micm-nlp

A research framework for NLP — the whole pipeline in a single YAML, run alone or in groups. Builds on the HuggingFace stack and adds a layer of features of its own.

pip install micm-nlp

micm-nlp is developed at the Muskhelishvili Institute of Computational Mathematics (MICM), Georgian Technical University.

It has backed two peer-reviewed publications:

  1. Cross-Prompt Encoder for Low-Performing Languages
    Findings of IJCNLP–AACL 2025; ACL Anthology
    Beso Mikaberidze, Temo Saghinadze, Simon Ostermann, Philipp Müller

  2. A Comparison of Different Tokenization Methods for the Georgian Language
    ICNLSP 2024; ACL Anthology
    Beso Mikaberidze, Teimuraz Saghinadze, Guram Mikaberidze, Raphael Kalandadze, Konstantine Pkhakadze, Josef van Genabith, Simon Ostermann, Lonneke van der Plas, Philipp Müller

What micm-nlp offers

Contribution

In short

Answers

Pipeline Unification

unit config → unit run

How do I describe a whole run in one place, and make it reproducible?

Experiment Orchestration

group config → many unit runs

How do I run many variations, and collect their results together?

Features

ready-made functionality

What can I do here that the HuggingFace stack does not already do?

Acknowledgements

micm-nlp was developed at the Muskhelishvili Institute of Computational Mathematics (MICM, Georgian Technical University), in close research collaboration with Teimuraz Saghinadze (MICM), Simon Ostermann (DFKI / CERTAIN), and Philipp Müller (Max Planck Institute for Intelligent Systems), whose joint work on the Cross-Prompt Encoder (XPE) drove much of the framework’s design and validation.

This work was partially supported by the European Union under Horizon Europe project “GAIN” (GA #101078950) and by the German Federal Ministry of Research, Technology and Space (BMFTR) as part of the project TRAILS (01IW24005).

Citation

If you use micm-nlp in your research, please cite the package and (if relevant to your work) the XPE paper that drove its design:

@software{micm_nlp,
  author        = {Mikaberidze, Beso},
  title         = {micm-nlp: a research framework for {NLP} built on {HuggingFace}},
  organization  = {Muskhelishvili Institute of Computational Mathematics, Georgian Technical University},
  url           = {https://github.com/bmikaberidze/micm-nlp},
  version       = {0.4.0},
  year          = {2026},
}

@inproceedings{mikaberidze-etal-2025-cross,
  title        = {Cross-Prompt Encoder for Low-Performing Languages},
  author       = {Mikaberidze, Beso and Saghinadze, Temo and Ostermann, Simon and M{\"u}ller, Philipp},
  booktitle    = {Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics},
  month        = dec,
  year         = {2025},
  address      = {Mumbai, India},
  publisher    = {The Asian Federation of Natural Language Processing and The Association for Computational Linguistics},
  url          = {https://aclanthology.org/2025.findings-ijcnlp.144/},
  doi          = {10.18653/v1/2025.findings-ijcnlp.144},
  pages        = {2380--2393},
}