@inproceedings{tikhonova-etal-2026-standard-transformers,
    title = "From Standard Transformers to {M}odern {LLM}s: Bringing Dialogue Models, {RAG}, and Agents to the Classroom",
    author = "Tikhonova, Maria  and
      Chekalina, Viktoriia A.  and
      Chervyakov, Artem  and
      Zaytsev, Alexey  and
      Panchenko, Alexander",
    editor = {A{\ss}enmacher, Matthias  and
      Biester, Laura  and
      Borg, Claudia  and
      Kov{\'a}cs, Gy{\"o}rgy  and
      Mieskes, Margot  and
      Serrano, Sofia},
    booktitle = "Proceedings of the Seventh Workshop on Teaching Natural Language Processing ({T}each{NLP} 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.teachingnlp-1.8/",
    pages = "41--44",
    ISBN = "979-8-89176-375-3",
    abstract = "Modern LLM education is increasingly centered on system building: grounding generation with retrieval, enabling tool use, and deploying models under latency and cost constraints.We present an updated release of our open course on Transformer-based LLMs and multimodal models (Nikishina et al, 2024).The update introduces topics which became importance since the first edition, namely session on Retrieval Augmented Generation (RAG), a hands-on session on tool-using agents, an API-based track for applied work with LLM, and practical local inference with vLLM.We also add a dedicated session on multimodal dialog models with a focus on dialog grounding. We enriched the course with a discussion on long-context transformers, focusing on KV-cache efficiency along with the related models and benchmarks.All materials are released online."
}