SpaceRefNet: a neural approach to spatial reference resolution in a real city environment. - Dmytro Kalpakchi; Johan Boye (SIGdial, 2019)

[Re] Learning to Learn By Self-Critique. - Isac Arnekvist; Dmytro Kalpakchi (CoRR, 2019)

BERT-based distractor generation for Swedish reading comprehension questions using a small-scale dataset. - Dmytro Kalpakchi; Johan Boye (INLG, 2021)

Minor changes make a difference: a case study on the consistency of UD-based dependency parsers. - Dmytro Kalpakchi; Johan Boye (CoRR, 2021)

Textinator: an Internationalized Tool for Annotation and Human Evaluation in Natural Language Processing and Generation. - Dmytro Kalpakchi; Johan Boye (LREC, 2022)

Collecting Visually-Grounded Dialogue with A Game Of Sorts. - Bram Willemsen; Dmytro Kalpakchi; Gabriel Skantze (LREC, 2022)

Automatically generating question-answer pairs for assessing basic reading comprehension in Swedish. - Dmytro Kalpakchi; Johan Boye (CoRR, 2022)

Quasi: a synthetic Question-Answering dataset in Swedish using GPT-3 and zero-shot learning. - Dmytro Kalpakchi; Johan Boye (NoDaLiDa, 2023)

SweCTRL-Mini: a data-transparent Transformer-based large language model for controllable text generation in Swedish. - Dmytro Kalpakchi; Johan Boye (CoRR, 2023)

EMBRACE: Evaluation and Modifications for Boosting RACE. - Mariia Zyrianova; Dmytro Kalpakchi; Johan Boye (CoRR, 2023)

Ask and distract: Data-driven methods for the automatic generation of multiple-choice reading comprehension questions from Swedish texts ; Fråga och distrahera: Datadrivna metoder för automatisk generering av flervalsfrågor för att bedöma läsförståelse av svenska. - Dmytro Kalpakchi (2023)

Quinductor: A multilingual data-driven method for generating reading-comprehension questions using Universal Dependencies. - Dmytro Kalpakchi; Johan Boye (Nat. Lang. Eng., 2024)