧪 DETECT — German ATS Evaluation Metric

📄 Published at EACL 2026

DETECT is the first German-specific metric for holistic Automatic Text Simplification (ATS) evaluation, covering:

  • ✂️ Simplicity
  • 🧩 Meaning preservation
  • Fluency

It is trained entirely on synthetic LLM responses, enabling scalable and consistent evaluation.

🔗 Repository:
👉 https://github.com/ZurichNLP/DETECT/
📌 Korobeynikova, Maria, et al. “DETECT: Determining Ease and Textual Clarity of German Text Simplifications.” Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026.


📚 Open-Source LLMs for Social Scientists

I’m a leading contributor to the first open repository dedicated to fine-tuning large language models for social science research.

🔗 Practitioner Guide:
👉 https://github.com/DigDemLab/OpenSource-LLM-Practitioner-Guide
📌 Alizadeh, Meysam, et al. “Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning”. Journal of Computational Social Science, vol. 8, no. 1, 2025, p. 17.


🛠️ Skills & Expertise

🧑‍💻 Natural Language Processing

  • Text simplification & evaluation
  • Prompting & synthetic data generation
  • Model benchmarking & metrics

🧠 Large Language Models

  • Fine-tuning (instruction & task-specific)
  • Evaluation pipelines
  • Error analysis & interpretability

Accessibility-Focused NLP

  • Plain language & readability
  • User-centered evaluation
  • Inclusive model design

🧰 Tools & Tech

  • 🐍 Python
  • 🔥 PyTorch
  • 🤗 Hugging Face
  • 📊 Evaluation frameworks

🌍 Research Interests

  • Evaluation of LLMs beyond accuracy
  • Accessibility & inclusive NLP
  • Synthetic data for model training and evaluation
  • Transparent and reproducible ML for the social sciences

📫 Let’s Connect

If you’re interested in LLM evaluation, accessibility, or open NLP for social impact, feel free to reach out or explore the repos above ✨

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