@inproceedings{simov-etal-2026-small,
    title = "Small Can Be Beautiful in {LLM}s for {SSH}: a Case for {B}ulgarian",
    author = "Simov, Kiril  and
      Paev, Nikolay  and
      Osenova, Petya  and
      Valchev, Teodor  and
      Marinov, Stefan",
    editor = "Montejo-Raez, Arturo  and
      Grisot, Cristina  and
      Blochowiak, Joanna  and
      Ljube{\v{s}}i{\'c}, Nikola  and
      Battaner, Elena  and
      Rigau, German",
    booktitle = "Proceedings of Shaping Multilingual, Multimodal {AI} for the Social Sciences and Humanities ({LLM}s4{SSH}) @ {LREC} 2026",
    month = may,
    year = "2026",
    address = "Palma de Mallorca (Spain)",
    publisher = "ELRA Language Resources Association (ELRA)",
    url = "https://preview.aclanthology.org/paragraph-normalization/2026.llms4ssh-1.20/",
    doi = "10.63317/5n9bq7g3it2s",
    pages = "187--197",
    abstract = "In the paper we present a set of small LLM-based models for solving the basic NLP tasks for Bulgarian - POS tagging, Lemmatization, Dependency parsing, Named Entity Recognition, Named Entity Linking, Event Annotation, among others. In order to create fine-tuned models for these tasks, we first pre-train models using architectures like BERT, Modern-BERT, and T5 with different sizes, over Bulgarian data only. For each of the tasks we report our approach towards the fine-tuning, the results from the experiments and also the evaluation. Then we define a way to visualize the results over HTML documents which contain the analyzed texts. Our rationale are as follows: most, if not all SSH research scenarios, need a reliable processing chains that can be customized with respect to the specific needs. These scenarios also would need proper visualization for human observation. We aim to provide such a basic LLM-based toolkit."
}