Search Results for author: Dmytro Kalpakchi

Found 11 papers, 9 papers with code

Textinator: an Internationalized Tool for Annotation and Human Evaluation in Natural Language Processing and Generation

1 code implementation LREC 2022 Dmytro Kalpakchi, Johan Boye

We release an internationalized annotation and human evaluation bundle, called Textinator, along with documentation and video tutorials.

Collecting Visually-Grounded Dialogue with A Game Of Sorts

1 code implementation LREC 2022 Bram Willemsen, Dmytro Kalpakchi, Gabriel Skantze

We address these concerns by introducing a collaborative image ranking task, a grounded agreement game we call "A Game Of Sorts".

Coreference Resolution Image Retrieval +6

EMBRACE: Evaluation and Modifications for Boosting RACE

1 code implementation15 May 2023 Mariia Zyrianova, Dmytro Kalpakchi, Johan Boye

When training and evaluating machine reading comprehension models, it is very important to work with high-quality datasets that are also representative of real-world reading comprehension tasks.

Machine Reading Comprehension Multiple-choice

SweCTRL-Mini: a data-transparent Transformer-based large language model for controllable text generation in Swedish

1 code implementation27 Apr 2023 Dmytro Kalpakchi, Johan Boye

We present SweCTRL-Mini, a large Swedish language model that can be used for inference and fine-tuning on a single consumer-grade GPU.

Language Modelling Large Language Model +1

Automatically generating question-answer pairs for assessing basic reading comprehension in Swedish

1 code implementation28 Nov 2022 Dmytro Kalpakchi, Johan Boye

This paper presents an evaluation of the quality of automatically generated reading comprehension questions from Swedish text, using the Quinductor method.

Question Generation Question-Generation +1

Minor changes make a difference: a case study on the consistency of UD-based dependency parsers

1 code implementation UDW (SyntaxFest) 2021 Dmytro Kalpakchi, Johan Boye

Many downstream applications are using dependency trees, and are thus relying on dependency parsers producing correct, or at least consistent, output.

Data Augmentation

BERT-based distractor generation for Swedish reading comprehension questions using a small-scale dataset

1 code implementation INLG (ACL) 2021 Dmytro Kalpakchi, Johan Boye

An important part when constructing multiple-choice questions (MCQs) for reading comprehension assessment are the distractors, the incorrect but preferably plausible answer options.

Distractor Generation Multiple-choice +1

[Re] Learning to Learn By Self-Critique

no code implementations30 Nov 2019 Isac Arnekvist, Dmytro Kalpakchi

This work is a reproducibility study of the paper of Antoniou and Storkey [2019], published at NeurIPS 2019.

SpaceRefNet: a neural approach to spatial reference resolution in a real city environment

no code implementations WS 2019 Dmytro Kalpakchi, Johan Boye

Adding interactive capabilities to pedestrian wayfinding systems in the form of spoken dialogue will make them more natural to humans.

Cannot find the paper you are looking for? You can Submit a new open access paper.